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Using Sabermetrics for Fantasy Baseball: Ballpark Factors

If you have ever selected a streamable pitcher based on home park or benched an otherwise must-start arm at Coors Field, you already know how much a stadium can impact a player's bottom line.

Ballpark Factors quantify the influence each stadium has, allowing you to make the most of your fantasy team's real-life schedule.

Today, we continue our journey through baseball sabermetrics with a look at how each team's home stadium can play a factor in the fantasy baseball world.


How to Interpret Ballpark Factors

Ballpark factors are generally set to a base of 100 (or 1.000, which doesn't actually change anything), meaning that a park factor of 100 plays perfectly neutral. Factors greater than 100 signify that a given park allows more of that outcome, while numbers below 100 represent less of those outcomes.

There are multiple sources of ballpark factors, including FanGraphs, Baseball Prospectus, ESPN, and Statcorner. Each calculates their numbers a little bit differently, but they all use the base-100 scale listed above. There is no "correct" factor to use, as each system has its own merits. Just make sure you stick to a single source for any analysis to control for the variance.

The source you choose also dictates how much each point above or below 100 is "worth." A player only plays 50% of his games at home, with the rest of his schedule comprised of road games. Some sources such as Fangraphs halve all of their factors to accommodate this, making each point above or below 100 represent a one percent increase or decrease over a full season of stats. Other sources leave that job to you, making every point worth two percentage points in a player's final line.

If that's too confusing, it's fine to forget it. The only thing you need to know is that a park factor of 110 is considerably higher than a 105 mark. It's also important to note that ballpark factors aren't everything. If a particular park has a runs factor of 99, that isn't a strong enough argument to stream a pitcher there absent other compelling reasons.

When most fantasy owners think of ballpark factors, they think of homers. A park allowing plenty of bombs is viewed as a hitter's park, while parks allowing fewer dingers are more pitcher-friendly. Let's consider Guaranteed Rate Field as an example.

The home of the Chicago White Sox is known as a home run haven for good reason. In 2019, the stadium had a Baseball Prospectus HR factor of 106 for right-handed batters and 125 for left-handed swingers. This means that the stadium helps left-handed hitters more than right-handed hitters, creating a meaningful platoon split in how the park plays. Of course, a right-handed hitter with an opposite-field power stroke could benefit like a lefty, and a HR factor of 106 is nothing to sneeze at. The point is that all ballpark factors should be considered with nuance.

While most fantasy owners are familiar with certain ballparks allowing more or fewer homers than others, BABIP is an under-appreciated component of ballpark factors. Altitude, infield conditions, foul territory, batter's eye, and the size of the stadium can all influence how a ballpark plays beyond just home runs.


Coors Canaveral

For example, the Colorado Rockies managed a league-leading .348 BABIP at home last season against a  road BABIP of .292 that ranked second to last. The Rockies have a similar split in every year of their existence, so 2019 was no fluke. Players tend to perform a little better at home, but Colorado's splits seem indicative of more than that.

Indeed, Coors Field promoted more singles (111 for RHB, 108 for LHB per Baseball Prospectus), doubles (121, 104), triples (193, 120), and homers (109, 109) than the average park in 2019. The sample size of triples is usually too small to mean anything, but Coors Field has many quirks to help explain its extreme offensive environment.

It's a gigantic ballpark, offering plenty of real estate for balls to find grass. Pitchers claim that breaking balls behave differently due to the elevation of the Mile High City, removing some of their weapons. Fatigue may set in faster for the same reason. The introduction of the humidor has decreased the ballpark's HR rates compared to the complete bandbox it was at the height of the Steroid Era, but it still consistently posts the highest BABIPs in baseball. For this reason, fantasy owners should generally be skeptical of Colorado hurlers.

Colorado is the most extreme example, but every stadium has some quirk that makes it unique. Fenway's Green Monster, the Trop's artificial surface, and the miles of foul territory in Oakland can all affect a player's fantasy stats.

That said, sometimes ballpark factors can lie. Eighty-one games are a relatively small sample size, so a park could play dramatically differently in a given season than it has in the past or should be expected to moving forward. Some ballpark factors come in three-season or five-season variants to attempt to filter out some of this noise, but it's still something to consider in your analysis.



Ballpark factors quantify how much influence a player's environment has on his final totals. A 100 factor is league-average, with numbers above or below that indicative of more or less of whatever it is a factor for. Most fantasy owners think of homers when considering park factors, but singles, line drives, and even strikeouts have park factors as well. Platoon splits can also dictate where a given player is most likely to succeed. Check out this link for more information on how to use advanced metrics to dominate your leagues.

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WPC+ Videocast: Win Your H2H Points League in 2020!

Pierre Camus and Nicklaus Gaut reveal the right way to rank players for fantasy baseball points leagues. Don't use the same old rankings and tools as everyone else and don't treat it the same as roto 5x5 leagues!

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ADP Surprises

Pierre and Nick break down the right way to do rankings for points leagues and walk through RotoBaller's premium tools for individual platforms. Why are star players like Ronald Acuna Jr. and Adalberto Mondesi less valuable while players like Carlos Santana and Michael Brantley more valuable?

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Thanks for listening to today's episode! Be sure to tune in throughout the week, and to also follow RotoBaller on Twitter, YouTube and iTunes for the latest fantasy news and analysis. We are your secret weapon...

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When and How Do You Target Sleepers on Draft Day?

A popular buzzword this time of year is "sleeper." Every fantasy baseball writer, podcaster, and radio analyst wants you to know why their sleeper is the one you should be targeting on draft day. Conversely, your league mates hope you've never even heard of their sleeper. As I prepared to write this article, I found myself asking this question: If we are all identifying our sleepers individually, don't we need to decide who they actually are in order to determine when and how to target them in the draft?

I worry that we get too caught up in the idea that a sleeper has to be some relatively unknown player no one is talking about and I wonder if that's an oversimplification. If we adhere too strictly to the thought that a guy has to be flying under everyone's radar, we're inadvertently allowing the fantasy community at large to decide who does and does not qualify as a sleeper. In doing so, we're consequently also allowing the community to subliminally dictate our draft strategy. If we're not in charge of choosing who can be considered a sleeper, we're also not entirely in charge of figuring out the appropriate time to draft one. What we should be doing is deciding for ourselves how we feel about each and every player on the draft board.

I propose doing away with the groupthink that has ruled a player has to fall outside a certain ADP range or level of popularity in order to be categorized as a sleeper. Instead, I offer this definition: A sleeper is a player for whom you individually have significantly higher expectations than the consensus does. If you personally feel that any given player is capable of producing well above his average draft spot or preseason ranking, he is one of your sleepers. With this philosophy in mind, join me as I walk you through the process of targeting players you've identified as your own personal sleepers.


How Early is Too Early?

A few notes before we begin: Fantasy leagues come in all shapes, sizes, and formats. This discussion will be based on a 12-team redraft league with rotisserie scoring, a snake draft, and 25-man rosters populated by players from both the AL and NL. Also, any ADP references, draft slot scenarios, or players I mention are simply examples. None of this is meant to be interpreted as exactly what to expect at your draft, as all drafts are going to feature their own unique developments along the way. Finally, all ADP information is courtesy of NFBC.

Because I'm framing this discussion around the idea that virtually any player can qualify as a sleeper, I'm technically of the mind that there is no such time as "too early" to target one. We know that our likelihood of landing any one of the players we're aiming at depends largely on our draft spot, as well as what the rest of our league mates do. That said, the first few rounds of a fantasy draft in any sport are not exactly the time to go rogue. I'm fine with diverging from the pack a little early on, but we should avoid excessive reaches.

So the first thing we want to do is come up with our own customized rankings. Even if we don't have the time or the inclination to sift through upwards of 400 players, we should definitely give ourselves a baseline to follow for at least the first 150 or so. Then we can compare our personal rankings to those of whatever site we're using, and also measure them against ADP information. In doing this, we'll be able to pinpoint players we think are ranked too highly, even in the first couple rounds.

For example, are we worried Juan Soto could take a step back without Anthony Rendon hitting in front of him? Are we concerned about the mileage on guys like Justin Verlander or Max Scherzer? Particularly if we're drafting from a late first-round slot, these are important determinations to make. If we're not totally sold on the players in the consensus 10-15 range, maybe we'd prefer Jose Ramirez and Freddie Freeman slightly further down the draft board with our first two picks.

Though they don't fit the conventional definition of "sleepers," we're already taking the first steps toward bucking tradition. We believe Ramirez and Freeman are capable of outperforming a handful of consensus late first-rounders, and we're not afraid to go and get them. After all, they're most certainly not going to be there in Round 3.


The (Un)Importance of ADP

ADP is useful information to have, but it's not important for the reasons everyone seems to think it is. Fantasy owners with an unwillingness to think outside the box view ADP as a guideline of, "This is when I should draft this player." If your league mates operate that way, let them. In the meantime, we'll be using ADP as a guideline on when everyone else thinks they should draft a player. In turn, we can use that to exploit variances in our own rankings.

To put this idea into practice, consider the following scenario. Eloy Jimenez is currently the 18th outfield-eligible player coming off the board with an ADP of 57.71. But let's say we believe he'll finish top-10 among outfielders, and we rank him accordingly. If everyone else also viewed Jimenez as a top-10 outfielder, he'd have an ADP closer to that of Starling Marte (29.68). Instead, he's being drafted nearly 30 picks later, which allows us to attack the middle ground.

Even though we believe Jimenez to be a top-10 positional value, we know we don't have to pay a top-10 positional price. At the same time, we also know about how early we do need to strike in order to make sure he doesn't wind up on someone else's team. An ADP of 57.71 indicates Jimenez is routinely coming off the board near the end of the fifth round; if we're truly committed to him as "our guy," we can steal him in the late fourth.

During the preparation process and the draft itself, we should always be measuring our custom rankings against ADP and site rankings to seek out these advantages.

Before we continue, I have to emphasize that this part of the process is not bulletproof. Many of us play in super-competitive leagues, and not every single one of our league mates is going to blindly follow site rankings or ADP. We're inevitably going to encounter situations where one of our league mates employs a similar line of thinking as us, and we might end up missing out on a couple of our sleepers as a result. The important thing is to trust what we're doing and not let the occasional tough break derail us. More often than not, taking the time to prepare in this manner is going to work out in our favor.


Reaching for Players: Reckless vs. Calculated

I mentioned above that we don't want to "excessively reach" for sleepers in the first couple rounds, but let's discuss that thought as it pertains to the middle of the draft. As the draft progresses, we can afford to take more risks with our selections because we're not passing up on nearly as much certainty in the middle rounds. But when we're weighing these risks, we need to ask ourselves whether they are reckless or calculated.

Sometimes when we evaluate a player's upside, we get so excited over his best-case scenario that we forget to appropriately consider his floor. Let's say we're super-high on Mallex Smith as a sleeper for 2020. Sure, Smith could steal 50 bases and score 100 runs, but what if he never gets on base to begin with? What if the Mariners never get enough going on offense to put Smith in a position to be a productive fantasy player? Smith becomes (or remains) pretty one-dimensional if things don't break right for him in 2020, which makes him a tough guy to justify reaching for at any point in a fantasy draft.

Unless, of course, we find ourselves greatly in need of some stolen bases, in which case we may feel compelled to take a chance on him. Smith's ADP is 150.81, which places him at about the middle of the 12th round. Maybe we get to the 10th and realize we're strapped for steals, so we nab him up early. Now we're virtually guaranteed 40-plus stolen bases as long as he stays healthy all year, but there's a good chance that's all we're getting.

This is a reckless reach, for one key reason: We allowed our roster's perceived shortcomings in one specific category to drive us to reach for a player with a low floor in many others. The odds of our reach for Smith translating into anything more than a lofty steal total aren't very good. We could theoretically have taken someone much safer like Michael Brantley with that pick. One or two reckless reaches aren't going to torpedo our season, but we want to keep these to a minimum.

As we're going through our custom rankings and labeling guys as sleepers, we should notate whether or not reaching for them would be considered calculated or reckless. In doing so, we'll realize it's probably better to just leave one-dimensional or low-floor players where they are in the rankings and scoop them up at the appropriate ADP if the opportunity presents itself.

A quick example of a calculated reach would be a player like Franmil Reyes (ADP 153.63). Reyes is not going to help us much in a category like batting average, and if he steals a base straight-up in 2020 the opposing catcher should have to take a lap mid-game. But say we went heavy on pitching early in our draft and missed out on a lot of the big bats. Reyes' power is such that he could provide us with first-round homer and RBI stats at a 12th-round price, and the Indians' lineup should be productive enough around him to give him a chance to contribute in runs scored as well.

Grabbing Reyes in the late 10th or early 11th, a couple of dozen picks before his ADP, is a calculated reach. If everything comes together for Reyes, his power ceiling is astronomical. And if he doesn't get there, he's still a solid bet to give us a palatable power floor, which is more than we can say for a lot of other players in this range.


Attacking the Final Rounds

In a 25-man-roster league, our rosters should be pretty well-set after Round 18 or so. We shouldn't ignore the need to supplement our starting lineup with bench depth, but the final seven-ish rounds are also where we can afford to get creative and take some serious gambles.

Austin Riley (ADP 286.32) is being taken, on average, in the 23rd round. He's currently set to split time with Johan Camargo at third base in 2020, but who has the higher upside here? If Riley permanently establishes himself as the player we saw during the first month of his 2019 debut, he could be one of the absolute steals of this year's draft. We shouldn't be afraid to grab a guy like Riley several rounds earlier than his ADP in an effort to capitalize on his ceiling. He's not crushing us by occupying a bench spot early in the year, and he could wind up helping us win a championship in the long run.

As we navigate the final rounds of our draft, we should take a balanced approach. Take a run at a young player with upside, then follow that up with a less volatile pick like, say, Masahiro Tanaka (ADP 225.48) or Brian Anderson (ADP 241.17). Then, our bench will be a nice blend of low-risk and high-reward players.


Final Thoughts

By now, I hope you have an idea how you plan to craft your sleeper strategy for 2020 drafts. Before we part, a few final thoughts.

  • I can't stress enough how important it is to come up with your own rankings. Just this week, I did so myself for one of my leagues and discovered that the site's default rankings had Gerrit Cole as the 60th-ranked player on the draft board. While this is an extreme example for which I admittedly have no explanation, the draft comes at you fast once it starts. The last thing you want is for a player you're targeting to slip your mind because you don't see him on the draft board at the juncture where you'd like to take him.
  • Prospects are great sleepers when drafted appropriately, but avoid stacking your roster with too many. Many of them won't see regular playing time early in the season, which means they'll be occupying your bench for awhile. If your bench is cluttered with guys who aren't playing every day, it limits your overall roster flexibility. Plus, it's more difficult for us to convince ourselves to drop prospects because all anyone talks about is how good they're eventually going to be.
  • Remember: Your sleepers are your sleepers. As long as you're taking a disciplined approach to drafting them, who cares what anyone else thinks of your picks? Get the guys you want within the confines of what can be considered responsible drafting, and more often than not you're going to leave your draft feeling pretty good about your team.

Thank you for taking the time to read this, and I hope it helps. If you have any fantasy baseball questions, feel free to direct them to me on Twitter: @cjoreillyCLE. Happy draft season, and good luck!

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Elite Starters and Pitching Trends Revisited

Last year I wrote a series [Part 1, Part 2, Part 3] on whether we were properly valuing elite starting pitchers. The basic premise was that we were likely to see fantasy-relevant starters (not openers) throw fewer innings again in 2019. I hypothesized that if there were fewer and fewer starting pitchers providing 200 innings of excellent quality, then elite starters were being undervalued, especially in leagues using quality starts.

That research led me to investigate which pitchers were most likely to produce elite seasons. I concluded that pitchers who were coming off an elite season were more likely to return top-tier, if not elite, value. As a result, I argued that those pitchers should be drafted more aggressively than starters going just one or two rounds later. I'm condensing the points a bit, but that was the spirit of the series.

Did those conclusions hold up? I think so, but I’ll let you judge.


Trends in Pitching Use

2019 extended some but not all of the patterns I described last year.

QS% IPS CG Pitchers with 180 IP Pitchers with 180 IP and Above-Average ERA
2013 52 5.89 124 64 48
2014 54 6 118 66 49
2015 50 5.8 104 56 45
2016 47 5.6 83 46 34
2017 44 5.5 59 35 25
2018 41 5.4 42 32 28
2019 37 5.2 45 33 30

Certainly, the expansion of the starter and the increased reliance on bullpens continued to eat into starter innings. Innings per Start dropped from 5.4 (base 10) in 2018 to 5.2 in 2019. Likewise, the number of quality starts dropped from 1,996 down to 1,794, a 10% year-over-year decline.

Conversely, 2019 had three more complete games than 2018, and one more starter who reached 180 IP. This year, it occurred to me to check how many of those pitchers with more than 180 IP were able to maintain an ERA better than league average. It turns out that number increased from 25 pitchers in 2017, to 28 in 2018, and to 30 in 2019. That’s two straight years of growth. Those increases are modest enough that maybe they are an anomaly. Or it may be that despite reduced starter usage, managers and teams have calculated how and when to use starters more effectively. Those increases are minor enough that they aren't a clear reversal in the trend, but they are significant enough to suggest that we've reached the saturation point for relievers and the trend for starters has leveled off or even started to rebound.

One potential reason to be skeptical of that is the addition of the extra roster slot for 2020. That seems like a further opportunity for teams to lean on their bullpen to get through games, especially as more teams focus on load management. On the other hand, teams won’t be able to rely on lefty specialists to carve through perilous sections of an opposing lineup, so maybe we will see managers give more opportunities to their starting pitchers.

At the very least, 2019 was close enough to what I expected that the core concept about the scarcity of top-tier starters held true, but if anything, the situation seems more complicated than it did last season.


Were Elite Starters More Valuable?

Last year, I defined an “elite starter” as a starting pitcher who returned a value of at least $26.88 in a $260, 12-team league while using a 70/30 split. My thoughts on that have evolved some, but I’m going to keep that definition because it’s still functional. I picked the original setup because it offered middle-of-the-road settings with an aggressive hitting-to-pitching split that recognized how most leagues allocate more space and budget to hitters rather than pitchers. Here are the top 20 pitchers for Wins leagues in 2019:

Pitcher Values in W Leagues
Justin Verlander $45.8
Gerrit Cole $42.4
Jacob deGrom $28.7
Zack Greinke $26.0
Jack Flaherty $24.6
Stephen Strasburg $24.5
Hyun-Jin Ryu $24.0
Shane Bieber $21.9
Charlie Morton $21.7
Max Scherzer $20.7
Clayton Kershaw $20.0
Walker Buehler $18.4
Lucas Giolito $17.4
Sonny Gray $16.9
Mike Clevinger $16.3
Mike Soroka $15.3
Luis Castillo $15.2
Patrick Corbin $15.1
Chris Paddack $11.7
Lance Lynn $11.6

And here is that data graphed against previous years:

The 11th through 20th best starters actually improved relative to the top 10, but the stratification that I described last year is still present in this data set.

From the data above, we can see how elite starters were exceptionally more valuable than other starters just a few spots below them. For example, Gerrit Cole ($42.4) was marginally more valuable than Clayton Kershaw ($20) and Walker Buehler ($18.4) combined. That’s confounding to think about, but here's the comparison:

Walker Buehler 182.1 14 17 3.26 1.04 215
Clayton Kershaw 178.1 16 22 3.03 1.04 189
Buehler+Kershaw 360.2 30 39 3.15 1.04 404
Gerrit Cole 212.1 20 26 2.50 0.89 326

Some of the difference is that 212 innings of a 2.50 ERA might not look like it provides twice the value of a 3.15 ERA, but Cole’s ERA value is worth about $7 compared with the $3.50 of value from Kershaw and Buehler’s 360.2 innings of 3.15 ERA.

To illustrate the difference in the stratification between top-ranked hitters and the top-ranked pitchers, here are the top 20 hitters for that same league:

Top-20 Hitter Values
Player Value
Ronald Acuna $46.1
Christian Yelich $44.9
Cody Bellinger $44.7
Rafael Devers $39.4
Anthony Rendon $38.9
Alex Bregman $36.5
Nolan Arenado $36.1
Mike Trout $35.5
Freddie Freeman $35.4
Xander Bogaerts $34.1
Trevor Story $34.0
Mookie Betts $32.8
DJ LeMahieu $31.6
Juan Soto $31.6
Ketel Marte $31.5
Peter Alonso $31.4
Jonathan Villar $31.0
Marcus Semien $30.2
Jorge Soler $28.9
J.D. Martinez $28.6

In Wins leagues, there were 30 hitters between Justin Verlander at $45.8 and Zack Greinke at $26.0.

Meanwhile, Quality Starts leagues had markedly similar results.

Pitcher Values in QS Leagues
Player Value
Justin Verlander $45.7
Gerrit Cole $42.9
Jacob deGrom $34.4
Jack Flaherty $28.7
Hyun-Jin Ryu $26.6
Zack Greinke $26.4
Shane Bieber $24.5
Stephen Strasburg $24.0
Max Scherzer $23.3
Charlie Morton $21.2
Clayton Kershaw $20.8
Sonny Gray $19.3
Walker Buehler $18.5
Patrick Corbin $18.2
Lucas Giolito $17.4
Mike Soroka $16.5
Luis Castillo $15.7
Mike Clevinger $15.3
Chris Paddack $12.2
Lance Lynn $11.2

Surprisingly, 2019 had the closest alignment I’ve seen in pitcher value between QS leagues and Wins leagues. Based on what I saw last winter, I would have expected QS leagues to have an even greater exaggeration in elite-starter value, but in 2019 they had slightly less stratification. I don't have any reason to explain that except for my hypothesis above that teams are finding ways to use their starters more effectively.

We can say with confidence that elite starters were still exceptionally valuable compared to starters just a tier below them. Of the three elite starters in Wins leagues and the four in QS leagues, two were players from the pool of elite starters the year before. The other two were candidates I identified last season.


Do Elite Starters Return Their Draft Cost?

Here things get trickier. Early-round picks provide little opportunity for profit. Managers can either hope that picks return their value in an absolute sense OR that positional scarcity will provide greater profitability over other players at that position.

As I wrote above, the second half of my conclusion was that elite starters were most likely to come from those starters who’d been elite the year before and who had been a top-100 player in the previous season. For 2019, that meant Chris Sale, Jacob deGrom, Max Scherzer, Justin Verlander, and Corey Kluber. The core conclusion that I reached last year was that those five starters were significantly more valuable and more likely to return fair value than those starters going immediately after them. That part turned out to be mostly true.

ADP 2019 Value
Max Scherzer 4.8 $20.70
Jacob deGrom 10.4 $28.70
Chris Sale 12.4 $5.10
Justin Verlander 21.2 $45.80
Corey Kluber 22.8 $0.00
Aaron Nola 24.6 $5.00
Gerrit Cole 26.8 $41.20
Blake Snell 27.8 $0.00
Trevor Bauer 31.0 $0.00
Noah Syndergaard 34.8 $0.00

The five starters did outperform those starters going nearby, but the real story here was that six of the top-10 starters provided $5.10 of value or less. Those top-five starters, the ones who were at least top-100 players in 2018 and then elite in 2019 provided an average value of $20.06 with a median of $20.70. By comparison, starters 6-10 provided an average value of $9.24 with a median value of $0. If you were taking one of the first ten starters off the board, you wanted one of those top-five players. It gave you much higher odds of getting your money's worth out of the player.

The average value of $20.06 for those five starters was still below my expected average of $28.20 for a post-elite starter. Maybe that’s just year-to-year variance. Maybe it is the small sample size of five players with a single year’s data. After all, 2018 did offer the highest number of elite starters (six) at any time in the last eight years. Perhaps it made sense that we would see a correction back to only three elite starters in 2019. Regardless, for elite pitchers, it was the greatest variance in year-after results since 2013, and it’s difficult to look past.

Moreover, the elite starters came from where we expected: Verlander and deGrom were on last year's list, and Gerrit Cole was one of the candidates I tagged as most likely to emerge as an elite starter. For QS leagues, Flaherty was on the list, but the measures weren't nearly as confident in his ascent.


Sale, Kluber, and Snell

Last year, I concluded that previously elite starters were more likely to provide useful (even if not elite) seasons to fantasy owners. That didn't happen for Corey Kluber, Chris Sale, and Blake Snell. Corey Kluber’s 35.2 innings had a net value of $0 while Chris Sale’s injury disrupted 25 starts provided a pitiful $5. Both of those players fell below my 20th percentile outcome of previously elite pitchers. If it happened to only one of them, I’d feel better. However, for two of the five to suffer from that fate, it feels like a distinct loss. Obviously, we're talking about a difference of a single-player season, and maybe just one injury, but it raises questions about the stability of elite pitcher value in comparison to those hitters going near them. I'll address this more at the end.

Blake Snell was a different case, I think fantasy managers had reason to hope he could repeat, and his injury luck feels even more random than Kluber's or Sale's. However, Snell didn't have the previous track record of players likely to be elite starters. Consider Gerrit Cole’s status this season. Compare Cole’s excellent 2018 and elite 2019 to Blake Snell’s mediocre 2017 and elite 2018. Blake Snell exemplifies the type of elite starter who was less likely to repeat with another elite performance. That’s not to suggest that Snell won’t bounce back this season, but his lack of track record didn’t have clear analogs among pitchers who provided elite seasons.

In contrast to Snell, Cole’s two-year combination doesn’t guarantee that he will again offer elite value, but based on the elite starter performances of the last seven years, he and Jacob deGrom are about as safe a bet as anyone in the league.

Justin Verlander is a close third, but the prospect of age regression is awfully steep as he enters his age-37 season. In the seven years of data I’ve examined, only one pitcher was elite at the age of 36, Justin Verlander. To find another example of a pitcher generating an elite season at the age of 36 or older, I had to go back to Roger Clemens at the age of 42 in 2005. Clemen's use of PEDs makes him a problematic comparison, but at this point, I think we can say that Verlander, like Clemens, has had a Hall of Fame career. That makes him exceptional in ways that will defy categorization.



Despite 2019's chaos, we do have relative clarity on where elite starters come from and that those players who offered elite value are more likely than other early-round starters to return their value in the season after. After I had written the first two articles in the series, my editor Alex Roberts referred me to a piece from Ariel Cohen that drew a similar conclusion. I would certainly recommend that piece as well.

The last point I thought about after publishing the series last season was about early-round hitter value compared to early-round pitcher value. Last year Corey Kluber, as the last elite starter off the board, was going as pick number 24, and Aaron Nola was going as pick number 25. That provides us with a simple breakpoint to divide the difference between elite starters and second-tier starters. We can then compare that to the hitters going in that same range. Here's the difference:

 Picks 1-24  25-50 $ Diff % Diff
Pitchers  $ 20.30  $ 8.90  $ 11.40 56%
Hitters  $ 28.50  $ 21.30  $ 7.20 25%

There are different ways to cut up the data for this, but most of the ones I tried gave me similar results. Early round hitters are the safer play, but there is a more significant difference in value between the elite starters versus another starter going just one or two rounds later.

I'm not inclined to make the argument that this means everyone should be rushing out to draft deGrom, Cole, or Verlander. The evidence above could easily be interpreted as a demonstration of why the LIMA strategy is more useful than ever.

In the next article, I'll go into how I'm planning to draft starting pitchers this season. Certainly, I want to get one of those three arms, but I'm concerned about the recent "pocket aces" trend, and my guidance is not as simple as "spend your first-round pick on the best starter available."

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Announcing RotoBaller's New Live Draft Tool

Last season at RotoBaller, we released a set of interactive cheat sheets to help fantasy players prepare for their drafts and the upcoming season. This preseason we have updated these cheat sheets and have also added a brand new Live Draft Tool to give you an edge while drafting in real-time! 

In addition to the Live Draft Tool, we also include players’ performance from the previous season, RotoBaller’s current rankings, and risers/fallers between the first half and second half of last season, as well as hot players down the stretch. This tool is great to use during draft prep, and even better to use during your drafts with the new Live Draft Tool. 

A special shout out to Connelly Doan for building out this Live Draft Tool and interactive cheat sheet, and for working out a way to make this tool useful for live drafts. The goal of this article is to give a brief overview of how to effectively use the Live Draft Sheet during your live drafts. Having a tool backed by RotoBaller’s rankings and projections will help you crush your drafts in 2020!


Live Draft Sheet: What’s In It and How Do I Use It?

The Live Draft Sheet is structured in a fairly simple format to allow users to interact with it quickly during drafts. There are several main aspects. The first is the 2020 RotoBaller Rankings and Projections table.

This table includes a list of player names, positions, RotoBaller’s overall rankings and tiers, NFBC’s ADP values, and our own Nick Mariano’s (2018's Most Accurate MLB Draft Ranker) player projections. It is automatically sorted by RotoBaller’s overall rankings but can be sorted by any of the columns by simply clicking the header for that column.

The next key feature is the Player Search.

This is a list of all players also ordered by RotoBaller’s overall rankings. As players get drafted, you can unclick their names on this list. Unclicking a player’s name will remove them from the Rankings and Projections table. This way, you can see the top remaining players in your draft as you progress through it. You can also search for specific players using the Search feature (enter a player’s name next to the magnifying glass).

Finally, there is a Position Filter at the top right of the sheet.

This filter contains every set of position combinations in the draft pool. For instance, players who are eligible to play third base and shortstop would have a position of 3B/SS. This is important from a fantasy perspective because multi-position eligibility carries value. However, finding all possible combinations of positions could be difficult and time-consuming during a live draft. Fear not, we thought of that!

The position filter contains a search function (next to the magnifying glass) that you can use to expedite this process. Let’s say you’re interested in 1B-eligible players. First, you would uncheck the “Select all” button. Next, you would type in “1B” in the search field. This will pull up all position combinations containing 1B. You can then select each combination by holding Ctrl on your keyboard and clicking all the relevant combinations.

One word of caution - because this Live Draft Tool is browser-based (i.e. it's not a separate application), if you refresh it, the results will reset. So, if you're doing a live draft, do not refresh.



Thus, with just one table and two filters, you can maneuver your way through live drafts quickly and easily with RotoBaller’s rankings and projections!

You can do pre-draft research using the other four sheets and then win your drafts using the Live Draft sheet. The sheet has some instructional text included, in case you need a reminder during your drafts. Good luck this season!

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RotoBaller Friends & Family Industry Mock Draft: What the Experts Were Thinking

The RotoBaller Friends & Family Mock Draft has become an annual tradition where we gather some of the biggest names from the fantasy baseball world and put together a mock draft just as spring training has commenced. Thanks to RT Sports for once again hosting and providing a custom draft site where readers could follow along live at!

This year's participants are a who's who of expert analysts, representing sites such as The Athletic, CBS Sports, USA Today, RotoWire, RotoGrinders, Fantasy Alarm, Fantasy Guru, Fantrax, Fangraphs, Baseball HQ, and, of course, RotoBaller.

After the draft wrapped up, we asked each of the participants to give some detailed feedback on their most interesting draft choices. Their answers may provide insight as to what they were thinking both before and during the draft itself. The 30-second clock in this mock left no time to question strategy or hesitate, so our drafters had to be on their toes! The format was 5x5 mixed roto league, snake draft, and the order randomized an hour before the mock. Here are the full results, along with their reflections.


Mock Draft Results

Click on image for full-screen view


Clay Link - RotoWire

You took several pitchers in the later rounds that are unproven but could break out, such as Jose Urquidy, A.J. Puk, and Dustin May. Do you feel this position is best to take draft-day risks on because of the volatility of starting pitching these days?

I do like to dabble with some potential breakout arms. Blake Snell was a league winner a couple of years back, and while that kind of Cy Young breakout is rare, I see profit potential with Urquidy, Puk and even Sandy Alcantara. I want more proven options at hitter -- with the rare mega-prospect exception -- but there are far fewer sure things on the pitching side and you have to be able to see slivers of upside.

Luke Voit in round 16 was identified as one of the best value picks by many of our participants. Do you expect him to produce enough counting stats to be a starting 1B even though he might be hitting at the bottom of the lineup?

While the Yankees have plenty of options for first base, I expect Voit to secure the primary job this spring. He was doing essentially what I thought he would do last summer before the core-muscle issues popped up. I heard him say he did less powerlifting this offseason, which is probably good because he was a little too big and bulky. Perhaps with a better range of motion with his core, he will be able to go start to finish as a top-10 fantasy first baseman.


Steve Gardner - USA Today

It almost looked like Alex Bregman would fall to the third round before you grabbed him at 2.11. You then took George Springer in the fourth round, Greinke in the sixth, and Brantley in the 11th so clearly you aren't worried about fallout from the Astros scandal. Are fantasy owners overreacting, making some of these players great values?

I didn’t go into the draft with an Astros-centric strategy, but you could draw that conclusion based on my selections of Alex Bregman in the second round, George Springer in the fourth and Michael Brantley in the 11th.  They were just good values at the time.

I think that may be the case more often than not in drafts this year. People generally tend to think they know more than they really do about how things are going to play out. Since we know the Astros were doing something illegal in 2017 (and part of 2018), we want to incorporate that into what we should expect this season. In reality, there’s very little correlation between what happened in 2017 and what will happen in 2020. Whether the Astros’ illegal activities continued into last season and therefore invalidate what they accomplished on offense is something we can never really know. So why factor that into their players’ projected values?

If people are going to discount a four-category, multi-position star like Bregman because they don’t think he’ll hit 41 homers again, fine. But to discount him or Springer or Jose Altuve because they’re going to get booed a lot on the road seems just silly to me. And to discount a batting average lock like Brantley (who just joined the Astros last year) is even sillier. If others are giving me a discount on Astros (and doing so on *pitchers* as well), then I’ll have no problem taking it.

What are your expectations for Miguel Sano this year?

We’ve all seen the downside of Miguel Sano from his .199-hitting 2018 season. But there’s also elite power potential in his bat. Even after missing the first seven weeks of last season, he still hit 34 homers in 105 games. Among players with a minimum of 400 plate appearances, Sano’s 11.2 at-bats per home run ranked fourth in the majors – behind only Mike Trout, Nelson Cruz and Christian Yelich. In terms of hard-hit rate, Sano (52.7%) trailed only Aaron Judge. But if you’re looking at overall season leaderboards, you’re not going to see Sano’s name among the qualifiers because of his late start.

Add in Josh Donaldson to this year’s Twins lineup and there’s no easy out in the bunch. Plus, Sano is going to be even more valuable because he’ll gain in-season fantasy eligibility at first base.  To get him in Round 10 with the 119th overall pick seems like a pretty good value to me. In fact, I think I may need to move him up in my rankings.


Ray Murphy - Baseball HQ

You took a trio of starters early on (Sale, Kershaw, Clevinger) that could make your rotation the best by far of this group, but each comes with serious injury concerns. You didn't take your next SP until the 15th round. Is this all-or-nothing approach something you would attempt if this weren't a mock?

Well, I was comfortable with the Sale/Kershaw combo, but ended up getting Clevinger because I timed out. (That 30-second clock was rough!). So I didn't really want three SP in my top-five picks. But once I had them, I decided to steer into that and work on my offense (and closers) for a while before getting back to SP. I can't vouch for how this would have worked out if we played it out... but honestly, it would have been pretty interesting.

Landing Mike Trout at the third spot is a luxury a lot of owners might have in 2020. Given the choice, do you prefer a top-three pick?

I was a big fan of a top-three pick until a couple of weeks ago. Now, with the injuries to the likes of Clevinger, Severino, etc, the SP options coming back at the 2-3 turn are going to be pretty thin. That's fine with me, as I'm generally comfortable waiting a little longer to get my first SP. But if you have a top-three pick, there are going to be some team-construction issues that come with those slots now.


Derek Carty - RotoGrinders

With the fourth pick, you struck first at the pitcher spot with Gerrit Cole. THE BAT projects some regression for him at a 3.07 ERA, 1.05 WHIP, and just under 300 K. Why does this make him more valuable than players like Betts or Bellinger.

It's less about Cole himself than about top-tier pitchers in general.  For years, the math has supported the ace pitchers being more valuable than they get drafted as. If you run THE BAT, Steamer, ZiPS, and ATC through the FanGraphs Auction Calculator, every single system has the top pitcher as either the most valuable (ahead of all hitters) or the second-most valuable player on the board. Conventional wisdom has it that pitching is "too risky" and so you can't spend an early pick on, but that's faulty logic. The top pitchers are much safer than people assume (especially relative to whatever hitters are being taken early because they had one great year, which is dumb and carries plenty of risk too), even if you care about safety (which I don't). The old logic is that it's better to wait until the later rounds and find the diamonds in the rough. This is great in theory, but it's not as if we know those late-round steals ahead of time, and people tend to have too much confidence in their ability to do so. Middle-round pitchers, especially that second and third tier, tend to be terrible investments. From a value standpoint, the elite pitchers each year are worth extremely early picks, and they get underdrafted as a result. Cole at 4 is strong value.


Howard Bender - Fantasy Alarm

You were the last one to take a starting pitcher, waiting until round 6 to make Aaron Nola your SP1. Was this an intentional strategy or did you simply feel the value wasn't there to take a pitcher earlier?

Waiting on starting pitching was part of my plan/strategy heading in. With a strategy that focuses more on saves and steals, it was more important for me to attack the offense first. I would grab my steals early and splash in some power while waiting to see what was left for me at pitching. I thought about making a move in Round 5, but after seeing names like Paddack, Syndergaard, Nola, Greinke and Giolito on the board, I knew I could wait one more round. The strategy allows me to discount ERA, as my closers will help fix that, so my focus for starters was on strikeouts. Nola is a 200+ K guy who should improve on last year's numbers and Trevor Bauer (Round 8) was the same, in my opinion. I don't feel like I sacrificed pitching by waiting and, in fact, allowed me to augment my power with the Matt Olson pick, so according to my strategy, it all went very well for me.

It seems you made a point of securing steals and saves early. How important is it to get an advantage in these categories on draft day?

It's like the late-90s all over again. Power is all the rage because "chicks dig the long ball" and stolen bases are down. The closer position, while still volatile, saw fewer guys lose their job in 2019 than we had seen in the previous three seasons. If power is abundant and can be found everywhere, then why not make that early move for speed? And while everyone is freaking out about all the starters coming off the board, you can stay focused on steals/more offense. Then while everyone is then scrambling for the next tier of hitters, I can grab the top closers and high-strikeout starters. The key is to bulk up on the two categories to the point where you know you will be able to trade later in the year while still maintaining your position in the standings. They are, traditionally, the two categories you can move up the most in for roto leagues and everyone will be looking for both in the second half. Fantasy championships are not won on draft day. In-season management is paramount and having a strategy that carries you through the full six months and not just the first half is key.


Vlad Sedler - Fantasy Guru

A couple of big-name players, Giancarlo Stanton and Manny Machado, fell to you in rounds 5 & 6 respectively. Do you feel they are being discounted too much by fantasy owners or is this a fair range for them to fall?

It's amazing what a difference a year makes. Both were easy second-round selections this time last year. The fall of Stanton and the concern with him is warranted given his injury history. But it is worth noting that he had consecutive seasons in 2017 and 2018 with no health concerns, a minimal one in 2016 and appears fully recovered from last year's ailments. Machado's drop in ADP is a bit more surprising, especially since he's been the modicum of health and leads the majors in plate appearances over the past five years. As I did in the RotoBaller mock, I'm willing to take a shot at these two guys at current price in all my drafts this spring in hopes of a return to glory.

You took a pair of young Rockies in Garrett Hampson and Ryan McMahon in the middle rounds. What do you realistically expect from them this year?

When in doubt in the middle or late rounds, draft a Rockies hitter. At least that is what happened with my selection of McMahon. Not someone I am going out of my way to target, although he did have a nice rookie season and can certainly build on last year's success. With Hampson, it's simply a case of 'I can't quit him'. At least, not yet. The Rockies are known to stall and ruin the progress of their good prospects and we just have to hope that won't be the case with Hampson this year. He is one of the league's fastest players and could easily swipe 30-plus with at least 500 PA and half his games at Coors Field.


Pierre Camus - RotoBaller

You took Marcell Ozuna at 79 overall, 20 spots higher than his current NFBC ADP, opting for him over outfielders like Tommy Pham and Luis Robert who also bring speed to the table. Explain that pick.

A couple of minor injuries hampered Ozuna the last two years in St. Louis, but moreover he just never seemed to fully fit in. Despite this, he still posted elite Statcast numbers with a .548 xSLG, .382 xwOBA, and 49.2% hard-hit rate in 2019. A move to Atlanta gives him slight upgrades in ballpark and lineup support. Busch Stadium was third-worst in HR factor for right-handed batters at 91, whereas Atlanta's Truist Park was right around league average at 99 last year. Atlanta ranked ninth in team average and seventh in runs scored, while St. Louis was 23rd and 19th in those categories respectively. A healthy Ozuna should easily exceed 30 HR, 90 RBI, and finish with an average closer to his .288 xBA. Pham and especially Robert don't have the same floor at multiple categories. Plus, I wasn't too worried about speed because I had just taken Victor Robles I knew I could make up for that category later on at a discount with guys like Tim Anderson and Mallex Smith.

The last 10 rounds of your draft are mostly filled with young players, many of whom are considered sleepers in 2020. Do you shoot purely for upside at this point rather than filling your bench with high-floor veterans?

I consider it upside with a safety net. I take young players who are set to have a big role on their team and are fairly certain to start, but haven't yet completely proven themselves. Mitch Keller, Griffin Canning, and Tyler Beede should have rotation spots secured and each is a top pitching prospect for his team. Mike Yastrzemski and Trent Grisham are also set to start in the outfield and can contribute across multiple categories. The one player I am most skeptical of is Aristides Aquino because he could be in a logjam with the Reds' situation and might find himself optioned back to the minors. He also has 30-HR upside and has already tasted success in the majors, so it's worth a shot at that juncture.


Nando Di Fino - The Athletic

A couple of years ago, we expected Carlos Correa and Byron Buxton to be perennial fantasy studs. You secured them both in rounds 10-11. How do you weigh risk vs reward when picking players like these?
I think by that part of the draft, you have to take a shot. Correa is going to have depressed value because we're all human and hate the Astros, but he's somehow avoided the scorn that Altuve and a few others have. Although in pure baseball terms, I'm banking on him not being hurt this year. Hopefully, he gets 150 healthy games in and returns to form.

Buxton is still only 26 and still doesn't have that 475 at-bat season. Once we hit these double-digit rounds, you have to weigh the risk of injury against the potential. And if this is the year he comes in, stays healthy, and gets 40 steals.. awesome. I'm in for that. If he doesn't, I think the downside here is greater than Correa's, as Correa has at least shown some BA skill in the past and I can maybe get .280 out of him, even in a bad season. Buxton seems capped, to me, at around .265 (although a new hitting coach might change that).

Were you surprised Shohei Ohtani fell to round 8 and are you worried about an innings limit on the pitching side?

I really was, especially in this format where there's only one Ohtani. And I'm not worried... I guess I'm "cognizant" of it. I read that there might be a loophole where he can bat, then get optioned for a rehab pitching start, then come back up and hit again. So as long as I have the bat side in the lineup for a while, I'm content. Once he starts pitching, it'll be like trading for a starter, but giving up nobody, as I can keep the bat whenever I want it in there, too. I like the flexibility, basically. And to be totally honest, it makes things a little more fun.


Ariel Cohen - Fangraphs / RotoBaller

Why are you confident that Juan Soto is worth the ninth overall pick in favor of guys who provide more speed like Turner/Story or taking an ace like Scherzer/Verlander.

I don’t think about Soto as the “9th overall pick.” My selection of him had to do more with the options available to me at the time. As per my recent article on Finding Combo Value Players Using Z-Score, Juan Soto has four projected categories with a Z-Score of over +1.00, and the fifth category (SB) is still above the pool average. That’s a great skills composition.

I don’t feel that you NEED to take a speedster in the first round. I think that it is more important to bank reliable stats. Soto will get that bank, PLUS he will get double-digit swipes. Shortstop is a very deep position this year. I’d rather take an OF early on if similarly priced. In 12-team leagues, I don’t feel the need to take a starter in the first round, as the waiver wire will be tapped quite a bit. I would have taken Cole/deGrom if they fell to me, but for Verlander/Scherzer -  I have a small fear of injury/age issues and it bumped them below Soto.

Since you are the man behind ATC projections, I'm curious which of your mid-to-late-round picks were data-driven decisions based on potential earnings and which were "gut feel" picks?

Franmil Reyes to me was pushed up via “gut feel.” Projections see him as a mid-30 HR player, but I would be the over on projected totals, and 40-45 HR are in play. Same with Rougned Odor. I think he’s a 30/10 player who’s BA projection is far too light. Eric Hosmer was a data-driven decision. His value was immense for the round selection. He actually came up as the most valuable player to take about 1-2 rounds prior. Renato Nunez was also data-driven. ATC projections are high on him – and I went with the numbers for his selection!


Chris Towers - CBS Sports

You went the discount closer route with Giovanny Gallegos and Wade Davis and only one expert waited longer to take a reliever. Do you make it a point to de-prioritize saves on draft day?

My strategy this year is to either target bounce-back candidates — Edwin Diaz and Craig Kimbrel, primarily, but also Sean Doolittle — or to wait as long as I can. In Davis and Gallegos, I managed to acquire relievers with two very different concerns: Davis has the job for now, but may be washed up; Gallegos certainly seems to have the skill, but may not have the job. However, given that you can expect roughly half or more of all Opening Day closers to lose their job at some point in any given season, it just doesn't make much sense to invest much in the position, especially in a year when many of the "safer" options have limited track records of viability.

Do you worry that players who broke out last year like Ketel Marte, Josh Bell, Lucas Giolito, and Jorge Soler could face serious regression this year?

Of course, I'm always concerned about that — "Don't pay face values for career years" was one of my guiding principles when looking for bust candidates for 2020. However, in the case of each of those players, I got them at enough of a value that I'm not so worried about it. Marte was the No. 13 hitter in Roto last season; Bell was No. 38; Soler was 23. At those costs, you've baked in a lot of the regression, it seems to me. I could quibble with some of the picks — Bogaerts instead of Marte might be the one I'd consider re-doing if I could — but overall, I think those players are probably being penalized too much coming off seasons where they each appear to have made significant changes to their underlying skill sets.


Eric Cross - Fantrax

The early part of your draft was highlighted by three straight young White Sox hitters in Moncada, Jimenez, and Robert. Are your expectations sky-high for this offense in 2020?

They are. The plan going in wasn't to necessarily load up on White Sox hitters, but the values all seemed about right. Moncada seemed to turn a corner in 2020 and Eloy absolutely dominated to end the season. I'm really expecting big things from them in 2020 to go along with a potential 20/25 season from Luis Robert as well. As long as he can keep the AVG respectable, the value should be there due to the power/speed.

J.D. Davis is a player whose ADP keeps rising, as he is increasingly being viewed as a sleeper to target. Can last year's Statcast numbers be duplicated and is playing time a concern at all for you?

Davis seems to be everyone's darling this year. But we're now at the point where it's fair to ask if his ADP has risen to the point where it will be difficult for him to return a ton of value. When I look at the underlying metrics and Statcast data, nothing screams big regression coming in 2020. But then again, is there more room to improve and really turn a profit? As for the playing time, I'm not too concerned. I think the ABs will be there between the outfield and third base to keep his bat in the lineup daily. To sum it up, he's legit, but the ADP is rising a little too high for my liking now.


Nick Mariano - RotoBaller

You passed up a chance to take Scherzer or Verlander at the turn, opting for offense instead. Explain your thought process early on.

The bulk of my drafts usually yield one starting pitcher in the first two rounds, so I wanted to explore hitter-hitter given my lowly 12 draft slot. In my mind, the top 11 are fairly set. Come 12, and this goes for 15-teamers and so on, I can go many directions and not feel a loss of value. I don't love Scherzer or Verlander enough to forgo building offense in this power-happy era. I do love my ability to piece together a formidable pitching corps in a 12-teamer with mid/late relievers, where I don't need a Scherzer/Verlander as much as I need the offense.

With elite first basemen who won't hurt the BA thinning quickly, I opted for Freeman. Then Ramirez could be a top-five pick next year if he proves the average can return and irons out some streakiness. Either way, the speed is there without sacrificing power or overall offensive ceiling. I can't cobble that together late in the draft without opportunity cost drowning me, as opposed to making it work with the pitching categories.

Many of your hitters fall into the HR+SB or BA+HR+SB cohort of our Expected Draft Value system (Ramirez, Meadows, Hiura, Laureano, Danny Santana). Are "combo" players the best way to attack a draft rather than focusing on category specialists?

I do love me some combo meals. In general, I would rather spread my production across as many players as possible. If I'm banking on 50 steals from Adalberto Mondesi and then that shoulder injury destroys his 2020, I'm in a deep hole. Whereas, if one pillar out of six falls, the other five can hold the roof up. I wouldn't say this is the best way to attack a draft, but I believe it's a strong strategy if you didn't get a top-10 pick. There's no replicating a Mike Trout, scientists have tried and failed, so I need to be sure I make up for not having a peak five-tool guy with skills across the board. No freeloaders here, you have to earn your roster spot!

More 2020 Fantasy Baseball Draft Strategy

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H2H Points League Draft Strategy

Points leagues are essentially the rawest version of fantasy baseball. These are not players, these are stat-lines and you want to put up as many points per week as possible. Do not get too attached to underperforming players who have name-value and potential.

There is a stark difference in draft strategy when it comes to leagues with H2H/roto styles versus points. Rather than focusing on an array of categories, points leagues are a simpler, more direct version of fantasy baseball. Players with deficiencies in any particular category can overcome them by performing extraordinarily in others.

Unlike roto leagues where heavy home-run hitters can be forgiven for poor averages, there is typically no singular category acting as a saving grace for players. Everything you need in the player is averaging out, and being spit into one number weekly and if that number is not satisfactory, they may not be worth holding onto after a few months.


General Points League Strategies

Let's begin with the most important point - knowing your league's settings matters more than anything. If doubles are weighted relatively close to home runs, you can circumvent missing out on big power guys by focusing on strong hitters who are not as flashy. Quality starting pitchers running thin as the draft goes along? No problem, just draft guys with high strikeout percentages that can compensate for shorter outings and/or high walk rates if strikeouts are weighted disproportionately. Study your league's settings and become comfortable with the idea that you may be zigging while your league-mates zag.

Someone like Aaron Judge or Giancarlo Stanton sounds appealing come draft day given their big power ability and notoriety, however many points leagues penalize hitters for strikeouts. Given their tendency to whiff often, it may not be prudent to invest early on in such hitters and allow someone else to make that mistake. Other hitters of note who may fall in the same realm include Matt Olson, Joey Gallo, Jorge Soler, and Eugenio Suarez.

Of course, any player could be the right player, assuming you get him at the right price. Almost every database you can draft from is flawed in some manner. There are inefficiencies galore in player pricing/ADP. End-of-bench pieces who should be drafted in the top-200 can be found at the bottom of the barrel in the 300-400 range. Digging for players coming off of down/injured years is the best way to navigate this for the most part, but also, using your knowledge of your league's settings, you can find random hitters who happen to have high averages and don't strike out a lot but fail to put up typical counting stats. These players' ADPs are in the sunken place due to it.

Someone like Luis Arraez, for example, will not be the most popular asset in rotisserie formats given his lack of home runs and RBI but because he can get on base consistently and not mess up, he could be a valuable points league option. Andrelton Simmons is another unsexy name who can consistently provide great value in points leagues given his minuscule strikeout rate and propensity to hit. Diamonds can always be found in the rough of points leagues given that they are not as popular as roto or H2H categories leagues and therefore, strategies are discussed far less online.

The biggest mistake to avoid is taking a speedster like Adalberto Mondesi or Victor Robles too early. Their ADP is inflated because of the rarity of SB nowadays. Do not fall for this ADP trap. Their per-game average will look like hitters you can nab deeper in drafts unless stolen bases are weighted heavily, in which case, they would be worth the pick. Again, know your settings.

Pitchers are not too complicated to navigate. In fact, they are more valuable and the good ones are easier to identify. Streaming pitchers is also less painful than it would be in other formats. Mediocre performances still oftentimes lead to at least positive point gains rather than painful hits to multiple ratios. The occasional negative performance may sting but you can usually recover if you have reliable innings-eaters and/or pitchers who can collect strikeouts.


Host Website Variance

From format-to-format, there are different weights placed on hitters versus pitchers, even deeper, there are differences from website to website.


ESPN's standard scoring format weighted a fair mix of hitters and pitchers at the top of their rankings, however, the top-two scorers, Houston's Justin Verlander and Gerrit Cole outscored the next highest scorer, Alex Bregman, by over 100 points each. That is a massive margin akin to how Christian McCaffrey who outscored the RB2 in 2019, Aaron Jones by nearly 200 points. This means that while ESPN does not have too much bias in their scoring settings if you hit on the correct aces in any particular year with their scoring settings, you should have a much better shot at winning making those top-end starters not only anchors but also lottery-tickets.


Fantrax's scoring settings allowed for Cole and Verlander to remain atop their leaderboards. However, the next 23 players on the board were all hitters, and those just behind the pitchers were hardly even behind compared to ESPN. The takeaway here is that while starting pitching still has value, it is best to go into drafts with a hitter-heavy approach and wait on pitching, or punt it all together and take a heavy streaming approach as to not miss out on any potential top-25 hitters.


On Yahoo, the top-nine individual points leaders were all starting pitchers. Unfortunately, according to fellow RotoBaller Nicklaus Gaut (@Nt_BurtReynolds), Yahoo is undergoing a massive change in their points settings for 2020 and presumably beyond which would require you to familiarize yourself with a new system, rendering these old rankings useless.

The point remains that every website is different and you should know what you're getting into beforehand. It is little edges like this that help you consistently win your leagues (along with paying attention to the waiver wire in a laborious fashion, unfortunately).

The best strategy is to roll with the best player available come draft day. That does not mean going with whoever is at the top of ESPN/Yahoo/Fantrax's ADP but finding good projections for 2020 (conveniently available in RotoBaller's Draft Kit) and using your own intuition to grab the players most likely to produce consistently. Best of luck!

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Using Sabermetrics for Fantasy Baseball: Expected Stats

Statcast is a valuable tool for fantasy analysis, and it can be easy to look at a stat called "Expected Batting Average" and blindly use it as your projection moving forward. Of course, proper use of these metrics is a little bit more nuanced than that.

First, a disclaimer: This article is about the "Expected Stats" found on Baseball Savant. It is not about the various "xStats" developed by fantasy analysts such as Mike Podhorzer or used in projection systems such as Ariel Cohen's ATC. Those tools have value, but any attempt at an in-depth analysis of them would involve far more math than the average fantasy owner is interested in.

With that out of the way, let's begin by identifying what the Expected Metrics are and how they work.


How To Use Statcast's Expected Metrics In Fantasy

The first is xBA, or Expected Batting Average. This statistic is calculated using Hit Probability, itself a stat measuring how often a batted ball with a particular exit velocity and launch angle has fallen in for a hit since Statcast was introduced in 2015. For example, a line drive to the outfield that has historically fallen in for a hit 80 percent of the time counts as 80% of a hit by Hit Probability. xBA is simply a batting average produced using Hit Probability, actual K%, and official ABs. If you play in a traditional 5X5 roto league, this is the Expected Stat you'll probably use the most.

As of January 2019, the Hit Probability formula was modified to include the batter's Statcast Sprint Speed, more accurately representing his ability to beat out a ground ball. That said, the adjustment feels like it may be too light in certain circumstances, so you may still want to make a slight adjustment upward for true jackrabbits.

Next up is Expected Slugging Percentage, or xSLG. It is calculated in the same manner as xBA, except that each batted ball is weighted according to its probability of being a single, double, triple, or home run instead of just a hit. If your league counts slugging percentage, you might get good use out of this stat.

Finally, we have Expected Weighted On Base Average, or xwOBA. It is calculated the same way xSLG is, except real-world walks and HBP are added to the equation. Each result is also assigned a linear weight with more math than the simple multiplication used to calculate slugging percentage. This is the stat with the most real-world value, but doesn't translate that well to fantasy unless you play in a realistic Points format.

The principal value of all three metrics is to take both luck and defense (and therefore actual results) out of the picture, allowing a player to be judged solely on his contact quality.

We'll assume that you play 5x5 roto and stick with the simpler xBA from here on out. Generally speaking, a player who posts a higher xBA than actual batting average would be expected to improve his average moving forward, while the opposite is true if a player's batting average is higher than his xBA.

Baseball Savant's Leaderboards allow you to sort players by the difference between their BA and xBA, so finding some samples is easy. Fernando Tatis Jr. of the San Diego Padres had the largest negative differential in 2019, posting a .317 average against an xBA of just .259. Tatis probably figures to beat his xBA based on the speed caveat noted above, but it is something to think about before spending a top draft choice on him in redraft formats.

Going the other way, Marcell Ozuna posted the best positive differential with a .288 xBA against a .241 actual mark. These advanced stats don't understand that certain players are more susceptible than others to the shift, so you should check those numbers before you blindly project improvement. In Ozuna's case, he performed roughly as well against the shift (.255 average) as he did without it (.258), so he looks like a nice bounceback candidate.

Pitchers illustrate another problem with xBA. Zach Plesac of the Cleveland Indians was the "luckiest" pitcher according to the metric in 2019, posting an xBA of .288 despite a batting average against of .241. The metric doesn't consider a defense behind a pitcher, however, so Francisco Lindor's outstanding 11 Outs Above Average could help Plesac sustain such a gap moving forward.

League-wide, major leaguers posted a .252 batting average and .250 xBA in 201, a two-point differential that has declined in each year of Statcast's existence. This trend suggests that the technology is getting better, but also that it isn't foolproof. It is always best to utilize Statcast Expected Stats as part of a broader analysis, rather than using them as your sole data point.



In summation, Expected Stats allow you to evaluate a player's performance based on his exit velocity and launch angle, taking variables such as the opposing defense out of the calculus. This can give you a better sense of a player's true talent level, but there are limitations on what you can do with it. Check out this link to brush up on other metrics you can use in your fantasy draft prep.

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Using Sabermetrics for Fantasy Baseball: Pitcher Statcast

Statcast metrics such as Barrels and Brls/BBE are great ways to evaluate a batter's performance, so it is only natural to assume that the metrics would be predictive for pitchers as well. As much as batters want to hit a Barrel every time, pitchers want to avoid them at all costs. Yet there is evidence that pitchers do not have the same influence over Barrels as a batter does.

Jorge Soler of the Kansas City Royals finished with a league-leading 70 Barrels hit last year. Mike Leake led MLB pitchers by allowing 59, a significantly lower number than Soler's total. Neither performance was an outlier, so it seems to take fewer Barrels to lead pitchers in Barrels given up than it does to lead hitters in Barrels hit. This fits well with DIPS theory, which states that batters can do more to influence batted balls than pitchers can.

It's also not fantasy-relevant, as Mike Leake just isn't that appealing a fantasy option. The nest five names on the leaderboard consist of names with a wide range of fantasy viability: Rick Porcello (55), Merrill Kelly (53), Madison Bumgarner (53), Patrick Corbin (49), and Shane Bieber (48). There isn't a compelling reason to group these guys together for fantasy purposes. Are these numbers indicative of anything?


How to Interpret Statcast Contact Quality Allowed

Bieber is by far the biggest name on the list above, so let's focus our analysis on him. He allowed his 48 Barrels in 554 batted ball events for a rate of Brls/BBE of 8.7% last season. Back in 2018, Bieber allowed 24 Barrels in 342 batted balls for a Brls/BBE of 7%. These metrics completely contradict the popular perception of him, as he was hit hard in 2018 (4.55 ERA despite 3.30 xFIP) before living up to his peripherals last season (3.28 ERA, 3.23 xFIP). His Statcast metrics failed to capture his fantasy line.

Using the Brls/BBE leaderboard might seem like a better bet than raw Barrel totals, but again we find a contradictory example within the top five. David Hess (13.2% Brls/BBE), Jeff Hoffman (12.9%), Erik Swanson (12.3%), and Derek Holland (12.2%) are all obvious fantasy avoids, but Josh Hader (12.6%) is the first RP off of the board in most drafts.

Hader had contributed obscene amounts of strikeouts, saves, and an ERA that starts with a 2 for two straight seasons now. His rate of Brls/BBE was slightly elevated in 2018 as well (10.6%), but there's no reason to think that it's predictive of a drop-off considering that Hader has already succeeded with it twice.

Maybe we need to simplify this and just use average airborne exit velocity? Unfortunately, the leaderboard in average airborne exit velocity is a total dumpster fire: Hess (96 mph), Chad Bettis (95.9 mph), Chad Green (95.6 mph), Felix Hernandez (95.5 mph), and Edwin Jackson (95.4 mph). We don't need Statcast to figure out that we really don't want to roster these guys, making it superfluous at best.



Ultimately, Statcast metrics such as Barrels and average airborne exit velocity should probably just be ignored for pitcher analysis. These metrics are great for evaluating batters, but I can't get anything out of them for pitchers even with the benefit of hindsight.

That conclusion may make this seem like a worthless article, but it isn't. Seemingly every fantasy analyst uses contact quality to credit or penalize pitchers, either through the Statcast numbers above or an approximation such as the Hard% posted on FanGraphs. This type of analysis may explain a pitcher's performance after the fact, but it seems to have zero predictive value. Therefore, there may be a competitive advantage to be gained by ignoring this type of analysis completely. Check out this link if you want to learn about some more predictive metrics.

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Finding Combo-Player Values Using Z-Scores and ATC Projections

Towards the end of last season, I asked the question – “Draft Speed or Pound the Power?” Loaded in this seemingly simple query are two contradictory approaches – one for power and one for speed.

  • Power Approach 1: Home run totals are dramatically up in baseball these days. Therefore, there are many power bats available late in drafts, and one does not need to purchase power early on.
  • Power Approach 2: Home run totals are dramatically up in baseball these days. Therefore, fantasy teams need to acquire tons of power early on in drafts to keep pace with the inflated team HR totals.
  • Speed Approach 1: Stolen bases are dramatically down in baseball these days. Therefore, one does not need to purchase speed early on, since team SB totals will be depressed.
  • Speed Approach 2: Stolen bases are dramatically down in baseball these days. Therefore, purchasing large SB players will make a tremendous difference for fantasy teams; they are essential to purchase early.

These seemingly contradictory philosophies beg the notion of acquiring as many “combo” players as a fantasy owner can possibly afford. In my article, I showed that multi-category players are a fantastic investment for one’s fantasy team. Finding the combo players is an exercise worth undertaking.

By most people’s standards, a “combo” player is defined loosely as a player who will hit a lofty number of home runs, and at the same time will steal a large number of bases. A 25/15 player refers to a hitter who will amass 25 HRs and 15 SBs. For many, the 25/15 individual power/speed thresholds are one way to define a combo player. Today, for my very first article on RotoBaller, I will take a look at finding this year’s combo players from the perspective of Z-Scores.



For those of you who have never used Z-Scores before, here is a brief introduction.

Z-Scores, often referred to as standard scores, are the kernel of a widely popular auction valuation method for fantasy. In a standard rotisserie baseball league, there are five scoring categories for hitters: BA, R, RBI, HR, SB. The question becomes – how do we combine all five categories into one all-encompassing metric? How do we know how many runs scored are equivalent to one stolen base, etc.?

The general idea involves transforming each categorical statistic in order to be on the same basis. The heart of the Z-Score engine calculates the following value for each player, by scoring statistic.

Where: Z[i] = Player i’s Z-Score;  X[i] = Player i’s Category Stat;  X-Bar = Average Stat for the category;  S = Standard Deviation for that category.

For all rate stats (beyond the scope of this article), we must first convert them into a counting stat. Using hits as an example (zxH), we calculate the total number of a player’s hits above the pool’s mean batting average.

Using the formula above, to calculate your player/category’s Z-Score: Take your player’s stat, subtract the average stat, and divide by the standard deviation across the player pool for the stat. Repeat for all categories. To obtain a player’s total Z-Score, simply sum up across all scoring components.

With regards to the individual Z-Scores as calculated above, a Z-Score of exactly zero indicates that a player is exactly average. A +1.00 indicates that a player is one standard deviation over the mean, and a -1.00 indicates that a player is one standard deviation below the mean.


Finding Combo Players

Now that we have set up the Z-Score framework, we can now look for “combo” players using these standard scores. Perhaps, one might define a combo player as having four categories with a Z-Score of at least +0.75. Or perhaps, one might choose to define combo as any 3 categories which have at least a +0.50 Z-Score.

Rather than set a hard definition for the number of categories requiring a particular threshold, I would like to use these Z-Scores as a means in order to filter for players. Let’s use the standard scores to scope out the players who are:

  • Excellent in every category
  • Great in every category
  • Good in every category
  • Excellent in most categories
  • Great in most categories
  • Good in most categories
  • Excellent in some categories
  • Etc.

The data used in this analysis stems from the ATC Projections as of February 16, 2020. Average Draft Position (ADP) data comes from the NFBC for the dates between 2/4/20 – 2/16/20.

This will be a meaningful discovery exercise. By filtering on various Z-Score thresholds, we will be able to find all of the combo players both atop the draft as well as lower down. We may be able to find some undervalued players who will be able to quickly balance out your rotisserie team’s categories.

Let’s start with the elite.


5 Categories with Z-Scores over +1.00

In most standard rotisserie leagues, Christian Yelich will be taken this season either first, second or third. Some will debate that Mike Trout should be taken with the first overall draft selection since he is the most stable player in all of baseball. Others will debate that Acuna should be selected first due to his potential 40/40 ability. Either way, Yelich is a consensus top 3 draft pick in 2020.

What makes Yelich special is that he is the only player to have a Z-Score of at least +1.00 in each and every category. Yelich is more than one standard deviation better than the mean in every offensive category; he is the definition of a true 5-category player. Yelich will set an incredibly strong base for his fantasy owners lucky enough to draft him.


5 Categories with Z-Scores over +0.75

Next up, let’s add in four more players who have Z-Scores in each category of at least +0.75.

Trout would have made the prior list, if not for his mere 14 stolen base projection which only earned him only a +0.84 in that category. Acuna makes the SB threshold by a wide margin but falls a hair short of making it in the batting average category. Similar to Acuna, Trevor Story nearly misses the opening group’s cut by just a few points of average.

Francisco Lindor almost made the elite group, but for his +0.82 in RBI. As the runs batted in category is very context dependent, Lindor has the raw skills to be among the elite.

If you are not fortunate enough to select among the first three players of drafts, have no fear – there are two shortstops later in round one that have near-elite skills in Story and Lindor.


5 Categories with Z-Scores over +0.50

Next, we will look at 6 more players who are should be considered strong combo players. All six have at least a +0.50 Z-Score in each and every scoring category.

Similar to Mike Trout, Cody Bellinger misses elite status because of his stolen base projection. In Bellinger’s case, he is just a small decimal point away from making the second combo tier. Mookie Betts, another early first-round player, misses the first two lists because of a lower projected RBI total. Four categories of at least +1.00 Z-Scores and an 85 RBI projection though, is not too shabby!

Jose Ramirez is the only second-rounder to make the 5-category combo player cut. ATC projections are expecting him to revert back to his 2017-2018 days where he hit 30+ homers and stole 25+ bases. ATC is also expecting Ramirez to still hit for a valuable average at .276. If you miss out on Story/Lindor in the first round, Ramirez might be a wonderful 2nd round consolation.

At ADPs just under 40, we have Javier Baez and the young Austin Meadows. Both are projected for 31 HRs and 13-14 SBs. Baez projects for slightly more run production, but Meadows will give you a few more points of batting average. Take note of the two during the 4th round of your drafts.

But the player that truly grabs my attention here is none other than Keston Hiura. In his second season, Hiura is expected to achieve a Z-Score of at least +0.50 in all categories. His greatest Z-Score maxes out at +0.68, making him a true “many paths to value” hitter. I love these types of players – who don’t do anything exceptionally well, yet do decently well in all categories. Hiura reminds me of players like Alex Gordon, Alexei Ramirez and Hunter Pence. I used to love grabbing these types on my roto teams year after year.

Hiura’s price isn’t cheap this year, but his categorical risk is lower than most due to his "combo" nature.

Next up are the 4-category combo players.


4 Categories with Z-Scores over +1.00

Note - Even though the 5-category players belong on the 4-category lists, I won’t repeat any names we have seen thus far. I will only be listing out the new members to each group.

You will now notice that a few numbers above are colored in red. The red colors signify players/categories which have a below average Z-Score. You will also notice that for each of the players in this tier, the one category below the +1.00 threshold is always stolen bases. Furthermore, for almost all of the players (other than Juan Soto), their Z-Score for SB are negative.

All of these players are currently being selected in the first two rounds of drafts. Soto, Arenado and Bregman are currently first round players. Freeman is going near the 1-2 turn of 15-team drafts. Devers and J.D. Martinez can be found in the back half of the 2nd round.

To me, Devers is the sharpest pick of the lot. His stolen base total is close to average. His power is superb, and for all other categories, he is extraordinary. Devers has over a +1.80 projected Z-Score in three different scoring categories. He’s a sneaky late 2nd round pick as a 4-category combo player.


4 Categories with Z-Scores over +0.75

Dropping the Z-Score threshold to +0.75 yields two more players – Rendon and Alvarez. Rendon had nearly made the previous list if not for his good-yet-not-elite power totals. 29 HRs these days is now merely “very good.”

Yordan Alvarez, who has a higher Total Z-Score than Rendon is being selected in drafts 20 picks later. Perhaps fantasy owners are discounting him because of his sophomore status? Perhaps he is discounted because he is DH-eligible only? Whatever the reason, ATC projections think that he is a relative bargain as a 4-category combo player.


4 Categories with Z-Scores over +0.50

For this tier, we now relax the 4-category requirement of Z-Scores to +0.50.

Rather than going though all of the above players, a few notes:

  • Bryce Harper is the only player to make this combo list due to his stolen bases and not his batting average. Harper has a below average BA.
  • Eddie Rosario and Nick Castellanos are the only two players found after pick 75. Rosario is especially interesting, as his overall Z-Score total is in line with others selected 25-40 spots ahead of him.
  • George Springer is statistically similar to Rafael Devers. Unless you believe that he is due for a banging or buzzer scandal related decline, he’s a great choice at his price point.

Next up are the 3-category combo players.


3 Categories with Z-Scores over +1.00

Now we come to the more limited combo environment, where any 3 categories will do. For our first 3-category level, each player must still achieve elite status in three different categories.

Some quick notes on these batters:

  • Trea Turner is this tier’s first-round player. His power metrics are lacking for his price point, but his speed more than makes up for it. He is somewhat riskier than other elite options as he is only a 3-category contributor.
  • Ozzie Albies is above average in all five categories (all Z-Scores > 0.00). Like Hiura above, I would deem him as a “many paths to value” player. Second base is not an especially deep position in 2020 - so I enjoy the idea of drafting one of Albies/Hiura, which sets a nice base in the middle infield.
  • Matt Chapman is available at pick 89. For elite power and run production, he’s a great option for the price.


3 Categories with Z-Scores over +0.75

  • Michael Conforto is a name that I didn’t expect to see in this study. But as a Mets fan, I am pleasantly surprised! Tuck Michael’s name away in case you need a 3-combo player after pick 110.
  • Rhys Hoskins is also a player available late in this group. He has more power than Conforto but could hurt your batting average and speed. I prefer Conforto to Hoskins.
  • Max Muncy appears overvalued in this tier. Simply compare his Z-Score profile to Hoskins to see that a 50-pick gap isn’t worth reaching for.


3 Categories with Z-Scores over +0.50

  • Josh Bell, Tim Anderson and Trey Mancini are the players found near pick 100. The trio appear undervalued according to ATC’s projected Z-Scores.
  • Batting average darling Michael Brantley is included in this group. That batting average is a rare commodity after pick 125.
  • Later picks in the tier include Carlos Santana, Paul DeJong and Adam Eaton. Eaton is an immense bargain if he can stay on the field all season long. DeJong at pick 191 is a great value.

Finally, let’s look at the players who are strong in just 2 categories. We aren’t looking at “combo” players any longer, but it is helpful to know the players who can provide a strong boost for particular categories.


2 Categories with Z-Scores over +1.00

  • Altuve and LeMahieu will help in runs and batting average.
  • The rest of this group will help in HRs and RBI.
  • Khris Davis currently sits at pick 177. He projects for at least a +1.25 Z-Score in both the power and RBI categories. Keep Davis in mind for power late, provided that your team has built up enough speed and batting average.


2 Categories with Z-Scores over +0.75

Just for kicks, here is one more listing for players who are “very good” at 2 categories:

  • Kevin Newman/Nick Madrigal are late average/speed helpers. Newman has a job in the majors; Madrigal should come up to the big league at some point.
  • Yuli Gurriel projects to be an undervalued BA source.
  • Franmil Reyes appears to be an undervalued power source.
  • Vlad Jr. seems like the overspend in this group.
  • Jeff McNeil is not far away from being a “many paths to value player.”
  • Carlos Correa projects to be above average in four categories.
  • Marcell Ozuna projects to be above average in five categories! That is quite valuable around pick 100.



Fantasy owners often do single category filtering in-draft. Instead, we can better prepare ourselves by parsing out the combo players in advance. By mapping out the multi-category contributors via Z-Scores, we are able to bubble up a number of potentially helpful players for the upcoming 2020 draft season.

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Using Sabermetrics for Fantasy Baseball: Spin Rate

Spin rate has become one of the most recognizable Statcast metrics, with supporters of a given pitcher highlighting his spin rates to make their case.

Unfortunately, the baseball world has done a lousy job conveying what spin rate really means. The result has been a ton of owners who know that spin rate exists, but very few who can use it to improve their fantasy rosters.

This article will teach you everything you need to know to fold spin rate into your pitcher evaluations. We'll also illustrate the efficacy of spin rate using Pitch Info data from actual pitchers. Let's get started!


How to Interpret Spin Rate

Spin rate is measured in RPMs, or Rotations Per Minute. Each pitch type has its own baseline numbers, so a high-spin fastball might have an average spin rate for a curve. Comparing different types of pitches by spin rate is rather pointless, so try to focus on how any given pitcher's offering compares to the same pitch type thrown by other arms.

So, are higher or lower spin rates better? The answer is that it depends on the type of pitch you're looking at. Let's start with fastballs.


Interpreting a Fastball's Spin Rate

The average spin rate for fastballs ranges from 2,100 RPM to 2,400 RPM. Heaters with spin rates above this range tend to have "late-life" and induce more whiffs than your average heater. They usually have backspin, or spin against gravity, that guides the ball weakly into the air if contact is made. This allows them to post elevated pop-up rates to complement their whiffs. It's worth noting that fastball spin rate is positively correlated with velocity, meaning that a pitcher with a velocity spike may also experience a spin rate jump.

For example, Mike Minor's four-seam fastball averaged 2,650 RPM in 2019 to lead all MLB starters. Its 9.4 SwStr% was very good for a heater, so he got the whiffs we would expect from a high spin rate. It also had a distinct fly ball tendency when put into play (41.5% FB%) and a high IFFB% (28.9%), suggesting that it produces pop-ups as expected as well. Minor's fastball is clearly a weapon.

However, Minor does not possess the best four-seamer in MLB despite pacing the pack in spin rate. Justin Verlander's average fastball spin rate of 2,574 RPM ranked 15th in MLB (minimum 250 total pitches thrown), but bests Minor's in all of the metrics cited above: 14.3 SwStr%, 55.6 FB%, 25.5 IFFB%. The reason why is that Verlander's fastball gets more movement out of its spin than Minor's.

We have to consider "gyrospin," alternatively called "useless spin." If you've ever seen a bullet in slow-motion, it rotates slightly while flying straight to its target. That rotation is gyrospin and it has no impact on where the bullet ends up. A metric called "Active Spin" measures how much spin is actually affecting a ball's trajectory. Verlander paced baseball with an Active Spin rate of 98.5% on his fastball, while Minor's 67.8% Active Spin rate was much less impressive.

If you're looking for a contact manager instead of a strikeout artist, you want a spin rate below the average range above. Low-spin fastballs produce weakly-hit ground balls and a lower slugging percentage against compared to their high-spin counterparts. However, this can be a dangerous way to live. Contact managers need a lot of things outside of their control to go right to become fantasy assets, so fantasy owners should look for high-spin strikeout artists whenever possible.


Evaluating Spin Rate on Secondary Offerings

Unlike fastballs, changeups usually want a low spin rate to maximize how much they move. For instance, a changeup is Anibal Sanchez's out pitch. Last season, it posted an 18.7% SwStr% and 51.4% chase rate, suggesting that opposing batters had no idea where it was going to end up. The reason why is its spin rate: it averaged 1,447 RPM last year.

Breaking pitches usually want high spin rates. Unlike fastballs, breaking offerings have topspin, or spin toward the ground, that can help guide the ball downward if contact is made. Breaking pitches tend to be a given pitcher's strikeout pitch though, so owners generally aren't looking for any kind of contact on them. Breaking ball spin rates are therefore the least important to look at but may provide interesting information at times.

There are enough variables in play here that spin rate should never be considered on its own. Instead, start with Pitch Info and then use spin rate to confirm if a given pitch can sustain its elite performance (such as Verlander's four-seamer) or if it was probably a fluke.



To summarize, spin rate is measured in RPM. Fastballs can be good with high or low spin rates, but higher spin rates tend to translate better to fantasy. Changeups want as little spin as possible to maximize their movement. Breaking pitches typically benefit from higher spin rates, but it's not as clear-cut as it is for fastballs and changeups. Finally, gyrospin can distort spin rate readings, meaning that you should always combine spin rate with other metrics in your analysis. Check out this link to learn how to apply other advanced metrics to your fantasy prep.

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How to Attack RP in SV+HLD Leagues

No position has seen as much evolution in recent seasons as the relief pitcher. Gone are the days where starters were expected to go seven innings as most teams have embraced the idea of "super-bullpening" and try to fit as many pitchers that can throw 95+ MPH into their bullpen as they can.

Many fantasy leagues have begun to embrace this trend as well with leagues opting to include saves-plus-holds as a category instead of the traditional saves category. So how should you go about attacking the RP spots on your roster if playing in a league that gives credit to the unheralded middle reliever?

Keep reading below for my tips on how to gain an edge over your competition in leagues that reward the relievers that get the ball to the ninth inning men we all know and love.


Target Good Pitchers

It sounds too simple to be true, but playing in a saves-plus-holds league puts more of an onus on talent rather than opportunity. Anyone who's played in a categories-based fantasy league knows the running of the bulls-type scramble that ensues to pick up the next-in-line when a closer gets injured or traded. It doesn't matter if that player is on the worst team in the Majors; if a pitcher is in line to get saves, he will get scooped up instantly in fantasy baseball.

Adding holds to fantasy changes that completely. While there are only 20-something players at a given time that will help in saves, adding holds to the mix waters down the player pool to the point every team in a fantasy league can find players who contribute in SV+HLD. This means the true difference makers are the ones who contribute something else useful to your fantasy squad.

Elite pitchers, like Nick Anderson of the Rays, gain significant value in this format. A forward-thinking organization like Tampa Bay likely won't settle on a permanent closer. Anderson will be used in any high-leverage situation, regardless of the inning, so he'll likely rack up a ton of both saves and holds making him a top-10 option in this format. The tall right-hander struck out 110 batters in just 65 innings last season which made him a startable reliever in traditional roto leagues where holds don't matter. Give him credit for 16 holds to go along with his Ks and ratios and you've got a must-start reliever who is a top-flight option in this format.


Don't Overcorrect

As different as it is to play in a league that rewards holds, saves are still king. Last season, eight relievers had more saves than the three-way-tie atop the holds leaderboard. Looking back three seasons, 10 relievers have more saves than the holds leader (Adam Ottavino) has in that span. Saves plus holds leagues reward both stats equally so don't completely forget about saves just because you can fill the category with holds as well.

Playing in a league with holds changes how most fantasy managers approach the relief pitcher position. If too many managers start waiting on reliever under the assumption that they can fill the SV+HLD category late in the draft, then it could create value on the elite closers. Josh Hader, Aroldis Chapman, and Roberto Osuna are all still better fantasy options in this format than any middle reliever available, so if they start to fall in the draft don't be afraid to pull the trigger on an elite closer just because the demand for them is lessened.


Pick Pitchers On Good Teams

This is another tip that sounds overly simple, but it's one of the easiest ways to accumulate saves and holds. Last season, 11 of the top 12 teams in the holds rankings had a winning record. You don't need a statistics degree to know that winning teams have more leads and more leads mean more save and hold opportunities.

The Yankees alone produced three of the top-nine holds leaders last season in Zach Britton, Adam Ottavino, and Tommy Kahnle. All three had at least 27 holds with Ottavino and Kahnle both adding strikeout rates above 31 percent.  They are all back this season with the same manager on a team many are projecting to win 100+ games, so it's reasonable to expect at least 25 saves plus holds from each again this season. Other good teams, like Houston, had more established bullpen roles with Ryan Pressly setting up Osuna. Pressly tied for the league lead with 31 holds and produced a sub-one WHIP. He will be back in the same role and should have plenty of late leads to protect for the Astros.


Embrace the Change

Playing in a saves-plus-holds league is different than most fantasy managers are used to and fantasy baseball purists (such as myself) can find it intimidating to learn how to optimize their roster without having years of experience to draw on. That being said, new rules create new opportunities for your team to gain an edge over the competition. Many casual fans don't know non-closers on teams other than their own, so having a knowledge of the bullpens around the majors gives you a leg up. Half of competing in saves in fantasy baseball is simply being on top of bullpen roles. RotoBaller provides frequent updates of closer situations so keep it here for analysis on who is getting saves, and holds, in each team's bullpen all season long.

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Using Sabermetrics for Fantasy Baseball: Pitch Info

One of the most fundamental questions in fantasy sports is if a player's current performance is sustainable. More than any other sport, baseball has a slew of statistical measures that can be dissected in numerous ways to analyze player performance.

Pitch Info is a publicly-available pitch tracking system that provides a lot of different data to help fantasy owners make this determination for mound breakouts and busts alike.

Let's look at how to effectively use this data to give you an edge in your fantasy baseball league throughout the season.


Interpreting Pitch Info Data: Velocity

The first data point to understand is velocity. Generally speaking, a pitcher that loses fastball velocity is losing something to either an undisclosed injury or the aging process. Pitchers that gain velocity can expect to increase their production. For example, Lucas Giolito saw his average fastball velocity spike to 94.6 mph last season (92.8 mph in 2018). His K% soared as a result (32.3 K% vs. just 16.1% in 2018), making him a fantasy stud (3.41 ERA) instead of a dumpster fire (6.13 ERA in '18)

When evaluating a pitcher's velocity, you should always look at his baseline velocity as opposed to an arbitrary league average. Giolito's 94.6 mph isn't all that impressive by modern standards, but it clearly allowed him to take his game to a new level. Other variables like movement and location also matter, but velocity is a good introduction to using Pitch Info data.


Interpreting Pitch Info Data: Pitch Mix

Slightly more advanced is pitch mix, or what pitches a pitcher throws and how often he throws them. A pitcher may improve his production by abandoning a poor pitch or developing a new, effective one. This is a good stat to consult if a pitcher sees a sharp change in his K%, as a change in pitch mix could represent the change in approach that supports the new number. If the change does not have a corresponding pitch mix shift, it may be less sustainable.

Let's return to Giolito as our example. He made two substantial repertoire changes as part of his breakout, and Pitch Info allows us to track the performance of each individual pitch. First, he eliminated his sinker (19.9% thrown in '18. 0.1% last year) in favor of his four-seamer (39.5% in '18, 54.9% last year). Giolito's four-seamer was amazing, generating an above-average number of whiffs (11.5 SwStr%) while still spending enough time in the zone to get ahead in the count (55 Zone%). His sinker generated very few swings and misses in 2018 (4.3 SwStr%), while its 53.9 Zone% was just shy of his new heater. This was a good change.

Second, he threw more changeups (15.3% to 26.1%) at the expense of his curve (10.1% to 4.2%). Giolito's change was one of the best pitches in baseball last season, producing an incredible 22.2 SwStr% with a 52.5 Zone%. Throwing more of it could only be a good thing. In contrast, his curve doesn't accomplish anything in particular, with pedestrian SwStr% (5.1), Zone% (36.8), and O-Swing% (18.9) rates. Again, this change figures to improve Giolito's fantasy stock.

The same type of analysis may be performed for a number of other stats, including BABIP, FB%, LD%, GB%, and HR/FB. There is no point in looking at a league-average pitch mix, as every pitcher owns a different arsenal. All of these variables may be considered over a pitcher's complete repertoire to determine how good he is (or should be) without relying on any conventional metrics. This can be good for identifying sleepers, as pitchers that have one or two standout pitches could break out by simply using them more often.


Interpreting Pitch Info Data: Pitch Results

What is the baseline for this type of analysis? It depends on the observer, as there are almost as many ways to interpret this data as there are data points to consider. The league average O-Swing% was 31.6 in 2019, and most good wipeout pitches need to beat this number substantially. The overall Zone% was 41.8, including pitches like splitters in the dirt and high fastballs that were never intended as strikes.

The fastball will generally be inferior in results to pitches that do not need to live in the strike zone, as pitches hit outside of the zone offer better results than offerings in the hitting zone when they are put into play. However, getting ahead in the count is necessary to make those pitches work as intended, making (sometimes) mediocre fastball results a necessity.

It is dangerous to generalize, but 2-seam fastballs and sinkers tend to stink for fantasy purposes. They're usually hit harder than fastballs. They may post strong GB% rates, but also have high BABIPs and scary triple slash lines. Any sinker hit in the air was probably a mistake, so the HR/FB rate is usually high for the limited number of fly balls hit against them. Their SwStr% rates also tend to be poor. Overall, fantasy owners prefer a straight four-seamer to be the "zone pitch" in a pitcher's repertoire.

Personally, I look for fastball with a SwStr% of around 9% and a Zone% of at least 53%. Many pitchers succeed with a lower Zone%, but I can't stand watching walks. I then look for a wipeout pitch that offers a SwStr% of at least 17 and an O-Swing% of 40. Ideally, there is a secondary K pitch that prevents the 0-2 offering from being too predictable. Only aces really fulfill all of these criteria, but I can dream, right?



To conclude, Pitch Info tracks a lot of data of interest to fantasy owners, including average velocity, pitch mix, and individual pitch results. All of this data may be used to predict who will break out or which breakouts can sustain their current performance. If you would like more analytical tools to help you dominate your leagues in 2020, check out this link.

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Mock Draft Review: Best Late-Round Targets

Last week, some members of the RotoBaller staff completed a 12-team mock draft for standard 5x5 format. After the draft, we each broke down our strategy and some of our favorite picks, which can be found here. However, I want to take a closer look at one portion of the draft in particular.

Since we know that the difference between a good year and a great year can often be determined by the value found in the late rounds, I went through the draft board and identified my favorite players taken in the last 10 rounds of our mock draft. These are all guys who I think have tremendous potential to recoup value in redraft leagues and should be on your shortlist when you come to those final rounds.

(ADP was calculated using NFBC ADP from 1/1/2020 to 2/12/2020 and selecting only Draft Champions leagues)


RotoBaller Early Staff Mock


Carson Kelly (C, ARI) - ADP: 213

Carson Kelly is one of my favorite catchers if I find myself waiting on the position. He was a clear launch angle gainer, increasing from 5.4 degrees in 2018 to 14.3 last year. His barrel% jumped over two percent and his Hard Hit % improved nearly 15%, all while increasing his BB% into the top 8% of the league. For a 25-year-old entering his athletic prime, much of this is indicative of clear signs of growth that could signal a 20+ home run season with a .250 average in a good lineup.

The only bit of cold water I'll throw on this is that Kelly is a right-handed batter who hit .203/.303/.405 versus RHP and .356/.462/.667 versus LHP. The Diamondbacks signed Stephen Vogt in the offseason, and once the LHH Vogt returned from offseason injury, he put up a barrel% of 10.4 and a Hard hit% of 41.1 while also hitting .271/.330/.505 against right-handed pitchers. If Vogt gets hot, the Diamondbacks could rotate him in for a few games per week against right-handed starters, which would cap Kelly's at-bats around 400 and make him slightly less attractive than some of the other late catchers (more on that later).


Rougned Odor (2B, TEX) - ADP: 219

I wrote about Odor already in my piece on Brls/BBE% breakouts, so I'll just offer some snippets of analysis from that piece to highlight why I like him as a late-round value:

"He has also improved his BB% from 4.9% to 8% to 9% over the last three seasons. It's not a game-changing shift, but it's real progress, especially when paired with an O-Swing% that has dropped from 38.3% to 35.4% to 33.1% over the same span...When he does make contact, he is doing so with more power, increasing his barrels each of the last three seasons before this outburst last year. Pair that with an 86-percentile Hard-Hit% and a nearly five-degree increase in launch angle, and you have a bat that looks like it can provide consistent power.

In fact, Odor has hit 30 home runs and stolen at least 10 bases in three of the last four seasons. You're not going to get that from very many players, and certainly not any going this late in the draft. With more contact, and more powerful contact, Odor could put together another 30-10 season with a batting average around .230, which, if you remove his batting average from the equation, is enough to give him a rbEDV around pick 110 (23 home runs, 14 stolen bases, 77 runs and 74 RBIs)."


Mitch Keller (SP, PIT) - ADP: 221

On the surface, Mitch Keller was not great in his MLB audition for the Pirates last year, pitching to a 7.13 ERA, a 1.83 WHIP, and a .343 BAA. Not all of that was a fluke, as the right-hander features a fastball that induced only a 17.6 Whiff%, a .324 xBA, and .476 xSLG.

However, many of Keller's underlying metrics suggest that he was actually pitching much closer to his 3.47 xFIP. His BABIP was .475 for starters, which is certainly not sustainable. He had a 21.6% K-BB% and an 11.8% SwStr% while flashing two plus secondary offerings: A slider that had a 2.3 pVAL, a 47.8 Whiff%, and a 29.5 PutAway%, and a curve that had a 2.7 pVAL, a 34 Whiff% and a 25.5 PutAway%.

If he can limit damage on his fastball and use it to set up his plus off-speed, Keller should be in for 150+ innings of an ERA around 3.80, WHIP around 1.27, and just under 10 K/9. He won't get a lot of wins on the Pirates, but that stat line equates to a rbEDV in the low 200s.


Jose Urquidy (SP, HOU) - ADP: 222

Urquidy seems to be flying under the radar despite the fact that he's a prospect with a solid track record and a locked-in spot in the Astros starting rotation. He arrived to little fanfare but put up a 3.95 ERA in seven starts with a 24 K% and only a 4.2 BB%. He doesn't have elite velocity, but his command and plus off-speed offerings allow him to limit hard contact and pick up a fair number of whiffs, as both his curve and slider had a Whiff% over 40 during his big league stint last year.

Even with Forrest Whitley banging on the door, I'd expect Urquidy to keep his roster spot given Lance McCullers' innings limit and the question marks around the team's fifth starter spot. With 160+ innings, Urquidy could conceivably pitch to an ERA around 4.00 with a sub 1.2 WHIP and a 160+ strikeouts on a good team that's likely to up his win totals. According to rbEDV that would be good for pick 160 if he could pitch to a 3.70 ERA, so even with an ERA hit, Urquidy is well worth taking as you approach pick 200.


Adrian Houser (SP, MIL) - ADP: 253

Houser got 18 starts for the Brewers in 2019 and acquitted himself quite well. He threw 111.1 innings with a 3.72 ERA and 3.60 xFIP while notching a 25.3 K% and giving up 91st-percentile exit velocity and 86th-percentile xSLG.

He doesn't miss a lot of bats, with a 9.6 SwStr% and a 27.5% O-Swing, but he has good command of four offerings and started using his sinker as a primary pitch in 2019, which was smart as it had an 11.9 pVAL and allowed his 94-95 mph fastball to become more of a strikeout pitch with a 23.4 PutAway% in 2019 as opposed to 13.3% in 2018.

What's interesting about his success with his sinker is that Houser also experienced the 13th-worst defense behind him, according to Statcast's OAA metric. If he gets even league-average defense, Houser could be even more effective than he was last year, and he seems locked into a starting job with very little competition elsewhere on the Brewers' roster. That makes him closer to a low 200s value based on rbEDV and worth taking a late-round flier on in almost any format at his current price.


Starlin Castro (2B/SS, WAS) - ADP: 263

Castro was quietly effective in Miami last year, hitting .270 with 22 home runs, 68 runs and 86 RBIs. Now he moves to a much stronger Washington lineup and a better offensive park. People should be all over him, but his ADP is falling because many projection systems seem to have him playing 120 games or fewer. I'm not sure I understand that.

Even with Asdrubal Cabrera and Howie Kendrick back, Castro should see close to full playing time. Carter Kieboom is not a lock to take the 3B job, and Castro could slide to 3B if the Nationals decide to get innings at 2B for Cabrera or Kendrick, who can also get his at-bats in the outfield. Castro saw legit growth last year, cutting his K% and improve his hard contact for the third year in a row. In the middle of a strong offense, there's no reason he can't push for 20+ home runs and another 80+ RBI season with a strong batting average.


Brendan McKay (SP, TB) - ADP: 270

McKay is a prime example of how quickly we experience prospect fatigue. When the Rays called him up, fantasy managers unloaded their FAAB budgets to land him on their team. Despite showing flashes, he struggled, for the most part, compiling a 5.14 ERA and a 1.41 WHIP, while registering a negative pVAL on all of his offerings. He was in the fourth-percentile in curve spin and the third-percentile in exit velocity allowed, which is indicative of the hard contact that he was giving up. However, his minor league track record didn't simply go away.

Despite his poor performance, he had a K-BB% of 18.5 and a .261 xBA. Even when he was not on top of his game and giving up frequent hard contact, he was still striking players at a good clip and suppressing inflated average totals. As he begins to get comfortable in the majors and perhaps relies more on a changeup that had a 36.4 Whiff% and less on the curve that gave up a .299 xBA and .455 xSLG, McKay could provide immense value at his current price. I'd buy now simply based on upside, but if there are any spring training reports about a new pitch mix or improvements to the curve, I'd be even more aggressive in my pursuit.


Garrett Richards (SP, SD) - ADP: 287

Garrett Richards has a lengthy injury history. Everybody playing fantasy baseball knows that, which is why he's being drafted near pick 300. He hasn't pitched more than 100 innings since 2015 but has tantalized with upside in his brief periods of health. He had an average SwStr% of 11.7 from 2016-18 and a 25 K% during the same span. His best pitch has always been his slider, which he didn't throw much in his three starts last year, but it's more than likely that he was just beginning to get comfortable after coming back from injury.

The Padres signed him to a two-year deal and only got three starts from him in 2019. There's a very good chance they see just how much they can throw Richards in his final year under contract. Richards' risk isn't talent-based but volume-based, so if he were to get hurt, you could always pick up a streaming starter and continue to accrue stats at the position you had pegged for Richards on your roster. With a pick this late in the draft, even if you get just 100 innings of above-average K-rate and a high-threes ERA, you're getting more than enough value.


Dylan Bundy (SP, LAA) - ADP: 288

Dylan Bundy has been a favorite of Baseball Twitter this offseason. At first, it seemed to start as a joke, taking a renewed interest in him due to his move out of Baltimore, but then the stats started coming and the humor turned to genuine intrigue. Despite his K-BB% decreasing by 2.5% and his ERA still at a bloated 4.79, there were some interesting developments for the 27-year-old. Bundy limited hard contact, gave up fewer barrels, and pitched to career-lows in all the x-Stats (xBA, xSLG, XOBA, etc.). Then, Alex Chamberlain sent the Bundy debate into a new stratosphere but showing his remarkable similarity to rising star and Twitter-favorite Shane Bieber.

Now that Bundy has moved to a better pitcher's park, with a better defense, and a team more likely to give him an increase in wins, it's fair to wonder if the former top prospect could become a useful fantasy option. At the price he's going, it's certainly worth taking a chance.


Seth Lugo (RP, NYM) - ADP: 305 /
Drew Pomeranz (RP, SD) - ADP: 404

At the back end of your draft, there are few picks more productive and unsexy than a multi-inning reliever. Even though it became all the rage when Chris Devenski burst onto the scene three years ago, there are still many owners that chase saves exclusively, instead of pairing volatile closers up with solid ratio relievers.

Lugo and Pomeranz are two of the best late-round ones you can find. Lugo is a bit trendier since he was able to accrue six saves last year. While I think that's unlikely this year with Edwin Diaz hopefully returning to form and Dellin Betances in town, Lugo should still throw 70+ innings of sub-3.00 ERA baseball with a high 20s K%. He'll also be in line for cheap wins to add some additional value.

Pomeranz is in a similar situation but is less popular because he only transitioned into the bullpen full-time towards the end of the year. However, in his 28.1 innings out of the pen, Pomeranz had 50 strikeouts and a 1.88 ERA on a .165 BAA. His fastball was able to sit around 93 and played up even faster because of his big curveball. As the primary lefty in the pen, Pomeranz could snag some cheap wins and even get the occasional save against lefty-heavy lineups due to the new three-batter minimum.


Ian Happ (2B/OF, CHC) - ADP: 330

Ian Happ is only 25-years-old. I feel that warrants mentioning. As I discussed with Brendan McKay above, the fantasy community can turn its back on former prospects all too quickly. Happ burst onto the scene in 2017, hitting 24 home runs in 115 games and many people were ready to anoint him as a legitimate fantasy asset. Then his swing-and-miss tendencies got the better of him in 2018 and he wound up in the minors in 2019, and people had already forgotten about him. However, Happ still knows how to hit.

He played 57 games over the second half of 2019 after being recalled from the minors and showed improved patience and plate discipline, cutting his K% from 36.8% in 2018 to 25%. During the 26 games he played last September and October, Happ hit .311/.348/..672 with six home runs, nine runs, and 17 RBI. He seems likely to be the Cubs' centerfielder in 2020, but could also see time at 2B since the Cubs are currently set to start Jason Kipnis there.

If he gets 500+ at-bats, it's easy to see a 20-home run, 10-stolen base season for Happ with a good chance for 80+ RBI in a solid lineup. That's well worth taking outside of the top 300, especially if he winds up with that dual-position eligibility.


Travis Shaw (3B, TOR) - ADP: 345

Shaw is the ultimate bounce-back candidate. After hitting 30+ home runs in back-to-back campaigns, Shaw decided to change his swing and admitted to being thrown off all last season. He claims to be back to old his old mechanics, which means it's not out of the question to assume he returns to his previous numbers.

After all, he's only 29 years old and many of his alarming numbers from last year - 33 K%, .113 ISO, .175 AVG, 76.7 Z-Contact%, 60.5 O-Contact% - deviate so much from his career profile that it's easy to view them as products of a lost season. According to Statcast, his Hard Hit% was nearly identical to 2018 and his barrel% was identical to 2017, while his BB% kept the same gains he experienced in 2018. The biggest change is that his launch angle jumped from 16.6 degrees to 24.4 degrees.

So, Shaw has the same improved plate discipline and similar hard contact metrics as he did during the two separate years that he hit 30 home runs, he's still in a hitter's park and in the middle of a strong lineup that should give him ample opportunity for counting stats? Yeah, that helps me believe in the return to form, and if I get any indication that his swing is back to normal during the spring, I'll buy almost everywhere, as it's possible we see another season with a .250 average, 25+ home runs, 70 runs and 80 RBIs, all from outside the top-300 picks.


Josh James (RP, HOU) - ADP: 367

Josh James seemed primed to win a spot in the Astros rotation in Spring Training last year before a quad injury delayed the start of his season. When he came back, the Astros used him primarily out of the bullpen, where his elite fastball was able to play up.

However, people are writing James off as simple bullpen depth a little too quickly. He's worked primarily as a starter for his entire minor league career, amassing a K% over 30 the last two years. He has two solid off-speed offerings, with a slider that gets a 56.3 Whiff% and a changeup that registered a 50.7 Whiff%. Both pitches also show elite vertical movement, while the slider has proven to be a true wipe-out pitch for him.

Without any truly high BB% before moving to the bullpen, there's no reason why James should be viewed as a "former starter." With Brad Peacock, current favorite to land the fifth spot in the Astros rotation, experiencing neck issues, the path towards starting is looking better. For a pitcher of James' quality, that makes him worth taking this late in drafts.


Nathan Eovaldi (SP/RP, BOS) - ADP: 374

Speaking of taking a shot, Eovaldi is the ideal late-round flier. He threw 67.2 unsuccessful innings for the Red Sox last year while battling injury, but he showed the same dynamic stuff which led him to a K% jump between 2018 and 2019. In 2018, Eovaldi used his cutter to get ahead and then set up his 97-98 MPH fastball up as a put-away pitch. For some reason, while battling injury in 2019, Eovaldi massively cut back on his cutter usage and in favor of his curve, which had a 41.1 Whiff% but has only been a marginally successful pitch for him throughout his career.

If he can get back to using the cutter more and then pair that with the high fastball and his improved curve, there's no reason he can't repeat 2018 with an ERA under 4.00 and a K/9 north of eight while pitching for a team that should put him in a good position for wins. Plus, if new Red Sox GM Chaim Bloom brings his old Tampa Bay philosophy of the opener to Boston, Eovaldi would be the perfect pitcher to use as a "Follower," throwing five innings to limit his overall wear-and-tear and still be in line for victories. That's a chance I'm willing to take this late in drafts where I'm essentially investing nothing and can move on easily if he falters.

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Using Sabermetrics for Fantasy Baseball: Pitcher BABIP

While FIP is a useful tool to predict a pitcher's future ERA performance, fantasy owners should remember that ERA, not FIP, is what really matters in most formats. This means that we are interested in the "luck" that separates the two statistics.

While some of this luck is unpredictable, we can and should predict some of what goes into a pitcher's bottom line. BABIP plays a big role in the variation of a pitcher's perceived luck, but it may not be as clear-cut as it seems.

Let's get to it!


How to Interpret BABIP for Pitchers

When calculating BABIP for hitters, we assume a neutral defense because they figure to see a balance of poor and skilled defenders as they travel around the league. This is not true for pitchers, as they always pitch in front of their own club's defenders. A team with Victor Robles and his 23 Outs Above Average (or OAA) figures to provide better defense to its pitchers than a team that lacks a premium glover. A better defense helps pitchers sustainably outperform their FIP.

Outs Above Average is a Statcast metric that makes it easier to look at the quality of a pitcher's defense. Outs Above Average, or OAA, measures each player's defensive contributions using Catch Probability. If a batted ball is caught by a player, the player receives OAA credit equal to 1 - the ball's Catch Probability. For example, a successful catch on a ball with a 40% Catch Probability is worth 0.6 OAA (1 - 0.4 = 0.6).

Players also lose points equal to the batted ball's Catch Probability if they flub the catch. Missing the ball in the example above would subtract 0.4 from the player's OAA. Another great feature of OAA is that the stat is sortable based on a shift. If you want to know how a third baseman fares when shifted to a traditional shortstop position, OAA makes it easy to look at that data. Robles led all outfielders in OAA last season, while Javy Baez (19 OAA) took the top spot among infielders.

There are other defensive metrics, but they are much more abstract than OAA while also leaving out important pieces of the puzzle. Ultimate Zone Rating (or UZR) makes no effort to account for the shifts in today's game, rendering it completely obsolete. Defensive Runs Saved (DRS) has one fantasy purpose: measuring the value of a pitcher's defensive contributions to his own cause.

For example, Dallas Keuchel finished second among pitchers in DRS last season despite only throwing 112 2/3 IP. This is nothing new for Keuchel, who has a whopping 50 DRS over his 1,302 career IP. Fantasy owners have known for years that Keuchel posts lower than average BABIPs when he's on despite being a ground ball pitcher, but the reason isn't some magical contact suppression ability. It's the fact that Keuchel rates as roughly double the defender Javy Baez is if you prorate his DRS over a position player's number of innings.


What else impacts a pitcher's ERA?

BABIP is also partially determined by a pitcher's style. An extreme ground ball pitcher may have a higher BABIP against because grounders have higher BABIPs than fly balls (.236 to .118 in 2019.) This stylistic difference also changes how much a given pitcher will benefit from (or be hindered by) a particular defender on his team. For instance, a fly ball pitcher would love to pitch in front of Robles, while a ground ball specialist would benefit more from an elite infielder like Baez instead.

While defense is largely out of a pitcher's control, some pitchers can control their BABIP to a degree. For example, you would probably be tempted to say that the .218 BABIP Justin Verlander allowed last season was a fluke, and you would be partially right. However, Verlander combined a strong fly ball tendency (45.2 FB%) with an above-average IFFB% (12.4%). Flies have the lowest BABIP of all batted balls. Furthermore, pop-ups are rarely hits, so inducing them consistently enables a pitcher to post better than average BABIPs. The combination would be expected to produce a low BABIP allowed.

The same principle holds for pitchers who can limit line drives, but this skill is not quite as sticky as pop-ups. Liners post very high BABIPs but randomly fluctuate, as we have seen in a previous article.

Every pitcher allows a few hits, and the sequencing of these events may also cause a difference between a pitcher's FIP and ERA. Allowing three base hits over three innings is probably harmless, while allowing three hits in one inning and then nothing in the next two frames likely puts a run on the board.

Sequencing luck is measured by strand rate, or LOB%, and research shows that it is largely an unstable, luck-driven stat. In 2019, the league average LOB% was 72.3%, with higher numbers generally forecasting a higher ERA moving forward. Elite strikeout guys tend to be the best at getting the K "when they need it," and as such may sustain slightly elevated strand rates.



To conclude, a pitcher's BABIP includes some unknown variables but also some predictable inputs. The quality of his defense can help or hurt him. Sequencing does not affect BABIP, but can impact a pitcher's ERA substantially. A given pitcher's style, as a ground ball or fly ball specialist, may also impact his performance. If you would like to learn more about other advanced stats, check out this link for a full glossary.

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Talking Projections and Data-Based Drafting with Ariel Cohen

The fantasy baseball industry is driven by data and many analysts go so far as to develop their own systems for projecting value. Recently, ATC has become more popular as a baseline for those who are seeking a way to rank players for the upcoming season.

I recently had a conversation with the man behind the numbers in order to gain perspective on his unique system and how to best apply it on draft day.

Ariel Cohen is the creator of ATC projections, reigning FSWA baseball writer of the year, and former presidential candidate (really). 


How to Use Projections

David Emerick:  As someone who publishes projections, can you tell us how most projection systems work and what made you design ATC in response to what was already out there?

Ariel Cohen: I’ll tackle how ATC came about first. In the year 2010, I simply wanted to improve my odds of winning my home leagues. I figured, let’s start by using the most accurate projections that I could possibly find. I didn’t know which projections were better than others, so as any good actuary would do, I initially just used them all. I compiled spreadsheets of all the projections that I could get my hands on and averaged them. Everything that I’ve learned in the actuarial field suggested that averaging different models would produce a better overall result.

ATC isn’t a substitute for other projections... it allows the best components of each system to shine brighter.

That was a great start. At the end of the year, I went back to look and see which individual projections performed better than others. When I started to look into each statistic by projection system - different projections performed better or worse for certain stats. One system might have been awesome for HRs, but was poor for pitcher strikeouts. Another might have been mid-pack in RBI - but was lousy in pitcher walks.

It dawned on me that using a straight average of projections is not the ideal way to aggregate the lot. Instead, weights should be drawn closer to the individual accuracy of its components. So I ran regressions and calculated some prospective weights. The better power systems got a larger share of the total for power, and the better speed systems earned more weight in the speed totals. The following year, the first iteration of ATC was created. ATC stands for Average Total Cost [and yes, ATC are also my initials].

Over the years, I’ve gotten a lot more sophisticated and the data is more robust. With each passing season, I am more accurate. But the general method and principle from the first iteration still holds true today.

Most projection systems use external variables to project stats. Power might be projected based on a player’s average flyball distance, launch angle, barrels, and a bunch of others. Initial HR totals are calculated, and then are ballpark adjusted, regressed for age, and possibly compared to historical levels. ATC isn’t a substitute or competition for other projections. Rather, it is an enhancement; it allows the best components of each projection system to shine brighter.

The key is not to get any one player right - the key is to be directionally right on more players.

DE:  How do you think fantasy managers misuse projection systems?  When we’re looking at ATC projections, what should we be thinking about in terms of variability and reliability? 

AC:  To be honest, I think that most fantasy managers either disregard projections or simply use them as a tool mid-draft to take a sneak peek at a player’s stat line. Others use projections simply to confirm or deny their own general intuitions.

ATC is orchestrated to reduce minimum bias via the “wisdom of crowds.” While other projections could show huge outlier players (either up or down), ATC will be more reliable. Because ATC is an average of other projections, you won’t find an outlandish set of figures; its stability is its key. ATC will help you identify more “profitable” players than other systems, and similarly, it will steer you away from a larger number of “unprofitable” players. The key is not to get any one player right - the key is to be directionally right on more players - which is what ATC facilitates.

ATC is the best “base” set of projections that you can have. Start your exploration into the overvalued and undervalued players with the wisdom of crowds.

DE:  How can we do better? How can we use projections more effectively? 

AC:  To me, projections should be the starting point of anyone’s journey into player evaluation. You could be found guilty of hubris if you think that on the whole, you yourself - unaided - can outperform calibrated projection models. Sure, for any individual player you may have better insight, or you may discover a flaw in the model. But against any fairly accurate projection model, you cannot beat them in the long run.

I believe that the best advice is to always start with a projection set - and then adjust according to your own intuition or knowledge. ATC is the best “base” set of projections that you can have. Start your exploration into the overvalued and undervalued players with the “wisdom of crowds.” ATC represents the best of the projections, so why not start here?


Strengths and Weaknesses of Projection Systems

DE:  Certain stats, like batting average and ERA, are heavily regressed in most ranking systems. How should fantasy managers handle categories where the projections seem so close to one another? 

AC:  If I were to tell you that a player will either exactly hit .290 this season or .270 this season - what would you project him for? If you say .280 - you would be projecting the average, but of course, you would also be wrong. That player can’t hit .280, as we said. But I’d still guess .280 - to obtain the least amount of possible variance in the long run.

Projections are regressed. They won’t encompass the true variance of the final individual batting average distribution, but they will be the best guess for each individual player in its own right. The average of players will all seem closer to one another than what actually happens in a single season alone. That is intended.

There isn’t much to do here. The idea is to get your individual player selections right, rather than model the MLB distribution. You want to find the long-term undervalued players, and the regressed averages still give you the correct relationship between player skills.

That being said, when I do prospective valuation of players (generating player auction prices) - I add in a slight alteration in my process to account for this.

If the projected range of a category is markedly different from that of the past season, I will tilt the range number to align more with the past range. So if the standard deviation of saves in 2019 is 20, but I am projecting only a 10 S.D. for 2020, I’ll adjust that range. I’ll employ a value closer to 15, etc. I do so because I want to make sure that the projections aren’t totally misaligned with the true nature of the statistical distribution. In that way, I implicitly adjust the distribution of projections to a more realistic curve.

Was that too technical? 🙂

DE:  You mentioned that ATC’s stability is its strength. I think that one reason managers tend to undervalue projections is a sense that projections don’t seem to reflect breakouts or collapses. First of all, is it accurate that projection systems don’t capture breakouts and collapses? Secondly, if it is accurate, is that just because projections follow the pattern and breakouts/collapses are exceptional events?

AC: I don’t believe we need projections to predict full breakouts or collapses. Sure, obviously if our projection systems knew that Josh Bell would hit 37 homers and 116 RBI last year, that would have been fantastically helpful.

But the truth is - all that you would have needed to profit from Josh Bell last year from projections was for them to be somewhat above market value. If Bell’s ADP was in the 10th round - all you would have needed was for Bell to be valued as an 8th-round player. That’s called a “BUY” signal. If Bell is undervalued, he will make his way onto several of your fantasy rosters. Once on the roster - you enjoy the entirety of the upside and profit that he generated.

On the flip side, and perhaps even easier - all you need not to realize a collapse on your roster is for your projections to be somewhat below market. That would signal a “PASS” on the player. You don’t need a pitcher to be projected for a 5.50 ERA, if a 4.50 ERA projection will make you pass on a player that the market values as a 4.20 ERA player.

As for outsized results - projections are just the averages or medians of player expectation. Breakouts or collapses should occur for some each season - simply by the process risk alone.

DE:  Do recent changes to the baseball distort our ability to project player performance?

AC:  Yes, it does, in that the composition of the ball greatly affects the major league run environment. Pitchers who are fly-ball oriented would have an outsized difference in their ERA resulting from a change in HR/FB. Hitters who have “warning track power” may show a 5-10 HR difference in their power output. For a number of players, the ball matters greatly.

Max Kepler was recently asked if his career year in 2019 of 36 HRs had anything to do with the ball. The quick recap of his response was, “yeah.”

For most, as for the change in the ball - we can simply just scale home runs up to fit the average change in power. In that scenario, the ball does not matter as much since everyone scales accordingly. For some though, the power increase may be outsized, which distorts our ability for adjusting projections. Likewise with the pitchers.

Don’t rely on the straight projections alone - analyze the players yourself. If you have a reason to believe the projection is off - go ahead and adjust it.


Are Stats Alone Enough?

DE:  How much do you follow your own system? Do you watch a game or see a stat line and think, “I should go add him,” then check the projection and think “Nah”?

AC:  I always start with ATC. I say ‘start’ because part of the fun, and part of being a good analyst is to have your own opinions. If I identify a player as potentially undervalued by ATC - I will then do my own deep dive to see if my own intuition agrees. Is a newfound level a skill - or perhaps it was just dumb luck? Will a higher strikeout rate continue onwards? If Statcast thinks that the player was lucky - do I agree? And so on.

Don’t rely on the straight projections alone - analyze the players yourself. If you have a reason to believe the projection is off - go ahead and adjust it.

The most common case that I will adjust projections is for playing time. If I believe that the projections don’t realize that a particular player hurt his wrist - and won’t have his power stroke back until mid-season - I’ll take down the power totals when I run my own valuations.

As far as seeing a player play live - sure! If I see something I like or don’t like in a player - I’ll change the projection for my own use. That’s part of the fun in this game!

ATC is an amazing tool, and probably the best starting tool that you can use. But you don’t have to, and shouldn’t use it as the lone source of your draft prep.

If what you personally observe can make a strong case to veer from projections - by all means, adjust!

DE:  Do you ever use the eye test and think that the numbers get it wrong?

AC:  Similar to the question above - absolutely! Computers can’t do what the human eye can. Models do what they do - but the human eye is more trained to spot nuances. GIGO. If what you personally observe can make a strong case to veer from projections - by all means, adjust! You are probably right!

Remember - projections are based on algorithms. They look at 2017, 2018 and 2019 data. If an event or injury that occurred in 2018 affected a player’s statistics, AND it is NOT something that is properly accounted for a model - a going forward projection wouldn’t be accurate.

Let’s say that a player’s wife had cancer in 2018. He was completely healthy, but his power was cut in half that year. Perhaps he was more tired and worried about his family. A projection algorithm does not have a “worried about family” variable. The algorithm will simply assume that his skills are diminished. In this case, the human eye and reasoning ability will be the better predictor.

I speak of this example from experience. I believe that in 2011, Adam Dunn’s daughter was sick - and it weighed on him. His 11 home runs were uncharacteristically low for the White Sox slugger. I knew of this and realized that projections took 2011 as a skills decline. But the reality was that his skills were the same. I was able to draft a 40 HR player for just $1 that season en route to winning a few home league championships.

DE:  Based on projections versus ADP or human elements that aren’t captured by the numbers, who are a couple of players you’re targeting this year?

AC:  In general, I try not to call players “targets.” Obviously, there are players that I view as somewhat undervalued and a handful that are very undervalued. There are players I will have more shares of than others - I call them “potential bargains.”

Brian Anderson and Bryan Reynolds are two players that appear to be strong potential bargains. None are that exciting (to others), which helps keep their draft price down. But both provide enough support in at least four of five of the roto categories and are a safe bet to return a profit.

On the pitching side, Miles Mikolas is a player that had a poor 2019 after a wonderful 2018. The pendulum has swung both ways - and the question is … where will 2020 end up? While I don’t believe that the pendulum will sway all the way to his incredible ’18 results - I believe that the shadow of ’19 sets market expectations closer to the dark side. It also doesn’t help that he has a relatively low strikeout rate for a fantasy pitcher.

If you simply set Mikolas’s value close to the middle of the prior two seasons, he will earn a nice profit as a mid to late-round draft pick. I personally believe he will exceed projections, but the point is he should be profitable either way.

I will also be drafting Chris Archer this year. Just kidding.

More 2020 Fantasy Baseball Advice

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Introducing EDV - Expected Draft Values for Fantasy Baseball

Last March at RotoBaller, we kicked off a cool fantasy baseball research project, exploring what we're calling Expected Draft Values. This offseason, we’ve refined the approach and our research, and taken things a step forward. We're sharing this concept with the fantasy baseball world now, and hope it's as helpful to you as it's been to us.

A huge kudos to Nick Mariano (2018's Most Accurate MLB Draft Ranker) for leading this effort, and having the utmost patience for all my questions, ideas, and waffling throughout this project. You're the man, Nick.

Expected Draft Values is one of the more practically useful fantasy baseball data sets to be produced. It's being used by our writers in their articles and analysis, and now it can be used by you, dear readers, for your draft preparation.


What Are Expected Draft Values?

So frequently, we hear fantasy analysts say “Player X is a great value at that ADP.” How do they really know that? And more importantly, just how good of a value is that player? If you're deciding between two "value" picks during a draft, you would want to know which returns more value!

Expected Draft Values (EDV) try to provide concrete answers to these questions, so you're informed as to whether Player X not only provides profits, but how big a profit. Put another way, EDV answers the question:

What sort of stat production do I need, at a given draft pick, in order to break even, or turn a profit?


How Do Expected Draft Values Do This?

EDV provides historically-averaged 5x5 Roto stat lines for every draft slot, to help you understand the type of production you should be expecting with any given draft pick. Technically, we averaged out 1,000+ player-seasons and resulting Yahoo overall ranks from the past 5 years, sprinkled in some data smoothing, and came up with a data set that reliably shows the average stat line for the 10th best player, 20th best, 100th best, etc.

Not all players are made equal, though. If you're thinking about drafting a steals-first player, you need to reference that against other steals-first players. Comparing your steals target against power hitter stat lines wouldn't be so helpful, would it?

To make Expected Draft Values easier, we divided up the player pool into seven cohorts:

1) HR+BA+SB  2) HR+BA,  3) SB+HR,  4) SB+BA,  5) HR,  6) SB,  7) BA.

These seven cohorts are not perfect, as many players don't neatly fall into one of them. However, it was important to try and approximate the different types of hitters one targets. Too few cohorts and it would be difficult to find player comps, too many and we wouldn't have enough player-seasons in a given cohort to make the data viable. This is one area we may tweak and improve upon in the future. Here is how we defined the cohorts:

Cohorts Metric1 Metric1 Value Metric2 Metric2 Value Metric3 Metric3 Value % of Total
SB SB 13 19.73%
HR HR 26 20.70%
BA BA 0.288 20.55%
HR+SB HR 20 SB 9 10.35%
BA+HR HR 20 BA 0.284 10.87%
BA+SB SB 9 BA 0.284 10.13%
BA+HR+SB BA 0.28 HR 18 SB 9 5.36%

With these cohorts, when you use Expected Draft Values for a player like Joey Gallo, you're able to reference highly-relevant comparisons of other power hitters, rather than a general averaged 5x5 stat line. If you're wondering why we didn't factor RBI and runs into any cohort definitions, it's because RBI and runs are mostly a product of batting order, lineup, and the batting average and power of a player.


Expected Draft Values In Action

Here’s a quick example of how EDVs can be used with one of my draft targets last year and this year: Joey Gallo. Gallo, a power cohort staple, has an NFBC ADP of 80.6 as of Feb. 8 (he's lower on other platforms). Many attribute his ADP to his poor BA, but most analysts are largely guessing as to how much negative value is driven by his batting average. In my opinion, which is supported by EDV, most over-weigh the negative value of Gallo's BA and consequently misjudge how much value Gallo’s pop provides.

Luckily, we can reference our Expected Draft Values research to clear this up. If we go to the HR cohort and follow it down to row 81, we reach the average stat line for players who finished the season ranked 80th overall. The important assumption here is that if you're drafting Gallo at 80th overall, you're expecting a player who'll finish the year ranked at least 80th overall, otherwise you're taking a loss on that draft pick.

What we see in the power cohort of the EDV is that, on average, power hitters who finished the year ranked 80th have produced a stat line of .265-31-88-85-4. So, if we draft Gallo at his ADP of 80 and he outdoes that stat line, we profit. That's the power of EDV, we have a clear and simple break-even point that's rooted in real results around which to make judgments on value.

But the real power of EDV comes when we combine the EDV with either a ranking or a projection. RotoBaller’s esteemed rankers have Gallo at 56 overall, yielding a profit opportunity at an ADP of 80. If you prefer a comp with real projections instead of our rankings, RotoBaller's Nick Mariano projects a .232-44-101-89-8 line in 607 PAs for Gallo. If we compare Gallo's projected stat line to his break-even point (265-31-88-85-4), it shows less BA than we need (.232 vs .265, a 13% deficit), but significantly more HR (41% gain), a bunch more RBI (14% gain), a few more R (5% gain), and double the SB (100% gain).

Granted, we can't simply average these percentage gains / losses together. Because of volume, Gallo's 100% 4-SB gain is way less impactful than his 13% batting average loss. Nevertheless, it's clear that what Gallo loses in batting average, compared to the EDV break-even point, he more than makes up for in the other categories.

Additionally, Nick's projection assumes 145 games for Gallo, so a fully healthy season for Gallo would see his stat line top Nick's projection for him, and widen the gap even further from the EDV break-even point. Bottom line, if you believe in Nick's projection for Gallo being close, then he's a great value at his current ADP.

But just how good of a value is Gallo? This is where it gets interesting, as finding an exact comp for Gallo's projection in our EDV stat lines is not simple. As the draft cost column gets more expensive, BAs tend to rise. That makes sense - better ranked players usually have better BAs.

Gallo is a unique player, and in a perfect world we would have a "+Power -BA" cohort for him. Without that, we have to approximate and find our way to the ~48-50 overall range, where we find where the projected BA loss seems to even out with his HR / RBI / R / SB profit. And voila, we've used Expected Draft Values to find that Gallo's projected stat line sits near a 48-50th overall ranked player, one taken in the early part of the 5th round in a 12-team draft.

Quick Note on Draft Cost / Rankings

The Rankings (Draft Cost) we used came from Baseball Monster. We find them quite similar to Yahoo!, and superior to ESPN and CBS. Since we spent a lot of time averaging and smoothing the EDV data, we like to think that BBM's rankings would mostly converge with other platforms, and thus using BBM is as good as using any other platform's rankings. This is one area of this project which can and will be improved next year. Real fantasy rankings need to be league dependent, because the number of started / owned players in a given league influences the relative scarcity of stat categories, which impacts player rankings. Next year, we'll roll out EDVs which can be adjusted for league depth.


EDV Summarized

EDV shows us that Joey Gallo is being drafted in a spot (80) that has historically returned a stat line which he is projected to beat. Ergo, Joey Gallo is a solid draft target based on his current draft price. Use this to inform potential targets as you go.

A slightly longer explanation: Gallo's ADP at 80 seems a bit low right now. Gallo's EDV (the expected production for a power hitter taken 80th overall) is 265-31-88-85-4. If healthy, RotoBaller's projection for Gallo show he should have an easy time beating this break-even stat line, making him a a fine target after the top 50 picks are off the board, and a great target after the top 60. Additionally, RotoBaller has Gallo ranked at 56, further cementing the notion that Gallo is a nice value at his current ADP.


What about Pitchers?

Pitchers were way, way, way easier to approach for EDVs. This is because there really aren't different "types" of pitchers fantasy managers target, thus no need to break them out into cohorts. You might be thinking of Miles Mikolas and Kyle Hendricks, low-ERA and low-K guys. They do exist of course, but most high-K pitchers are also going to be low-ERA / low-WHIP pitchers, and low-ERA / low-WHIP are also going to be high-K pitchers. Here are some interesting observations with the Pitching data set:

  • Elite pitching is worth paying for (surprise!)
  • The "load up on cheap elite RPs" strategy is legit. Many more relievers than are actually drafted end up returning value equal to starters drafted in the mid-to-late rounds.
  • Once you get past the Top ~110 players, inning-eater pitchers tend to be over-drafted. It would be smarter to target higher-upside low-IP guys (Rich Hill and Hyun-Jin Ryu are classic examples).


What Are the Different Ways Expected Draft Values Might Be Used? Q&A Time...

  • If you're deciding between three players in a draft slot, could EDV be utilized to indicate which player is going to provide you with better value at this pick? 
    • If you are utilizing projections in your draft prep, then you can match a player's projection up with the best EDV comp, which informs the overall value they are projected to return. If all three players are available at the same point in the draft, then whichever one of them projects for the highest overall value is likely your best bet, all things equal. In that sense, we're using EDV to simply turn a player's projection into an overall projected rank as an alternative to ADP.
  • Can EDVs be used for determining whether a player's ADP is justified? Can it also be used for general draft strategy? If one decided to use EDV as a draft strategy, they would just become a "best value available" drafter, which isn't ideal, right?
    • Correct, EDV, when combined with rankings or projections, can be used for determining whether a player is a good value at their ADP, and how good of a value they are.
    • General strategy should come first in any draft before a simple "best available player" approach. Roster construction is one of the most critical factors when drafting, and may influence you to go "off board" at times.
  • The Speed cohort doesn't start until "draft cost 73", does that mean I shouldn't draft a speedster until pick 73?
    • No. A better way to interpret the data is that a "speed-only" guy shouldn't need to be taken before pick 70 because historically, players who finished ranked 70 or higher were in the other cohorts (SB+BA, SB+HR, SB+HR+BA), meaning they returned more value than a speed-only guy would. In other words, never draft a Mallex Smith mold in the top 70. Even if you think you're locking up a category, you're setting yourself up for a net loss. This may feel intuitive, but it's nice to see objective confirmation.
  • How do we find the best EDV comps for the guys that are average (maybe above-average) across the board? I.e. what cohort would we place Andrew Benintendi in, and is his ADP (107)  outlandish right now? 
    • Benintendi's projection (272-18-77-96-13) makes it particularly hard to comp him to any EDV. He's a five-category guy by virtue of not being really good or really bad at anything, but not good enough in BA to meet the BA+HR+SB tier. My guess is, if he returns his projection, he'd be fair value around pick ~130.
  • Is EDV just as reliable to spot small values as it is to spot big values?
    • Trying to find value with a 10-pick profit is a tough exercise, for two reasons. One, the profit can be wiped out by a small AB increase or decrease. Also, you'll notice that sometimes in the EDV data, the stat lines in 10 consecutive rows are quite similar, so finding exactly where a player belongs is a tough task to begin with. EDV is much more reliable in finding clear value gaps, as Gallo illustrates.


Some Concluding Thoughts

Many fantasy managers are swayed by brand names, for better or worse. This may help with some popular sleepers, but often hurts because the herd mentality causes many managers to target the same players, drive up their prices, and over-target well-known players, even if they’re declining. Our cognitive biases lead us to be overly reactive in fantasy drafts, reacting to last season(s), the last day or week of news, or the number of times we heard a name in draft season, at the expense of the larger picture.

EDV aims to help with these common draft problems, by establishing break-even baselines for every type of player for every draft slot. With these baselines in hand, we can make better informed decisions at every point with both draft prep and in the draft room itself.

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Using Sabermetrics for Fantasy Baseball: FIP and xFIP

The first advanced pitching stat most fantasy owners encounter is FIP. FIP stands for Fielding Independent Pitching, and attempts to measure a pitcher's actual skill instead of the effects of luck or his supporting cast. According to the DIPS theory, pitchers control only Ks, BBs, and home runs allowed. Therefore, Ks, walks, and dingers are the only inputs to determine the number.

For fantasy purposes, it is sufficient to understand the three primary inputs listed above and the fact that the stat is on the ERA scale. That means that if a FIP would be a good ERA, it is a strong FIP. The math is perfect, meaning that the league average FIP and ERA are identical (4.51 in 2019).

Sometimes xFIP is cited instead of FIP. The "x" stands for expected, and the stat is rooted in the fact that HR/FB varies for pitchers just as much as hitters. While FIP uses a player's actual homers allowed, xFIP charges him with a league-average amount of homers based on his fly balls allowed. Some pitchers are consistently more or less homer-prone than average, but studies show xFIP is a more reliable predictor of future ERA than regular FIP.


How to Use FIP and xFIP

This predictive nature of FIP and xFIP is the reason fantasy owners should care about them. Both metrics predict future ERA more reliably than ERA itself, making them a good go-to stat to determine if an early breakout may be for real or if a struggling superstar is likely to rebound. All things being equal, it is generally expected that a pitcher's ERA will regress towards his current FIP and xFIP over the long season.

For example, Marcus Stroman began the 2019 season on fire, posting a 1.43 ERA in March and April. However, his 3.90 xFIP suggested that he was nowhere near as good as he looked. Sure enough, his ERA ballooned to 4.31 in May (4.55 xFIP) and continued to fluctuate wildly throughout the year, including both highs (1.80 ERA in July) and lows (4.91 in August). If you started counting on him based on his hot start in April, you likely ended up disappointed.

There are certain types of pitchers that may consistently defy FIP. The first is knuckleball guys, who have challenged DIPS theory since its introduction. Sadly, nobody really threw a knuckleball in 2019, nor are any expected to make a fantasy impact in 2020.

The other type is simply called a "FIP-beater" that manages to control the quality of contact against him to the point that he outperforms his peripheral stats. Johnny Cueto has been a poster boy for this group for a while. He posted a sterling 2.25 ERA in 2014 before following it up with a solid 3.44 mark the next year. The 2016 season saw Cueto return to ace status with an ERA of 2.79.

Sabermetricians never saw Cueto that highly, however. His 3.30 FIP and 3.21 xFIP in 2014 made that campaign's 2.25 ERA look like a fluke, while his regression in 2015 (3.44 ERA, but 3.53 FIP and 3.78 xFIP) seemed like a harbinger of things to come. His sterling ERA in 2016 (2.79 ERA) was again undermined by considerably larger FIP (2.96) and xFIP (3.42) marks. Many analysts projected his demise in each of these years only to be proven wrong.

In 2017, they were proven correct. Cueto struggled to a 4.52 ERA, with a FIP (4.49) and xFIP (4.45) to match. His ERA rebounded to 3.23 in 2018 in an injury-shortened campaign (53 IP), but his underlying metrics (4.37 FIP, 4.67 xFIP) suggested that he was actually as bad as the previous year. Injuries limited him to 16 ineffective innings last season, leaving him as a wild card for 2020.

Pitchers like this rarely make good fantasy investments. Strikeouts are a key component of FIP, so pitchers who defy it are still lacking in a common fantasy category. Why risk a poor ERA for two-category upside? There is an ongoing debate in the sabermetric community though, so my word is not gospel on the subject.


What is SIERA?

SIERA stands for Skill-Interactive ERA and attempts to measure a pitcher's true talent more accurately than FIP and xFIP. It is marginally more predictive than xFIP, but its increased complexity may not be worth it. The stat assumes that ground ball pitchers will have a lower BABIP on grounders than other pitchers, while fly ball pitchers will have lower HR/FB marks. It is also adjusted for overall run-scoring environment and a pitcher's home park.

That may sound good, but remember that those adjustments won't affect your fantasy team's bottom line. German Marquez posted a 4.76 ERA for the Rockies last year, but his SIERA was only 3.85 in part to "correct" for Coors Field. Obviously, pitching at Coors will not improve your fantasy team's ERA. SIERA is also not on the ERA scale, with a league average of 4.41 to the 4.51 the other metrics last season.



To conclude, FIP and xFIP are metrics that try to determine the ERA a given pitcher deserves based only on the outcomes he actually controls: Ks, BBs, and home runs allowed. While FIP uses the pitcher's actual homers allowed, xFIP regresses it to the league average figure. Both metrics are on the ERA scale, and may be used to predict future ERA with more accuracy than ERA alone. Check out some of these articles if you want to learn more about applying sabermetrics within a fantasy context.

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2020 RotoBaller Fantasy Baseball Mock Draft Reactions

Over the last couple weeks, RotoBaller's roster has grown with several new faces to join our esteemed veteran corps. We figured it would be nice to roll out the welcome wagon with a February fantasy baseball mock draft, putting six "RotoNewbs" with six RotoVets.

It was a snake draft hosted on Fantrax, a traditional 5x5 format with C, 1B, 2B, 3B, SS, CI, MI, 5 OF, UTIL, 9 P and 4 Bench slots. We'll post the draft board here, alongside rapid reactions from each participant.

In draft order, they are: KC Bubba, Bill Dubiel, JB Branson, Ariel Cohen (2019 FSGA Baseball Writer of the Year, woo!), Eric Samulski, Riley Mrack, Anthony Aniano, myself aka Nick Mariano, Mike Kurland, SP Streamer, Pierre Camus and Jorge Montanez. Without further ado...


The Draft Board

click image to see full-size draft board


Draft Reactions

What was your strategy, and was it executed well?

KC Bubba: With the first overall pick, I was looking to load up on some of the top bats. Grab one early arm and then fill in the rotation in the middle rounds. After that fill the rest of my team needs. I feel I executed it very well. I should have a strong hold on four offensive categories, and still not to bad in the fifth, steals. I was most proud of the way my pitching staff came together. Grabbing Snell gave me an ace caliber arm in Round 3, but was able to really build a strong rotation with picks in Round 7 on.

Bill: I went very power and strikeout-heavy in this one. I tried to find the sluggers that would help in multiple categories vs. the one-dimensional homer guys for hitters. For pitchers I targeted high-strikeout guys that I thought would also help in multiple categories. Essentially punted on saves, and tacked on some cheap steals late. I executed the strategy just as I envisioned it, and I'm happy with almost all of my picks at the values I got them at.

JB: It's always the same. Get as many speed-power studs as I can early while building a solid IP and K base for my five-man rotation. Then as the 20/20 skills dry out, I make sure to balance out the rest of the lineup with alternating power or speed guys. Balance is the key to life. After my five-man rotation is done, I go for the RPs until I can't RP no more. The JBullpen Method, folks..

Ariel: My strategy was "Replacement Level Drafting" (RLD). I looked to see which position had the biggest drop to the following players - and pounced at the top player at that position. I thought that allowed it me to acquire a lot of value in the aggregate. Mission accomplished. I also figured I'd get Jacob deGrom to start, which I did.

Eric: I came into the draft intrigued by a lot of mid-round SP options, so I decided to load up on hitters early and add high-upside arms in the middle rounds. Also, in this league with nine P spots, I decided that elite ratio relievers were more valuable to me than run-of-the-mill starters. They can help me in ERA, WHIP, SV and K if they get enough appearances and balance out some bad starts from my few SP. Overall, I'm happy with how I did, but I pushed my luck with a few arms that went right after I thought I could slip them through one more round and a few arms that I got sniped on. In the future, I might add one true ace to lead the rotation and then wait until Round 9 or so to start adding more arms.

Riley: My strategy was to pass on the elite pitching and take several of the middle-tier hurlers instead. For the first handful of rounds, I was selecting the best hitter available, but I felt I was too far behind on the pitching side after it was all said and done. This was a good spot to try this method versus several savvy players, and it made me realize the importance of taking an ace in the first two rounds..

Anthony: I wanted as much balance as power. Drafting a five-tool offensive player and a number one starter in the second round created that foundation. Mixing power like Pete Alonso with speed from Victor Robles adds to that balance.

Nick: There were a few things I wanted to test drive: How does it feel to go SP in Round 1 of 2020 drafts? How do I like drafting with two SPs within the first three rounds? Can I make it work with both Adalberto Mondesi and Jonathan Villar on the squad? How long can I wait to flesh out my rotation with two early, strong SPs in a 12-team format? I loved how this team turned out, and I'm a huge fan of all the veteran values that slipped down to me. Batting average is the likely liability, but the HR+SB upside still gives me a strong offense.

Mike: My goal was to target two or three of my top 25 starting pitchers and grab all the power and speed combinations guys I could. I definitely liked the outcome but I maybe have left myself a little light on power.

SP Streamer: I wanted to go hitting early and chase upside. It definitely happened as I grabbed Keston Hiura and Fernando Tatis Jr. early. I have to say I normally don't draft like that and wanted to see how it turned out. Hate the team.

Pierre: I tried out an early SP stack to see if I could come away happy with my lineup in a 12-team league. Generally, I was happy with the results but four pitchers in the first eight rounds might have been unnecessary.

Jorge: Picking at the end of the first round, I missed out on some of the big combo bats like Francisco Lindor and Trevor Story. So, I grabbed two aces in Justin Verlander and Max Scherzer to lock down pitching early then looked for value bats later on. The way the draft fell for me, I think i went too pitching heavy. In hindsight, I probably would have taken someone like Jose Ramirez at the first round turn with one of the aces.

Your favorite pick?

KC Bubba: This was between Zac Gallen in round 10 and Robbie Ray in Round 14. I will go with Ray. Being able to lock down an upper-echelon arm like Ray, at pick 168, was great. Ray was my 5th starting pitcher and has the upside to be an SP2 on your fantasy rosters. Ray brings major strikeout upside and if he can hone in the walks his ratios would be amazing.

Bill: Carlos Correa in the 11th seemed like too good a value to pass up. The main knock against him is that he's been hurt for a decent chunk of each of the last three seasons, and while that's a valid concern I'm willing to take a chance on a 30-homer, 100-RBI guy once we're in double-digit rounds. I honestly believe there has been some bias in mock drafts against the Astros given the cheating scandal and concerns over production moving forward.

JB: Carlos Santana in the 11th was exactly what I needed after waiting out 1B. I was also a little light on power so ill take a 30 HR, 90+ R/RBI veteran in the 11th every time. I think Santana will be my 1B target in every draft with the other Santana (Danny) as Plan B or acting as the trigger to take Carlos like what happened here with KC Bubba taking Danny 2 picks before me.

Ariel: Austin Meadows - I felt like I committed a robbery getting Meadows all the way at pick 55. He is a 5 category stud who may return 1st round value.

Eric: Jason Castro. OK, not really, but I think people are sleeping on Castro this year. It was Khris Davis in the 14th round at pick 164 overall. His production last year was impacted by his hip injury, which he never fully recovered from. I expect him to push 40 HRs again the middle of a strong offense with good RBI and R totals.

Riley: Nick Castellanos at 9.7 was a terrific value since I have him ranked higher than several outfielders that were taken before him. Comerica Park really suffocated his power, and it showed when he clubbed 16 long balls in his two months playing for the Cubs. The move to Cincinnati is monumental, and he'll slide nicely into that lineup with other potent bats around him.

Anthony: Charlie Blackmon in Round 5. I was shocked he fell to that point.

Nick: Edwin Encarnacion in Round 13 feels goofy. I know the playoff slump soured us Yankee fans and durability concerns loom at age-37, but he still hit 34 homers with 167 R+RBI in merely 109 games! Yes, that's nearly two-thirds of a season, with simple math highlighting the 50-homer pace in a full year. Now on a suddenly-stacked White Sox team, E5 is here to provide profits in 2020. Shouts to Justin Upton in Round 17 as well.

Mike: Cavan Biggio at pick 153 felt like a steal. He has legitimate 20 home run and 20 steal upside. Yes, the batting average is a concern but at this point the upside couldn’t be ignored in this format.

SP Streamer: I have to say two picks here, the back-to-back picks of Charlie Morton and Luis Castillo I loved. Combining both of them could be a lethal combo in 2020.

Pierre: Waiting on 1B seems like a bad idea but if I can get Christian Walker in the 15th round, I may take that tactic more often.

Jorge: Bo Bichette in the sixth round. After taking two pitchers early, I had some making up to do in the hitting categories. Bichette could be a 20/20 player with a good average and end up being a huge value here.

Your least favorite pick?

KC Bubba: Salvador Perez in round 15. I do love Perez, have written and talked about him often, but he wasn't a good pick in this draft. For this mock, it is a one catcher league and I broke my golden rule of waiting till late on catchers. If this were a two catcher league I would be pumped, but it is not. With players like Carson Kelly going in round 25, I should have waited.

Bill: I think I probably could and should have waited on catcher given the way this mock unfolded. Gary Sanchez fit my strategy well, but I think I could have waited and got a comparable power threat a few rounds later.

JB: Omar Narvaez in the 18th. I could've waited a little longer and still gotten Wilson Ramos or Carson Kelly. I didn't feel like I would be upset if I missed out on any of the remaining guys on the board, so I went ahead and got my guy. He's being undervalued this year and people are looking for reasons to bump him down despite a move to Miller Park from Seattle. Three straight seasons of .275 BA and showed he's got 20+ HR power. I will certainly hold off a round or two before I grab him next time, though.

Ariel: Brian Anderson. I might have grabbed him some 2+ rounds earlier than he would have gone and should have taken Eric Hosmer or Aristides Aquino instead.

Eric: Jake Odorizzi in the 15th round. I panicked and felt like I needed another SP right then, instead of trusting the plan for upside arms and snagging Andrew Heaney or adding more offense and waiting a couple of rounds for a guy like Luke Weaver, AJ Puk, or Mitch Keller. Shoot, even David Price a few rounds later would have been better.

Riley: I regret taking Vladimir Guerrero Jr. at 5.6, not because of his lack of ability, but seeing how far other third basemen like Josh Donaldson, Matt Chapman and Mike Moustakas fell. I would have been better off taking a pitcher with this pick and waiting at the hot corner for another few rounds. The drop off at pitcher is much more substantial through Rounds 5-10 than it is at third base.

Anthony: Gavin Lux in round 11 as my second basemen. The Dodgers have so much depth he can be on the bench if he struggles.

Nick: I don't dislike Brandon Lowe as an overall buy this season, but I had no clear lean construction-wise so I just let my board do the talking. Seeing Ryan McMahon in Round 20, Luis Arraez in Round 22 and Dansby Swanson in Round 23 doesn't feel great compared to the higher price tag paid for Lowe.

Mike: Not that I hated the pick by any means, but Kris Bryant in the 6th round is my least favorite pick due to how my team turned out. I should’ve taken more power there. Bryant is not a bad power bat but I needed someone with 40 plus home run potential and I don’t believe Bryant to be that guy.

SP Streamer: By far it was Hiura, I hated that pick and questioned it the second I picked him. Again I was trying for high upside while going for steals so it made sense. But I think it really put a hole in my team.

Pierre: I won't be taking Chris Sale in Round 3, if at all this year. Too much risk and it left me feeling compelled to take more arms early.

Jorge: Max Scherzer in the second round. Not that Scherzer is a bad pick there, but I had already taken Verlander the pick before. What I found in a 12 team draft is that it's easier to get pitchers I like late such as Matthew Boyd and Madison Bumgarner. I would have been better served taking a top hitter there like Jose Ramirez or Fernando Tatis Jr.

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Using Sabermetrics for Fantasy Baseball: Lineup Spot

You may be wondering why there aren't any advanced stats aimed at predicting a player's counting stats like runs and RBI. The answer is simple: modern sabermetrics reject the idea of a "clutch RBI guy" and therefore do not bother inventing predictive metrics for it. Runs and RBI are team-dependent stats and are unhelpful in ascertaining a given player's real value.

That might work for statheads, but fantasy owners frequently see 40% or more of a player's value tied to his RBI and run totals. We have to care about them. Drafting hitters from strong offenses can help pad the totals, but as you'll see, an even bigger advantage can be found by looking at a player's slot in the batting order.

Don't believe it? Yankees second baseman Gleyber Torres smacked 38 HR and hit .344 with runners in scoring position last season in a loaded lineup. Unfortunately for his fantasy owners, he hit fifth or lower for the Yanks in 93 of his 144 games played. His counting stats (96 runs, 90 RBI) accordingly fell well short of what you would expect given his other numbers. Here is a closer look at how to analyze a batter's lineup slot for fantasy purposes.


Lineup Slot & Counting Stats

In the table below, each batting order slot's PA, Runs, and RBI are presented from the 2019 season. The final number is simply R + RBI, an approximate measure of that slot's overall value to a fantasy team.

1st 22,823 3,323 2,320 5,623
2nd 22,281 3,279 2,623 5,902
3rd 21,760 2,917 3,021 5,938
4th 21,259 2,827 3,109 5,936
5th 20,794 2,627 2,848 5,475
6th 20,249 2,345 2,500 4,845
7th 19,705 2,195 2,267 4,392
8th 19,122 2,105 2,086 4,191
9th 18,518 1,849 1,699 3,548

Each batting order slot loses around 500 PAs compared to the slot before it. If we divide this total by the 30 current MLB clubs, we get a difference of around 17 PAs between consecutive hitters on one team. That may seem insignificant, but it compounds. For example, there is an average of 34 PAs separating a team's leadoff man from the three-hitter. Counting stats like Runs and RBI require an opportunity to accumulate, and hitters earlier in the batting order have more opportunity. Bear this in mind when comparing similarly skilled players on draft day.

RBI are highest from the cleanup spot, and trend downward in both directions from there. Leadoff hitters only get more RBI than the seventh, eighth, and ninth spots despite the largest PA total. This is because they never have runners on base before their first PA of the game, and need to rely on the weaker eighth and ninth hitters to get on in front of them after that. Since good hitters are usually clustered early in the order to maximize their PAs, leadoff men get minimal help from their teammates in producing RBI.

Runs peak at the leadoff slot and decrease from there. This decrease is not linear, as only 44 runs separate the first and second spots while 362 separate second and third. For this reason, fantasy owners want to stick to the early batting order slots where teams cluster their best hitters if possible. Leadoff guys have the most opportunity and the team's best hitters hitting behind them, so they score a lot of runs for the same reason they do not register many RBI.

Finally, the R+RBI column refutes the idea that a team's heart of the order is 3-4-5. It is actually 2-3-4, the only lineup slots to approach 6,000 combined R+RBI. The 1st slot is great for runs scored, and the 5th spot offers a respectable 5,475 R+RBI. However, the others clearly lag behind. This means that a player in the middle of a weaker offense is likely to outproduce a player on the periphery of a stronger one. Platoons, injuries, and lineup shuffling can change these numbers, but in general the earlier the slot, the better for fantasy purposes.



To conclude, counting stat production depends on opportunity and team support. Players that bat early in the order tend to get more of both, though leadoff men give up RBI potential for increased runs scored. If you would like to learn more about how to apply sabermetrics within a fantasy context, check out some of the other articles linked here.

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Using Sabermetrics for Fantasy Baseball: Pull%

We have previously determined that fantasy owners generally prefer batters to hit the ball into the air in order to have a chance at a home run. Yet, all fly balls are not equal for this purpose. A player can maximize his power production by pulling the ball in the air.

One way to illustrate this is to look at league-wide HR/FB by batted ball direction. Flies to the opposite field seldom found the cheap seats, posting a HR/FB of just 6.1% last season. Flies to dead center fared slightly better (10.8% HR/FB), but pulled fly balls were clearly the most productive (37.1% HR/FB).

Let's take a closer look at how Pull% can help you win your fantasy leagues in 2020!


How to Interpret Pull%

In 2019, roughly 58% of all home runs were to the batter's pull side. Only 16% of homers went to the opposite field, with the remaining 26% going out to center. This distribution is fairly consistent year-to-year, so it's safe to count on something similar going forward.

In a way, this makes intuitive sense. Pulled baseballs tend to be hit with the highest exit velocity, making it easier for them to leave the stadium. The power alleys next to the foul poles on either side of the ballpark also present the shortest distance to the cheap seats. If a player's HR/FB dramatically improves, a change in approach involving more pulled baseballs could help explain why.


How Pull% Affects Fantasy Performance

Boston's Xander Bogaerts provides a good illustration of this kind of change. In 2015, he pulled only 16.7% of his fly balls, producing a HR/FB of 5.3% and a total of seven dingers. He significantly upped his power game in 2016 by pulling 28.1% of his flies, leading to a much higher 11.4% HR/FB and 21 bombs on the campaign. The increased power was not exclusively the result of the Pull% spike, as he upped his FB% as well (25.8% in 2015, 34.9% in 2016). It helped to validate his HR/FB increase, though.

His change in approach did not last. Bogaerts pulled only 24.5% of his flies in 2017, dropping his HR/FB to 7.2% and his season HR total to 10 in the process. Once again, the raw number of fly balls Bogaerts hit decreased (30.5% FB%), so the change in Pull% was not solely responsible for the loss of power. This example illustrates that while a change in Pull% can support an increased HR/FB, it will only last so long.

In 2018, Bogaerts clubbed 23 HR on the back of a FB% spike (35.6% FB%) and a 15.5% HR/FB. However, his Pull% on fly balls decreased to 23.7% that season. Bogaerts finally put it all together last season, posting a career-best 33 long balls on the back of a career-best FB% (39.8%) and a 29.3 Pull% on those fly balls that contributed to a 16.7% HR/FB.


The Problem with Raw Pull%

Of all pulled baseballs in 2019, 58.2% were grounders. Pulled grounders might have a higher average exit velocity than other ground balls, but the shift still eats them up with minimal difficulty. They will never turn into home runs. In contrast, only 21% of pulled baseballs were classified as fly balls last season. Ideally, fantasy owners want their hitters to pull fly balls while limiting how often they roll grounders to their pull side.

This is much easier said than done, as all players pull many more grounders than flies. Let's consider Mike Trout as an example. His raw Pull% of 42.4% was marginally higher than the league average 40.7%, and he pulled 61.6% of his grounders compared to 28.7% of his flies. At first glance, you might think that Trout was making himself vulnerable to the shift without significantly boosting his power potential.

That assumption would be wrong. The shift was designed for batters who pull much more than 61.6% of their ground balls, allowing Trout to hit a solid .303 against it last year. Many batters fail to pull even 20 percent of their flies, so Trout rated well enough in that regard as well. Pulling more grounders than flies is far from a death sentence.



To sum up, pulled fly balls tend to perform better than other fly balls. This means that pulling more flies can produce an increased HR/FB, but you should never use raw Pull% to determine this. Most pulled balls are hit on the ground, where all of the exit velocity in the world cannot turn them into home runs.

Therefore, you should filter a player's Pull% by batted ball type to produce the most reliable results. If you're interested in learning more about the role of advanced analytics in today's fantasy environment, check out some of our other articles here!

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Early Mock Draft Analysis and Reaction: Fantasy Baseball

Pierre Camus and Nicklaus Gaut review the draft board from an early 2020 mock draft for fantasy baseball mixed leagues.

Like and subscribe to the RotoBaller channel on Youtube to get all our latest podcasts and catch us on iTunes and BlogTalkRadio as well!

Be sure to also tune into RotoBaller Radio on SiriusXM (channel Sirius 210, XM 87) - every weekday morning between 6-7 AM ET, every weekday afternoon from 1-2 PM ET, Saturday nights from 9-11 PM ET and Sunday mornings from 8-10 AM ET. You can also find new weekly shows on the site under RotoBaller Radio podcasts.


Mocking It Up

Pierre and Nick discuss results from a recent RotoBaller analyst mock draft to see how player ADP has already started to shift and to pick out the biggest values and reaches.

Players discussed include:

Fernando Tatis Jr.
Jacob deGrom
Justin Verlander
Manny Machado
Vladimir Guerrero Jr.
Brandon Woodruff
Danny Santana
Nate Pearson
Travis Shaw
J.D. Davis

Thanks for listening to today's episode! Be sure to tune in throughout the week, and to also follow RotoBaller on Twitter, YouTube and iTunes for the latest fantasy news and analysis. We are your secret weapon...

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When Should You Draft Your First Starting Pitcher?

Pierre Camus and Nicklaus Gaut decide when you should pull the trigger on your ace in fantasy baseball drafts this year. How early is too early and can you wait to take your first SP?

Like and subscribe to the RotoBaller channel on Youtube to get all our latest podcasts and catch us on iTunes and BlogTalkRadio as well!

Be sure to also tune into RotoBaller Radio on SiriusXM (channel Sirius 210, XM 87) -every weekday morning between 6-7 AM ET, every weekday afternoon from 1-2 PM ET, Saturday nights from 9-11 PM ET and Sunday mornings from 8-10 AM ET. You can also find new weekly shows on the site under RotoBaller Radio podcasts.


Aces Up

Pierre and Nick discuss starting pitcher ADP in the early rounds to determine when the best time to grab your SP1 is and who you should target.

Thanks for listening to today's episode! Be sure to tune in throughout the week, and to also follow RotoBaller on Twitter, YouTube and iTunes for the latest fantasy news and analysis. We are your secret weapon...

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Using Sabermetrics for Fantasy Baseball: Plate Discipline

No matter how high a particular player's BABIP may be, his average will be mediocre at best if he strikes out too much. This is why fantasy owners have known for years that players like Chris Davis are potential drains on a fantasy team's batting average. Furthermore, players that whiff a lot tend to continue to do so - it is a very sticky trait.

In 2019, the league average K% was 23%, meaning that roughly one in five MLB PAs ended in a K. Players who strikeout less frequently tend to hit for higher averages, while more strikeouts hurt batting average. Of course, a player may put up a fluke K% just as easily as a fluke BABIP.

Let's learn how analyzing stats related to plate discipline can help improve the performance of your fantasy baseball team entering the 2020 season.


How to Interpret Plate Discipline

Sabermetrics may be used to determine whether a given player "deserved" his K% over a particular period. The first number to check is SwStr%. This metric simply tracks what percentage of pitches a batter swings and misses at. The league average was 11.2% in 2019, with higher numbers indicating a proneness to K. If a player improves his strikeout rate without a corresponding improvement in SwStr%, the improvement is unlikely to stick moving forward. Likewise, a career-worst strikeout rate backed by a normal SwStr% is likely to regress in the player's favor.

Notably, Baseball Savant's Whiff% is not the same thing as SwStr%. Whiff% measures how often a batter swings and misses on all swings, while SwStr% uses all pitches seen instead. Whiff% figures are therefore much higher than SwStr%. Since SwStr% is used much more frequently in fantasy analysis, the rest of this article will use it.

Further detail is offered by O-Swing%, a measure of how often a batter swings at a pitch outside of the strike zone. Batters usually want to hit "their pitch," which they never get to see if they pop-up a fastball over their head early in the count. In 2019, the league averaged an O-Swing% of 31.6%. Numbers significantly higher than this indicate an increased likelihood of chasing a bad pitch and making poor contact or striking out.

This stat is also used to examine a player's walk rate, or BB%, in much the same manner as SwStr% is used to double-check K%. A strong walk rate when a player is still chasing too many pitches is not based in any repeatable skill, and will likely be normalized moving forward. Likewise, a lower walk rate paired with a career average O-Swing% indicates that the walks should come back.

Fantasy owners should always care about walks even if their format does not directly reward them. Every BB is a chance to steal a base or score a run, and players that know the zone tend to hit for higher averages to boot!


Evaluating Players Through Plate Discipline

Joey Votto is widely regarded as the master of plate discipline, and his surface stats support the assessment. His 12.5 BB% was really strong despite a down year overall, while his 20.2 K% bested the league average. Digging deeper, we find that these numbers are completely justifiable. His 21.1 O-Swing% was more than 10 percentage points better than the league average rate, and his 7.3 SwStr% was below the average as well. It is safe to conclude that Votto will continue to demonstrate outstanding plate discipline in 2020.

Cincinnati's Aristides Aquino does not measure up as well. He hit a reasonable .259 last season in spite of striking out at a 26.7% clip. He chased too many pitches outside of the strike zone (41.2%), making it tough to project a repeat of his 7.1 BB%. Worst of all, he whiffed at 18.9% of the pitches he swung at, one of the worst marks in baseball. Owners are drafting Aquino for elite power upside, but his plate approach is so bad that his batting average and OBP could crater to unrosterable levels.

Aggression or passivity at the plate can confound this analysis slightly. For example, Aquino was extremely aggressive last year with a Swing% of 55.7%. The league average was 47% in 2019. Even if a hitter has a high chase rate, he can't strike out if he resolves the PA before three pitches are thrown. Votto is on the opposite side of the spectrum, as his refusal to swing at borderline pitches (41.5 Swing% last year) leads to more Ks than his raw SwStr% numbers would suggest.

Other plate discipline metrics exist, such as Z-Swing%, O-Contact% and Z-Contact%, but SwStr% is usually a good enough proxy for fantasy purposes. One exception to this rule is a change in SwStr% rooted exclusively in pitches outside of the zone. Sometimes, missing those pitches can be better than hitting them.



To conclude, both K% and BB% are useful for fantasy purposes but fail to tell the whole story. SwStr%, or how often a batter swings and misses, is a better indicator of a player's future strikeout rate than K% alone. O-Swing%, or how often a batter chases pitches outside of the zone, performs similarly concerning BB%. If you would like to learn how to use more metrics to determine fantasy performance, check out our other articles on the subject here!

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Using Sabermetrics for Fantasy Baseball: Batted Ball Distribution (Hitters)

Fly balls can turn into home runs. Ground balls never do. It would seem as though fantasy owners want their batters to hit nothing but flies, yet this is not always the case.

Why would this be? The answer, of course, comes down to batted ball distribution and the manner in which batters make contact. The league average batted ball distribution in 2019 was 21.4% line drives, 42.9% ground balls, and 35.7% fly balls. Most individual players vary from this standard breakdown, providing insight into their fantasy viability.

In this article, we'll continue evaluating the most effective ways to use sabermetrics to get an edge in your fantasy baseball leagues.


The Value of Line Drives

Let's first look at how all major leaguers fared on each of the major types of batted ball in 2019. Grounders generated a BABIP of .236. Flies were not as productive, posting a .118 figure. This makes sense, as pop-ups almost never fall in, cans of corns to the outfield are only slightly better, and homers are considered out of play and do not count toward BABIP. Line drives turned into base hits far more frequently than either of the others, posting a .678 BABIP. The difference between liners and anything else is startling. Batters want line drives.

Tim Anderson's stellar 2019 provides a good illustration of what a few extra liners can do. He posted a .335/.357/.508 triple-slash line thanks in part to a 23.8% line drive rate, a far cry from his career line of .276/.303/.475. Anderson was an afterthought in real and fantasy baseball terms heading into 2019 but ended up surprisingly productive in both areas.

A player's LD% tends to bounce around the league average with random spikes and drops, none of which offer much predictive value moving forward. Anderson has a 20.9 LD% over his career, so luck was almost certainly the primary driver of his 2019. When BABIP is driven by luck, LD% is usually why.

This is not to suggest that no one consistently posts above-average LD% rates. For example, Joey Votto's career .349 BABIP is driven by his career 25.7 LD%. Considering the length of his career, it would be stupid to suggest that Votto has enjoyed a lucky decade-plus. Therefore, we give credit to Votto for being a plus-BABIP guy due to a LD% skill, just like we give Christian Yelich BABIP credit for his blinding speed. This distinction has to be earned over numerous full seasons, however. Most LD% surges are more fluky Tim Anderson than sustainable Joey Votto.


Which Is Better: Ground Balls or Fly Balls?

Unlike LD%, both GB% and FB% are stickier--a player with an elevated rate in one is likely to repeat a similar rate moving forward. By BABIP alone, grounders are better. However, this changes significantly if slugging percentage is considered. In 2019, grounders offered a slugging percentage of .258, only slightly higher than the .236 BABIP they posted. Flies had a .788 slugging percentage, easily offsetting the lower BABIP for most fantasy players. Sluggers like Cody Bellinger who lift the ball at an exceptional rate have a built-in slugging advantage because of their batted ball profiles.

The ideal batted ball mix, therefore, varies with the player. Elite speedsters like Billy Hamilton want more grounders than flies, as his career 3% HR/FB is never producing a lot of homers anyway. Sluggers like Albert Pujols want fly balls, especially since the shift and his lack of speed prevent him from realizing the larger BABIPs associated with grounders anyway. Fantasy owners usually prefer players with power and speed potential to have a higher FB%, as the extra power is more beneficial than a few extra times on base.

Incidentally, line drives averaged a ridiculous .916 slugging percentage to go with their .678 BABIP in 2019, so they are still the batted ball of choice.



To conclude, line drives are by far the most productive result for hitters. BABIP's luck-driven fluctuations are driven by LD%, a largely random stat. GB% and FB% are more predictive, and which one is favored depends on the hitter in question. Grounders offer a higher BABIP, but almost zero power. Flies result in base hits less often, but generate much more power when they do. The intricacies of BABIP could be a never-ending topic, but the information provided so far is generally enough for fantasy purposes. Check out this link to learn about some other metrics that can help you predict a player's performance.

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Early Mock Draft Analysis: MLB Mixed Leagues

Don't tell us it's not draft season yet! Truth be told, the RotoBaller crew was already planning a mock draft days after the World Series ended. As it turns out, we decided to wait until some free agent moves were made and settled for a slow draft that began shortly after the Winter Meetings.

We gathered some of our finest fantasy baseball writers in order to conduct a 10-team, 24-round, mixed-league redraft mock. Once the draft wrapped up, I sat down (figuratively) with each participant to get their takes on some of the more interesting picks or strategies they employed.

Once you finish deciphering the color-coded graph below (it's a beaut, ain't it?), you can read about the thought processes behind the final result.


Early Mock Draft Results

Click on image above for full-size view


Riley Mrack

Ronald Acuna is becoming more popular as the #1 overall pick over Mike Trout. How confident are you that he will live up to expectations and did you have any pause before that selection?

I had no hesitation when selecting Ronald Acuna Jr. with the first pick for a few reasons. He was three steals away from being the fifth player ever to join the illustrious 40/40 club at age-21 and is the only player capable of reaching these marks again in 2020. Trout is undoubtedly a superior overall hitter, but after three straight injury-shortened seasons and an 11-steal 2019 campaign, his double-digit SB streak is in jeopardy. Acuna Jr.'s speed is the difference-maker for me since they are comparable in all five roto categories except for thefts.

You were the first to take a reliever (Hader) and secured three closers in the first 12 rounds. Is this something you typically do and why?

I generally don't reach for relievers, but I felt this was a good opportunity to try this strategy. 30-save closers are becoming a rare commodity, so I locked up three players who should put up sterling ratios and maintain the ninth-inning job all season. Drafting at the turn also affected my mentality because I would rather start a reliever run than miss the boat on it completely. Judging by how my team turned out, I'd implement this strategy in some leagues so I won't have to rely on volatile arms or scavenge the waiver wire all season looking for saves.


Michael Grennell

You were the first one to draft two SP, in rounds 2 & 3. How important do you think it is to grab at least one ace early this year?

Starting pitchers and outfielders will always have the most shallow free agent pool after the draft, since most owners will be drafting five or more at those positions as opposed to drafting one or two at the infield positions. That means that after the first round most owners should prioritize either a top tier starter or outfielder in order to maximize your team's potential. It's far better to grab a Scherzer/Buehler/Flaherty/Clevinger early on, than wait until around the 10th round and have Madison Bumgarner as your best pitcher.

Aristides Aquino is a polarizing player this draft season. What are reasonable expectations for him and can we consider him an OF3 in most mixed leagues?

If there was one pick I would do over it would be Aquino; I think I would've tried waiting another round to grab him. Obviously, he had that amazing stretch in August, but that production fell off drastically in the final month of the season. But that performance in August intrigues me, and he has averaged 22 homers over his last four seasons in the minors. I think owners should look at him as a fringe OF3 in most formats but a definite OF4.


Ellis Canady

Aside from Yelich and a handful of steals from Harper, your team might be devoid of speed as you don't seem to have a true speedster on your team. Do you intentionally forego SB in order to bolster other stats or was this a matter of best player available in each round?

Speed is an important category as there are few players that sell the product you need. There are really only three ways to tackle it: speedster-heavy, spread the responsibility, and punt the category. The last one is not an option for me. Since I didn’t draft a speedster in the first round (Trea Turner), I chose to spread the responsibility, which is usually my preferred method. I expect Christian Yelich, Bryce Harper, Keston Hiura, Bo Bichette, Adam Eaton, and Amed Rosario to pitch in double-digit steals. Add a dash of stolen bases from a few of the others (George Springer, J.T. Realmuto, Rafael Devers, Andrew McCutchen) and I should be comfortably competitive in the category.

With the wealth of quality shortstops around, waiting to grab Bo Bichette as your starter seems like a calculated risk. Are you expecting a full-blown breakout season?

As stated, the shortstop position is rich with talent. I’m pleased to get Bo Bichette in the 12th round with the potential. His hand was broke in April of 2019, but he still returned and provided 11 homers and four stolen bases with a .384 wOBA after a promotion to the big leagues. I’m not naïve to think 2020 will be filled with funnel cakes and lemonade. However, I’d set the floor at a 20/20 guy with a very good batting average. Just in case, I backed him up with a 15/15 guy in Amed Rosario.


Scott Engel

Was grabbing Pete Alonso in round three a case of prioritizing an upper-tier first baseman because of the lack of depth there or are you just a believer that he'll repeat last year's numbers?

At that point, I could not pass on Alonso for the power and RBI production. The combination of his average Launch Angle and Barrel rate should translate into another big power year. If his Average Exit Velocity climbs, the results could be massive.

Between Adalberto Mondesi, Tim Anderson, Oscar Mercado and Mallex Smith, you'd be a sure bet to lead the league in steals. Do you make it a point to go after potential category-winners in SB?

I am always gunning for speed. Power is easier to come by. I like to space it throughout the draft to build a good final product in that regard.


Kev Mahserejian

You were the last analyst to select a relief pitcher and all three of your RP combined for 31 saves last year. Do you believe chasing closers early is a mistake?

Unless a closer sees an egregious fall in price, I typically stray away from drafting them early on. It's a strategy I've maintained throughout the years that has won me my fair share of leagues. I do not necessarily think it is a mistake to chase closers early if you hit on them. However, the position of closer is so volatile year-to-year in enough cases that I will choose to play my cards elsewhere. Several closers always pop up on the waiver wire throughout the season and I would prefer to bank on those and the ones I draft late than any early in drafts.

Are you surprised that Vladimir Guerrero Jr. fell to you at the 85th overall pick?

Vlad Jr. dropping that far is crazy. I get it, he underwhelmed in his first taste of the show but he was the number one overall prospect for a reason; he can hit and he will this year. I probably should have taken him even earlier to be quite honest.


Mike Schwarzenbach

You took a very slugger-heavy approach by selecting Yordan Alvarez, Khris Davis, Joey Gallo, and Franmil Reyes. Are you concerned about your average and steals taking a hit?

In the most power-happy era in baseball history, I definitely wanted to prioritize players that could set the pace in power stats. Starting my team with Bregman and Story set up batting average nicely while adding more power to the sluggers drafted later. Steals, on the other hand, are definitely a concern for this squad. By the time I realized the hole I was in, it was too late to find a player capable of making a real difference in steals without dragging down every other category meaning I will certainly make steals a priority much earlier in future roto drafts this season.

Your Alex Bregman pick at #6 overall occurred before the Astros sign-stealing scandal completely unfolded and A.J. Hinch was fired. Would you reconsider that pick or do you feel it will have no effect on him?

Not at all, Bregman is one of the brightest young stars in the game and I don't believe you blast 41 homers with 122 runs and 112 RBI just by stealing signs. Furthermore, MLB's investigation noted Astros players abandoned the sign-stealing in 2018 as they believed it was losing effectiveness bringing into question if he was even cheating during last year's second-place MVP finish. We may never know for sure what occurred behind the scenes in Houston, but Bregman is a former top prospect with the batted ball data to back up his monster numbers from 2019. Bregman is still sixth in my rankings and I'll take him there in every draft if given the opportunity.


Nicklaus Gaut

You didn't take a single closer and your only two RP are setup men (Nick Anderson and Giovanny Gallegos). Is punting saves something you recommend?

While I don't totally recommend punting saves, I'm more comfortable drafting that way in a 10-person league, as there should be plenty of opportunities if I stay diligent on the waiver wire. With Gallegos and Anderson, I have two elite setup men who, if they had the closer's job currently, would see their draft stock skyrocket. Best-case scenario, Gallegos takes over as Cardinals closer with Carlos Martinez set to return to starting and Anderson collects around 10 saves as a key member of the Rays yearly closer-carousel. Worst-case, I only get a handful of saves but still get elite ratios and strikeouts, with the pair combining for 203 K in 139 innings last season, with a 2.78 ERA and 0.93 WHIP. The average winner in NFBC leagues last year drafted, on average, 1.5 closers; I think I'm over halfway there.

You chose Chris Paddack ahead of veterans like Madison Bumgarner, Trevor Bauer, and Yu Darvish. Do rumors of an innings cap or past injury worry you at all?

Even with a supposed limit on his innings, I was happy to get Paddack at #87, which was about a round after I had him valued. Especially because the pitchers that went in the next two rounds were a lot of guys I happen to be down on, like Bumgarner, Bauer, and Eduardo Rodriguez. I did consider Yu Darvish here - someone I'm really high on - but he comes packaged with even more risk than the average pitcher with his long and storied injury history. I'm seeing Paddack being projected for between 165-170 inning, which seems reasonable to me, though I do think 175 IP is on the table. Given the type of production I anticipate, I think Paddack will return more than a chunk of fantasy profit.


Pierre Camus

Nolan Arenado has already fallen out of the first round in many early drafts, including this one. How much should the ongoing feud between he and the Rockies, along with a potential trade, concern fantasy owners?

While he certainly doesn't seem happy, it's not as if we have to fear a holdout or a loss of playing time. If Arenado does stay in Colorado, that's actually the best-case scenario because he'll remain in the heart of the lineup for a strong offense in the best ballpark there is. A move to the Cardinals or Rangers still wouldn't put him below Anthony Rendon or Rafael Devers in my estimation, so at this point he could be a bargain if you can get him outside the top-15.

At starting pitcher, you took on a mix of injury risk (Luis Severino, Mike Foltynewicz, Mike Minor, Jameson Taillon) and inexperience (Tyler Glasnow, Griffin Canning, Sandy Alcantara, Josh James). What was your strategy?

Ultimately, every pitcher comes with risk. Even a "safe" player like Corey Kluber, who had thrown 200+ innings in five straight years, succumbed to serious injury last year, while a first-round pick like Chris Sale tanked many teams with uneven play before going on the shelf. I shoot for strikeouts early and then try to hedge the ratios later with guys like Taillon and Alcantara. We've seen guys like Folty and Glasnow look dominant in flashes, so if I can hit on one for a full season, it was worth it even if the other doesn't pan out.


Marc Hulet

What do you expect out of Shohei Ohtani this year and do you think he'll be worth a rotation spot in all fantasy leagues?

I felt pretty good about taking a little bit of a risk on Ohtani because I already had Cole and Syndergaard locked up. The Angels club is always going to do everything it can to win and, while it lacks pitching depth, Ohtani is the best pitcher on the staff so a healthy number of the club's wins those should end up under his name. He was likely only scratching the surface of his potential on the mound in 2018. I believe we have a pitcher here that will miss bats and generate a lot of strikeouts — but I do have some minor reservations about how well he (as a fly-ball pitcher) will fare with the home run totals if the juiced ball is still hanging around. I have a potential ace here.

You nabbed rookie starters Jesus Luzardo, Brendan McKay, and Nate Pearson. Which one do you believe represents the best draft value in redraft leagues?

Outside of MacKenzie Gore, Luzardo and Pearson probably have the highest ceilings of any pitching prospect in baseball and they’re almost MLB ready so I don’t expect a huge learning curve from them but I do have concerns about how many innings they’ll be allowed to throw in 2020 with Luzardo coming back from a serious shoulder injury and Pearson also having his innings suppressed in recent seasons due to (less concerning) injury. So that leaves me with McKay as the best pick for 2020 because we can probably hope for around 160 innings from a guy who is still in his infancy as a full-time pitcher but has shown he’s not far off from having three or four plus offerings with above-average control. He’s also on a team, the Rays, that should be pretty good in 2020. If I was confident Luzardo was going to throw more than 120 innings in the Majors then I’d switch my vote, though, because he just might have the better overall fantasy results.


Bill Dubiel

You stacked your rotation early, taking Jacob deGrom in the first round, followed by Aaron Nola, Luis Castillo, and Jose Berrios within the first six rounds. Was this a matter of getting value where it fell or are you making a point of loading up on elite pitching this year?

In my pre-season analysis, I found that there were quite a few bats I knew I could get later in the draft that I would be extremely comfortable with over the course of a season. I didn't feel as strongly about starting pitching, and therefore I decided to load up on high-end starters. I was able to snag four guys who have fairly reliable floors but still enough upside where I can gain an advantage throughout the season there. Likely expect some regression with Castillo, but still that's four guys who will eat innings, approach or surpass 200 K, and likely keep their ERA under 3.75.

Now that he's signed with Atlanta, does Marcell Ozuna at 91 feel like a bargain or are there concerns about how he might fit with a new team in a crowded outfield?

Marcell Ozuna at 91 feels like a pretty good bargain to me, as he's going to occupy a prime position in what will be, in my estimation, one of the National League's best offenses. He's been a healthy everyday mainstay in whatever lineup he's been in, tallying 549 at-bats or more in each of the last four years. The depth in Atlanta's outfield doesn't concern me, as Ozuna should be prioritized as the second-best option behind Acuna. It'll be Ender Inciarte and Nick Markakis who need to battle for at-bats throughout the season.

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Using Sabermetrics for Fantasy Baseball: Barrels

Last time, we looked at how exit velocity (or EV) is only one piece of the fantasy analysis puzzle. Baseball broadcasts will commonly cite Launch Angle (LA) to complement their EV figures, but it is given in terms of degrees. Am I evaluating a baseball player or trying to find the hypotenuse of an isosceles triangle? Let's simplify things a bit to see how these numbers can actually benefit our analysis.

LA is basically a fancy way of saying things that the fantasy community has used for years. They don't do a good job of publicizing it, but LA is actually fairly simple to understand. Here is the batted ball type produced by the various degree measurements:

Batted Ball Type Launch Angle
Ground ball Less than 10 degrees
Line drive 10-25 degrees
Fly ball 25-50 degrees
Pop-up More than 50 degrees


What is a Barrel?

Most batters want to live in the 10-50 degree range, as grounders rarely produce power while pop-ups rarely produce anything other than easy outs. Well-struck balls in this range of launch angles are the batted balls that fantasy owners are most interested in. A Statcast stat called "Barrels" filters out everything else, allowing us to evaluate who is hitting most of these high-value batted balls.

A Barrel is defined as "a ball with a combination of exit velocity and launch angle that averages at least a .500 batting average and 1.500 slugging percentage." It should be noted that the numbers above are only a minimum threshold. In this respect, the stat is like a Quality Start. It is possible to register a QS with an ERA of 4.50, but the actual average ERA of all MLB Quality Starts falls well below 4.50.

The range of EVs and LAs that combine to form Barrels is called the Barrel Zone. This means that higher EVs can compensate for less ideal LAs to produce the .500/1.500 minimum. Batted balls must have an EV of at least 98 mph and fall within the 10-50 degree LA range in order to be classified as Barrels. We care about fantasy production, not the intricacies of a mathematical relationship. You don't need to worry about the math.

With this in mind, Jorge Soler led baseball in Barrels last year with 70. He was followed by a three-way tie at 66 (Ronald Acuna Jr., Pete Alonso, Mike Trout) and Nelson Cruz (65). This group passes the sniff test, as it includes the HR leader in each league and the best player in the game. Likewise, Billy Hamilton managed zero Barrels all year, living up to his reputation of weak contact. Still, we already knew this. What do Barrels add to the equation?


The Value of Barrels

They become more instructive when you stop looking at them as a counting stat and start examining them as a rate stat. By taking the number of Barrels and dividing by the total number of Batted Ball Events (BBE), we get a percentage that tells us how frequently a player's batted balls are Barrels.

Joey Gallo topped this list in 2019 with a 26.4% Brls/BBE figure, followed by Miguel Sano (21.2%), Aaron Judge (20.25%), Nelson Cruz (19.9%), and Gary Sanchez (19.1%). Guys like Sano and Judge didn't have the raw BBEs to crack the Barrels leaderboard, but the rate stat suggests that they could be intriguing values this year.

This data helped identify sleepers in every year of its existence. Chris Carter had an 18.7% Brls/BBE in limited 2015 playing time. He led the NL in homers the next year with 41, so he was a sleeper worth owning based on the prior year's Brls/BBE. Gary Sanchez ranked eighth in the league with a 15.8% Brls/BBE in 2016, foreshadowing his ascension to the top of the catcher rankings after a strong 2017. Gallo's 22.1% rate of Brls/BBE over 253 batted balls in 2017 suggested that his 41 HR were real, and he effectively repeated them the next season (40 HR). Likewise, Luke Voit's third-place finish in Brls/BBE in 2018 foreshadowed his .263/.378/.464 line with 21 HR in 510 PAs for the Yankees last year.

Like BABIP, Brls/BBE also seems prone to random fluctuation. Giancarlo Stanton's amazing 2015 (he hit 27 bombs in 318 PAs) was fueled by a 32.5 percent Brls/BBE, over 10 points higher than the league's second-best performance that year (Miguel Sano's 22.4% rate in limited time). A rate that high was almost certainly an outlier. Sure enough, he regressed to a still strong 17.3% Brls/BBE in 2016, 17.4% rate in 2017, and 15.1% in 2018 before missing most of last year due to injury.



Viewing Barrels as a rate stat can be beneficial, but important considerations like strikeout rate still aren't captured by the metric. That said, few metrics have proven to have the predictive power that Brls/BBE has shown in recent years. There are a few misses (Tyler O'Neill led baseball in Brls/BBE in 2018 but did nothing useful last year), but in general it's a stat you want to look at. Here are some other stats you can look at to become a more effective fantasy owner.

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Using Sabermetrics for Fantasy Baseball: BABIP for Hitters

The most accessible of the fantasy-relevant advanced stats is BABIP, or Batting Average on Balls In Play. It simply measures a player's batting average on balls in play, with outcomes such as strikeouts and home runs removed from consideration. In general, the league average hovers around .300, a nice round number to remember.

Many know BABIP as an approximation of luck, with either a very high or very low number indicative of a major batting average regression in the future. That is partially correct--the stat can be used to predict batting average fluctuations. However, a player's skills may allow him to run a better than average BABIP, or doom him to a consistently below-average figure. One example of this is Christian Yelich.

Let's see how this metric can be used to evaluate one of the most impactful bats in the majors and how you as a fantasy owner should use it to your advantage when preparing for your upcoming drafts.


The Above-Average BABIP Formula

Yelich has been a batting average force for a while now, but the addition of elite power to his profile has made him a consensus top-3 pick heading into 2020. In 2019, Yelich hit an outstanding .329/.429/.671 with 44 HR and 30 SB in just 580 PAs. One of the reasons for his success was a .355 BABIP, so Yelich loses a lot of value if we regress that all the way to .300. Should we really do that?

Yelich's career BABIP is .358, clearly indicating a sustainable ability to beat the league average .300. Considering last year's BABIP of .355 was within three points of his career rate, a repeat is the safest projection. What skills does Yelich possess that allow him to crush the average player?

Yelich is an elite speedster--his 28.7 ft./sec Statcast Sprint Speed was nearly two full ticks above average last year. It makes sense that someone with Yelich's wheels could beat out more base hits than other players, while most catchers would lag in this regard. Therefore, an established player's baseline BABIP should not be the league average .300, but whatever that specific player's career BABIP is.

Looking at BABIP by batted ball type can also be a great tool. Yelich gets his speedster hits exclusively on grounders, as running really fast does nothing to prevent a fielder from catching a ball in the air. While the league averaged a .236 BABIP on grounders, Yelich posted a .292 mark on them last year. His career rate is only .276. Therefore, we can conclude that Yelich will continue to outperform the league average on ground balls because his .276 career BABIP is much higher than the league average. However, he is unlikely to do so to the same extent he did in 2019.

Comparing BABIPs for the other batted-ball types year over year is something of a mixed bag for Yelich. His fly balls found pay dirt much less frequently, posting a BABIP of .133 against a career mark of .201. However, his line drives fared considerably better (.744 BABIP last year) than they have in the past (.690 career). Overall, both figures should be expected to regress to the mean and roughly cancel each other out. When we factor in slight regression based on ground balls above, we should probably expect Yelich to fall just shy of last year's BABIP while still clearing .300 easily in 2020.


The Below-Average BABIP Formula

The same trend is possible in a negative way. For example, Anaheim's slugging DH, Albert Pujols, is well known for being an all-or-nothing batter that pulls the ball at every opportunity. This makes him susceptible to the shift, as the infield defense knows where the ball is likely to go and can set up accordingly. He also lacks the speed to beat out infield hits most other major leaguers can, finishing second to last in Statcast's Sprint Speed metric last year.

These factors figure to hurt his BABIP on grounders, and Pujols's .212 last year indicates that it did. This is not a new trend, as he hit .160 on grounders in 2018, .192 in 2017, .217 in 2016, and .179 in 2015. Clearly, projecting regression toward the league average would be wrong, as his pull tendencies and subpar speed allow the defense to consistently perform better than average against him. Pujols's overall BABIP was .238 last year, a number that should be expected moving forward due to his consistently poor production on ground balls.



To conclude, BABIP can be used to indirectly measure a player's batting average luck by comparing it not to the league average of .300 but to an established player's career number. Foot speed, batted ball authority, line drive rate, and defensive positioning all give players some ability to manipulate BABIP. Players with these skills may still overachieve, and this regression can be predicted by examining BABIP by batted ball type. Younger players without an established baseline are generally regressed to the league average, but these predictions are less reliable than those based on a player's personal history. Click on this link to learn more about how sabermetrics can give you an advantage as a fantasy baseball owner!

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Is Mike Trout Still the #1 Pick in Fantasy?

Pierre Camus and Nicklaus Gaut debate whether Angels outfielder Mike Trout should still be the consensus number one pick in 2020 fantasy baseball drafts or if Ronald Acuna Jr. or Christian Yelich should be taken higher.

Like and subscribe to the RotoBaller channel on Youtube to get all our latest podcasts and catch us on iTunes and BlogTalkRadio as well!

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I'm Still Number One! Wait, Am I?

Pierre and Nick decide whether Mike Trout is still #1 in ADP for upcoming fantasy baseball drafts based on declining steals.

Thanks for listening to today's episode! Be sure to tune in throughout the week, and to also follow RotoBaller on Twitter, YouTube and iTunes for the latest fantasy news and analysis. We are your secret weapon...

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Using Sabermetrics for Fantasy Baseball: Exit Velocity

If you've watched a baseball broadcast in the so-called Statcast Era, you have undoubtedly noticed the broadcasters commenting on a batted ball's exit velocity, or EV. Many have taken to using stats like Hard% and Soft% to forecast how a player should be performing, expecting larger Hard% rates to produce larger BABIP and HR/FB figures. There is a relationship there, but it is not as clear-cut as you might think.

The hardest batted ball of the 2019 season was struck by Giancarlo Stanton. It was clocked at 120.6 mph, but Stanton only recorded a single for his efforts. The hardest-hit home run was a three-way tie at 118.3 mph: Gary Sanchez, Peter Alonso, and Aristides Aquino. Aaron Judge's best EV of the season was clocked at 118.1 mph and made an out. While higher exit velocity figures support offensive performance, you need to use other tools as well to accurately assess a player's performance.

The best way to get a feel for how hard a given batter usually hits the ball is to look at his average exit velocity. The league average mark in 2019 was 88.1 mph, but that stat is of little value. The exit velocity on airborne balls (both flies and line drives but not including pop-ups) is all you need when evaluating a player's HR/FB rate, while ground ball exit velocity is the best indicator of a high BABIP on ground balls. The two metrics should almost never intersect, but a lot of analysts ignore context and use overall average exit velocity to evaluate both HR/FB and BABIP. You really shouldn't do that unless you believe that a grounder has a chance of going over the fence. Hard% is even worse, as it assumes that all batted balls of at least 95 mph are equal and makes no attempt to differentiate ground balls from airborne ones. So how do you figure out what's useful among these sabermetric measures? As always, the answer lies in placing these numbers in their proper context.


How can I use EV to predict BABIP on ground balls?

Major league batters averaged an EV of 84.8 mph on ground balls last season, and every mph above or below that figure is very important. For instance, hitters produced a batting average of just .150 on balls in the 80-82 mph bucket in 2019, while batted balls at 85 mph or above produced a .347 batting average.

As we've previously seen, players who can be shifted should be expected to struggle on grounders regardless of EV, while faster players can punch above their weight. Much like broader BABIP, it is a good idea to compare a player's current BABIP on ground balls to his career mark to account for these factors. As such, average exit velocity on grounders should be seen as one piece of a larger puzzle instead of the end of your BABIP analysis.


How can I use EV to predict HR/FB?

In 2019, the average airborne exit velocity in Major League Baseball was 92.7 mph. All other things being equal, a batter with an average airborne EV in the same area would be expected to be near the league-average HR/FB. Unfortunately, nobody of fantasy interest matched the exact MLB average last season.

If we increase the threshold to 92.8 mph, we get a bunch of fun names to work with: Gleyber Torres (21.5% HR/FB), Charlie Blackmon (17.7%), Jose Altuve (23.3%), and Jonathan Villar (16.7%). By exit velocity alone, all four of these guys are due for significant regression that could adversely affect their fantasy value. However, all four of these guys played in power-friendly ballparks last season, and three of them will do so again (sorry Villar). While you might want to expect some regression from Torres and Altuve, their parks will probably inflate their HR/FB to some degree moving forward.

Some of the other factors that can impact HR/FB include Pull% and Launch Angle, both of which will be discussed in greater detail later in this series. While airborne EV is an important power metric to look at, there are other variables that can prove more important. Ironically, airborne exit velocity's most important use may be to confirm whether a player besting his career BABIP on fly balls and/or line drives can continue to do so.



Hitting the ball hard is obviously a good thing, but limiting your fantasy analysis to just exit velocity is asking for trouble. Variables such as strong pull tendencies and foot speed can trump raw EV in a player's BABIP on ground balls, while home park, Launch Angle, and Pull% can all support elevated HR/FB figures even if the EV doesn't. Oh, and for the love of the fantasy baseball gods, please don't use Hard% for anything.

If you'd like to learn how to interpret more statistics for a fantasy advantage, please click on this link and check out our other articles on the topic.

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