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Using Sabermetrics For Fantasy Baseball Part 9 - 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 Andrelton Simmons and his 21 Defensive Runs Saved (DRS) figures to provide better defense to its pitchers than a team that lacks a platinum glover. DRS is a counting stat like HR or RBI that measures how strong a defender a particular player is, with zero corresponding to an average defender and negative numbers possible for weak gloves. A better defense helps pitchers outperform their FIP.

Statcast makes it even easier to look at the quality of a pitcher's outfield defense. Outs Above Average, or OAA, measures each outfielder's defensive contributions using Catch Probability. If a batted ball is caught by an outfielder, the outfielder 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).

Outfielders also lose points equal to the batted ball's Catch Probability if they flub the catch. Missing the ball in the example above would, therefore, subtract 0.4 from the player's OAA. Lorenzo Cain of the Milwaukee Brewers led baseball with 22 OAA last season, helping Milwaukee to the best defensive outfield in baseball (30 total OAA).

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 .117 in 2018.) 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 Cain, while a ground ball specialist would benefit more from an elite infielder like Simmons instead.

While defense is largely out of a pitcher's control, some pitchers can control their BABIP to a degree. For example, Caleb Smith's .276 BABIP allowed last season might look like a fluke at first glance, but his batted ball profile supports a low BABIP. He has a strong fly ball tendency (50.8% FB%), so most batted balls against him figure to have a lower BABIP. He also produced a league-leading 18% IFFB% last season (min. 70 IP). Pop-ups are almost never hits, so inducing them consistently enables a pitcher to post better than average BABIPs.

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.

Finally, a pitcher's own defense may allow him to control the BABIP he allows. For example, Masahiro Tanaka limited the BABIP against him to .284 in 2018. One reason why is the incredible seven DRS he compiled in his 156 defensive innings. Simmons had 1,254 2/3 innings to post his DRS last year, so extrapolating Tanaka's performance to Simmons's workload yields roughly 56 DRS!

Extrapolations like that aren't necessarily valid, so Tanaka is probably not the defensive equal of two-and-a-half Andrelton Simmonses. Still, it seems insane to completely discount Tanaka's defense with the track record he has put together (25 career DRS in 824 1/3 innings).

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 2018, the league average LOB% was 72.8%, 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 necessarily, 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. Ballparks can have a substantial impact on a pitcher's ERA as well.

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Using Sabermetrics For Fantasy Baseball Part 8 - 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 that the metric is based upon, pitchers control only Ks, BBs (and HBP) and home runs allowed. Therefore, Ks, walks and dingers are the only inputs to determine the number.

Calculating FIP requires way more math than most fantasy owners are comfortable with, so don't worry about the formula. 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 (4.15 in 2018).

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 to Draft and Manage Your Team

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, Carlos Martinez began the 2018 season with a 1.43 ERA in the month of April and followed it up with a 2.19 mark in May. Many had speculated that Martinez was on the verge of a breakout before the season started, and his early results seemed to confirm it. Unfortunately, his underlying metrics (3.37 FIP/4.12 xFIP in April, 3.49 FIP and 5.23 xFIP in May) didn't support it. Martinez endured an awful June (6.75 ERA, 4.93 FIP, 5.67 xFIP) before dealing with injury issues and finishing the campaign in the bullpen. He finished with a 3.11 ERA for the season.

There are certain types of pitchers that may consistently defy FIP. The first is knuckleball guys, who have challenged DIPS theory since its introduction. Steven Wright was the only big league pitcher to throw a knuckleball in 2018, and his 2.68 ERA was substantially better than his 4.37 FIP or 4.67 xFIP over 52 2/3 IP. Significant regression should not be expected however, as he has a career ERA of 3.77 despite a FIP of 4.36 and xFIP of 4.67 over 341 1/3 IP. For Wright and other knuckleballers, there is no need to bother with FIP.

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 last season 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. 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?

Personally, I'm leery of anyone's ability to consistently defy FIP, knuckleballers notwithstanding. Matt Cain's story is very similar to Cueto's, and we know that it did not have a happy ending. There is an ongoing debate in the sabermetric community though, so my word is not gospel on the subject.



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. Of course, we can also predict how some of the "luck" that separates ERA from FIP will play out. BABIP for pitchers will be discussed in Part 9.

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RotoBaller's Industry Experts Mock Draft - The King's Perspective

At RotoBaller, we recently assembled a group of fantasy baseball experts to take part in the RotoBaller Friends and Family Expert Mock Draft.

Our participants came from all over the industry, representing a host of various sites such as:

Here is my take on how things went. Check out the full draft board at RealTime Fantasy Sports:


Expert Mock Recap

As a new RotoBaller, I was very excited to jump into my first mock draft as a member of the team. It was a 12-team 5x5 Roto style against some formidable industry names.

First of all, there was Nando Di Fino of the Athletic. Not only is he maybe the nicest guy on the planet, but he is the master of identifying the deep sleeper. I think he scouts kids on little league fields on the weekends. Then you have Ray Flowers, who I believe invented sabermetrics. Todd Zola is known as “The Lord” in fantasy baseball inner circles. Tim Heaney smiles a lot and is really friendly, then slits your throat at the draft table. Howard Bender sounds like Henry Hill of GoodFellas when you listen to him on SiriusXM Fantasy Sports Radio. Take one of his guys and I might get whacked. Plus, there were my new RotoBaller teammates. Great, Real Talk Raph can make fun of my picks in front of a national radio audience now...

But I was ready and confident. Like Jacob deGrom does so well, as I have often observed while I have covered him throughout his career, I shut out the distractions and focus on doing what I always do. I always tell readers I let the draft “come to me.” I am always poised, going with the flow and not getting emotional. I treat a mock just as I would a real draft. It’s the way I have always operated and I owe it to the RotoBaller community to invest the picks the same as I would if I was playing for a lot of money. If we were competing for a lot of cash, though, I would not want to be up against Vlad Sedler.

Strategically, I just wanted to take the best offensive player available at No. 9 overall and then focus mainly on building out the core of my offensive group in the first few rounds. I did want to sprinkle in some top-level starting pitchers, but closers could wait, as I have often been successful in acquiring them later on or during the season. Grabbing speed at key spots throughout the draft would also be a primary focus.


The Breakdown

You can see the full board right here. I do not have Jose Altuve in my first nine and he went three spots ahead of me. I was hoping Christian Yelich would slip to me at nine. I know much has been made of his elevated BABIP and HR/FB rate last year, but he is one of the best pure hitters in the game and he never seemed to be content in Miami. Yelich was always seemingly “bearing it” in his Marlins days from my past observations on the MLB beat, and he almost seemed happy-go-lucky in comparison in Milwaukee. Even with an expected dip in production, the across-the-board totals are still worthy of a top-10 pick.

But Nando took Yelich one spot ahead of me, and may send me a note when he reads this, he is that kinda guy. So I went with Ronald Acuna Jr., who produced amazing numbers in just 433 at-bats in 2018. It will be his first season in the majors this year, so opponents will find some holes in his game. But Acuna will adjust back and I am definitely expecting 30/25 production with some impressive RBI totals.

Once Chris Sale went off the board at the beginning of the second round, the “Big Three” of Max Scherzer, deGrom and Sale were gone, and I needed simply to take the best starter available when it was my turn in round two. Thankfully, that was Corey Kluber. So I had my anchor hitter and pitcher and knew it would be a long wait until my next pick. I was very happy to land Andrew Benintendi for a safe 20-20 floor, and he is still improving. I love the combination of peace of mind and some possible upside he gave me at that point in the draft.

I was considering a starting pitcher in the next round with very strong consideration for Noah Syndergaard to pair with Kluber. I get the sense from him that Syndergaard believes he has not delivered his best seasons yet, and he wants to prove that. But I just could not pass on Anthony Rizzo in the fourth round. His current ADP is 34.49.

Once I had three prime hitters, I knew I had to bulk up on starters, and Zack Greinke was an ultra-safe pick to me in the fifth. Mike Clevinger was my sixth rounder and I really believe in him. Once he cut down on the walks and adjusted his arsenal last year I was very impressed, and I almost see Clevinger as a luxury as my SP3.

I may have been a little earlier than some on Miguel Andujar in the seventh. His batting average may fall a bit this year, but he has a natural and dangerous swing that should keep his counting numbers in line with last season. I picked Mallex Smith before his recent injury, but I don’t see him missing much regular season time; if you can get him beyond the eighth round right now, go for it. I believe Smith really matured as a player last season, and now he may have found a real home in Seattle. The ardent fans in the Pacific Northwest may take to him as a fan favorite when he displays his all-out style.

I always want one standout closer or the best I can get in the ninth or 10th round, then a middle round guy and some late fliers. I grabbed Aroldis Chapman to lead my relief crew in the ninth, but then stayed away from the bullpen until the 17th, when I selected Arodys Vizcaino. Will Smith was a late pick, and Wily Peralta was my final pick overall, but I really feel good about Hunter Strickland to re-emerge with my Round 24 selection. With three late choices at closer, one or two are bound to get the job done.

I was nearly stunned to get Nicholas Castellanos in Round 12, when you consider he has an ADP of 80.24 and is a top-20 fantasy outfielder. I was not comfortable with my Cesar Hernandez pick in Round 16, as maybe I got too antsy for some more speed at that point. Kyle Freeland as my fourth starting pitcher in Round 11 made me shake my head in awe. A quality pitcher from Colorado? I still cannot believe it.

Joey Wendle was one of my favorite late-round picks for some speed and maybe even a little pop. And also proved I should have waited on Hernandez. I threw the Avisail Garcia dart in Round 26. If he can stay healthy I can get decent production from him. He’s been noted to me in the past as a guy who does not take the best mental approach to the game. But the MLB insider who tipped me off to that did note Garcia’s natural skills can still lead to quality production. If Garcia stays healthy he might provide respectable output in Tampa Bay.

Overall, I felt I adjusted well to the flow of the draft and gave RotoBaller readers a solid map of my outlooks and valuations so far. But there is a lot more mocking and rolling to be done, so I will be reporting back from the draft rooms in the near future.


Scott Engel has joined RotoBaller as a featured contributor as he builds on 20-plus years in the fantasy sports industry. “The King” is an inaugural member of the Fantasy Sports Writers Association’s (FSWA) Hall of Fame.

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Using Sabermetrics For Fantasy Baseball Part 7 - Lineup Spot

To this point, this series has focused exclusively on trying to predict and validate home runs and batting average. There is a reason for this--modern sabermetrics tend to 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 stat heads, 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.


Lineup Slot & Counting Stats

In the table below, each batting order slot's PA, RBI and Runs are presented from the 2018 season. The final number is simply R + RBI, an approximate measure of that slot's overall value to a fantasy team.

1st 22,631 2,056 3,187 5,243
2nd 22,132 2,334 2,907 5,241
3rd 21,614 2,848 2,708 5,556
4th 21,129 2,977 2,574 5,551
5th 20,642 2,502 2,390 4,892
6th 20,107 2,329 2,197 4,526
7th 19,534 2,036 2,079 4,115
8th 18,964 1,968 1,881 3,849
9th 18,386 1,556 1,707 3,263

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 280 runs separate the first and second spots while only 118 separate sixth and seventh. 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 1-2-3-4, the only lineup slots to exceed 5,000 combined R+RBI. The 5th slot is solid with 4,892 R+RBI, but the others clearly lag behind. This means that a player in the middle of a weaker offense may 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.

The only counting stat left is stolen bases. A player's success rate must generally hover between 65 and 75 percent to keep the green light, as otherwise he is costing his team runs. Players that consistently fail to reach this benchmark, such as Roughned Odor of the Texas Rangers, are poor bets to steal a lot even if they've swiped 20 in the past. This is particularly true of contending teams, as weaker clubs may run with reckless abandon just to see what happens.

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. This concludes the offensive portion of learning to use sabermetrics for fantasy purposes. Next time, we'll move to the mound and try to understand what the heck FIP is, and why it sometimes has an x in front of it.

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What I Learned in My First Slow Mock Expert Draft

Over the years, I’ve done hundreds of mock drafts, maybe even thousands. However, as someone relatively new to formal writing about fantasy baseball, I’ve never been part of an organization that ran a slow mock draft.

I recently took part in RotoBaller’s Dynasty Mock Draft, and boy was it ever SLOW. We started this thing back in early December and we’re just finishing it now. Holiday vacation plans impacted that, plus the fact it went a full 26 rounds and the list extended to every prospect available.

However, the draft allowed time to think and reflect, and it changed how I felt about some of my picks and players. Not only did the time involved make me realize how valuable it was as a learning experience, but it also forced me to recognize certain things about my knowledge and readiness. Plus, in the middle of winter, when there was no baseball in sight, it was just plain fun.


A Slow Draft Provides a Different Type of Preparation

Most mock drafts move so quickly that you’re usually focused on prepping for your next pick. There’s little time to evaluate your own picks and those of others. Most mock drafts make for fine practice, but they don’t tend to increase your player knowledge or critical insight into the draft. For me, a regular mock draft gives me a sense of the draft landscape and of my decision tree in drafts. The slow draft offered something else.

Case in point, in the 25th round of our mock, I still needed another relief pitcher, and I wanted to pick up a prospect. I felt like I needed to take an RP, but as I looked at the board, I saw that Luis Robert was still available, probably wouldn’t be around by my next pick, and taking an RP immediately or waiting wasn’t likely to change the quality of the pitcher I got. In a regular mock, I would probably have made that pick, stuck by the decision to prioritize my immediate need by drafting a relief pitcher and never looked back. The slow mock gave me a bit of insight into my own thought process.


A Slow Draft Gives You Time To Learn

Apparently, I don’t always know ADPs (and my own rankings) as well as I think I do, OR maybe the issue is that my judgments in a traditional draft are relative sh*t. With each round, I had a list of players I was planning to take with my pick. However, in the slow mock, I would sit and do another round of research about the players on my shortlist, or I would go back to doublecheck a player I had originally written off as someone not worth selecting.

Before I took Michael Conforto with the 51st pick, I had dismissed him as older than ideal and too much of a health risk for my fifth rounder, but when I realized he was only 25 (I had thought he was 27) and that he had demonstrated solid health in both 2015 and 2016 before his injury in 2017, I felt much better about selecting him. Having gone through the process, I think he was a steal in the fifth round, and it’s turned around my attitude towards him.


Your Opponents Will Teach You Which Players You’ve Undervalued

JB Branson, whom I thought had the best draft in the group, took Jack Flaherty two picks after I selected Patrick Corbin. JB’s pick made me realize that I needed to revise my pitcher rankings immediately.

In dynasty, I’d much rather have Flaherty than Corbin, even though I think Corbin is a strong SP1. Despite that, if you’d asked me outright before that moment, I’d have said that Corbin, whom I value more highly than most folks, was the more valuable pitcher.

Brady Grove taught me a similar lesson about Kyle Schwarber. In a traditional draft, when a guy takes a player like Schwarber before I would, I pat myself on the back and congratulate myself for being smarter than him. Humble, I know. In the slow draft, I had time to go and look at these players: I took time to figure out why my competitors thought they were worth more than I did. The time and prompt for research made me shift my valuations.


Completing a Slow Draft with Knowledgeable Competitors is Invaluable

It’s a general truism that you can’t win a league in the first few rounds, but you can lose it. By contrast, the end of a draft has the highest potential for providing a positive return, but in most mock drafts you never get to practice this section. Usually, if you start a 12-man mock draft with a random group in a Yahoo or ESPN lobby, half the guys will be gone by the sixth round. Two or three will drop out before the end of the second round. If you’re really committed to the mock draft, you’re basically drafting against the AI by the end. Unfortunately, when the real draft rolls around, you’ve had no proper practice with this section of the player pool, and you’re usually just throwing darts because all your great “sleepers” have been claimed by round 20.

With the slow mock draft, we completed all 26 rounds, and it prompted me to think more about the players going after pick 200, let alone those going after 72. I’m not saying that Diego Castillo or Sonny Gray or Max Kepler is going to be a league winner, but there’s an argument that each one of those guys could be a useful piece this season. I only realized how that could come to pass by looking at those picks more carefully as we made our picks through the final rounds.


An Open Invitation

Given my experience, I want to extend an invitation to do a slow draft to anyone who is interested. Why should the fantasy “elite” get this chance but not others? I don’t know if people will be interested in doing this or not, but just send me a DM @D_Emerick on Twitter. My plan is simply to run it the same way that RotoBaller ran ours: Use Google Sheets to keep a simple draft board. Utilize Twitter DM chat to keep people notified it’s their turn. Then sit back and let the strategizing begin.

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How to Approach Rookies in Re-Draft for Success

With the NFL season officially a thing of the past, we can now turn our undivided fantasy attention to preparing for our baseball drafts. We are still waiting on the answers to a few key questions (such as, I don't know, where Bryce Harper and Manny Machado might play their home games?), but we have enough information at hand to formulate the bulk of our draft strategies for 2019.

We know to target multi-category stars in the first few rounds. We know which positions are deep enough to wait on, and which ones we should try to lock down early. We know how volatile bullpens can be, especially in this day and age, and that spending high picks on closers doesn't always pan out.

But what about the players we have only seen sparingly on a Major League diamond, or not at all? Rookies can be tricky for a multitude of reasons in re-draft leagues, but fear not. I've devised a road map for how to go about acquiring and deploying them on your rosters, starting with how they fit into your draft plan and ending (hopefully) with a league championship.


Know Your Prospects

The first thing you'll want to do is take some time to familiarize yourself with the top prospects in baseball. There are endless resources available on the world-wide web, including a great deal of prospect research right here at RotoBaller. A fine place to start is with our Top 100 prospect list.

Take note of one thing in particular regarding any MLB prospect: his estimated arrival date at the big league level. If a player is expected to make his MLB debut in 2019, follow him closely throughout spring training to see if he is trending toward an early-season (or even Opening Day) roster spot. Players who put forth an impressive effort in spring ball are the ones you want to consider on draft day. If a highly-regarded prospect struggles during the spring, however, he may be sent back down to Triple-A to work on his game before being called up during the summer. In this case, you may want to hold off until the very last rounds of your draft before spending a pick on a player in the minors.

Or, you can simply file away a few names to follow early in the season and track their progress at the minor league level. If at any point a promotion appears imminent for a given player, don't hesitate to pick him up a couple days early. It pays to keep an eye on these developments in order to give yourself an advantage over the other owners in your fantasy league.


Know the Organization

Another crucial aspect of dealing with rookies, particularly in re-draft leagues, is understanding the team they're eventually going to suit up for in the Majors.

It is entirely plausible that a prospect's primary position is already occupied by a quality player at the big league level. As a result, he may see time at a different position, or shuffle around the diamond altogether at the behest of the manager. Case in point: Nick Senzel of the Cincinnati Reds.

Senzel is a third baseman by trade, but Eugenio Suarez is already firmly entrenched at the position in Cincinnati. An outfield experiment seems logical then, but keep in mind that the Reds added Yasiel Puig and Matt Kemp to an outfield already inhabited by Jesse Winker and Scott Schebler. Despite being a top-10 prospect believed to be prepared for the highest level, there is no ready-made path to consistent playing time for Senzel. Until we get a clearer picture of how the Reds plan to utilize him, his fantasy value takes a hit in re-draft leagues.

This is, of course, just one example, but the point remains: whether you're at your draft or browsing the in-season waiver wire, take into account the potential role a rookie will have on his respective team once called up before you acquire him.


Beware of Starting Pitchers

In 2018, 13 rookies recorded 100 or more innings pitched. Of those 13, six recorded 120 or more strikeouts. Of those six, three recorded an ERA below 4.00. Among starting pitchers league-wide, 120 strikeouts would have been good for the 86th-highest total, and a 4.00 ERA would have tied for 128th.

Using the same thresholds, in 2017 there were 12 rookie pitchers who accumulated 100 or more innings, four of whom recorded 120 or more strikeouts. Only one finished with an ERA below 4.00. A 120-strikeout season in 2017 would have tied for 85th, and a 4.00 ERA would have fallen in 86th.

The point here is that while it's become somewhat common to see rookie position players work their way into the upper echelons of production, rookie pitchers tend to have considerably more ups and downs. As such, you're going to deal with some turbulence if you choose to roster any.

Additionally, here's something to keep in mind if you play in a head-to-head league: everyday players give you the opportunity for fantasy production several days a week and thus can atone for a bad performance here and there. Starting pitchers, on the other hand, give you two outings a week at most. One or two disastrous starts from a couple of rookies could mean the difference between winning or losing your weekly matchup.

Now, fantasy baseball leagues come in all different shapes and sizes, and maybe you play in a deep league or have a few extra bench spots. In this case, feel free to stash a rookie pitcher or two and hope for a return on your investment. In most 10 or 12-team leagues with standard roster sizes, however, it's best to tread carefully with rookie starting pitchers, as opposed to selling out in the hope you'll strike gold with the next Walker Buehler.


Maintain Patience

This is easier said than done thanks to guys like Mike Trout, but it pays to remember a simple fact when dealing with rookies in fantasy baseball: not every prospect is immediately going to blossom into the second coming of Willie Mays, and that's okay.

Consider this: in Ronald Acuna's first full month of playing time (May) in 2018, he hit .235 and struck out more times than he reached base. Then he got hurt, missed most of June, and put up half-decent numbers across 22 games in July. It wasn't until August that he truly broke out with a .336/.405/.698 slash line that included 11 home runs, 21 RBI and 25 runs scored.

If you're the owner who spent a draft pick on a highly-touted prospect like Acuna, don't give up on account of a rough first month or two. Baseball season is a long and winding road, and even if a young player isn't helping you early on, he can still play a vital role in your quest for a title down the stretch.

Conversely, if you notice a development like this elsewhere in your league, don't be afraid to exploit it. If an impatient league mate is growing frustrated with the performance (or lack thereof) of a rookie, try to acquire the player in a buy-low deal. Acuna's 19 post-All Star break home runs in 2018 (good for fourth in the entire league) would have been well worth sending away a couple mid-tier veterans early in the season.


Finding Hidden Gems

So we've established that it pays to monitor the progress of highly-regarded prospects in spring training and early in the regular season. We've also discussed exercising patience with these youngsters once we acquire them, whether it be through the draft, free agency or a trade. This is all well and good for high-profile players, but what about the ones flying under the radar? Not every prospect is going to arrive at The Show on a hype train.

While the baseball community swooned over Acuna, Juan Soto and Gleyber Torres in 2018, there were plenty of other rookie position players who made an impact at various points throughout the season.

Willy Adames of the Rays posted the highest batting average among shortstops with 200 plate appearances after the All-Star break. Daniel Palka of the White Sox tied Miguel Andujar for the rookie lead in home runs despite recording 156 fewer at-bats. Miami's Brian Anderson crossed the plate 87 times, good for 18th among all outfielders league-wide. If you're not paying attention, you're going to miss the boat on guys like these.

And so my last bit of advice is simple: don't get complacent. Everyone in your league is going to be looking for the next Acuna, the next Soto, the next Torres. Maybe you'll beat your league mates to the punch on guys like those, and you'll be well off because of it. But if you want to separate yourself from your adversaries, you have to be the owner in your league who knows to look for the next Adames, Palka or Anderson as well.

By now, I hope you feel well-prepared for this aspect of your fantasy baseball season and confident that you're going to make the right calls when the time comes. Just remember to put in the preparation, have some faith in yourself, and be sure to check back here at RotoBaller as draft season gets into full swing for updates on prospects around the league.

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Using Sabermetrics For Fantasy Baseball Part 6 - Pull Percentage

Earlier in this series, we saw 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 3.8%. Flies to dead center fared slightly better (8.1% HR/FB), but pulled fly balls were clearly the most productive (34.6% HR/FB).

Let's take a closer look at how Pull% can help you win your fantasy leagues in 2019!


How to Interpret Pull%

In 2018, roughly 64% of all home runs were to the batter's pull side. Only 12% of homers went to the opposite field, with the remaining 24% going out to center. This distribution is fairly consistent year-to-year, so it's safe to count on 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.

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 last only as long as the player wants it to.

It is also possible for a player to improve his HR/FB without an uptick in fly ball Pull%. Last season, Bogaerts clubbed a career-best 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% last season. We can't use Pull% to validate Bogaerts's 2018 power spike, so we would need to look to other metrics to legitimize it.

You should also avoid looking at raw Pull%. Of all pulled baseballs in 2018, 58.7% 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 20.6% 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 40.2% was marginally lower than the league average 40.3%, and he pulled 56.4% of his grounders compared to 23.9% 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 56.4% of their ground balls, allowing Trout to hit a solid .304 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. Trout is among the most well-rounded players in the game today, but he still pulled 21 of his 39 long balls last season. 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. The next part of this series will look at lineup slot as a predictor of counting stats such as RBI and runs scored.

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Using Sabermetrics For Fantasy Baseball Part 5 - 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 2018, the league average K% was 22.3%, meaning that roughly one in five MLB PAs ended in a whiff. Players that K significantly less than this have an advantage in hitting for a higher average. Players that whiff more often tend to post lower averages. This is relatively common knowledge for most fantasy owners.

Let's learn how analyzing stats related to plate discipline can help improve the performance of your fantasy baseball team entering the 2019 season.


How to Interpret Plate Discipline

Sabermetrics may be used to determine whether a given player "deserved" his K% over a particular period, avoiding misleading data the same way BABIP is used to see through a fluky average. The first number to check is SwStr%, alternatively called whiff rate. This metric simply tracks what percentage of a batter's swings fail to make contact with a pitch. The league average was 10.7% in 2018, with higher numbers indicating a proneness to K.

SwStr% tends to increase if a batter swings harder, making power hitters more susceptible to the strikeout than other players. 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.

Further detail is offered by O-Swing%, a measure of how often a batter swings at a pitch outside of the strike zone. Generally, swinging at pitches outside of the zone is a bad idea. 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 2018, the league averaged an O-Swing% of 30.9%. 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

Let's look at some examples of advanced plate discipline stats in action. Joey Votto is widely regarded as the master of plate discipline, and his surface stats support the assessment. His 17.3% BB% was actually greater than his 16.2% K% last year, after all. Digging deeper, we find that these numbers are completely justifiable. His 16.4% O-Swing% was nearly 15 percentage points better than the league average rate, and his 6% SwStr% was roughly half the average as well. It is safe to conclude that Votto will continue to demonstrate outstanding plate discipline in 2019.

Kansas City's Adalberto Mondesi does not measure up as well. He hit a reasonable .276 last season in spite of striking out at a 26.5% clip. He never walked (3.8% BB%) and chased too many pitches outside of the strike zone (37.1%). Worst of all, he whiffed at 18.2% of the pitches he swung at, one of the worst marks among fantasy-relevant players. Owners are drafting Mondesi as a "safe" category stuffer, 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 the analysis slightly. For example, Mondesi was extremely aggressive last year with a Swing% of 54.9%. The league average was 46.6% in 2018. Even if a hitter has a high whiff 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 (39.7% Swing%) leads to more Ks than his 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 if an older player sees a decline in Z-Contact%, indicating that he can no longer make contact on pitches he used to hit in the zone. Another is a change in SwStr% rooted exclusively in pitches outside of the zone. Sometimes, missing those pitches is 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%.

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Is Punting Steals a Viable Draft Strategy in 2019?

For readers who tune in to watch MLB games regularly, the phrase “small ball is dead” is becoming more and more the cliche. Managers do not feel the need to run as much, there is a decreasing rate of sacrifice bunts, and above all, no more hit-and-run as a primary offensive tactic. While many factors have led to this shift in baseball strategy, at the end of the day, there are plenty of other factors that have changed the game. Overall, there are more runs, more power, and more well-rounded players. While philosophical conversations about baseball are fun, what matters for fantasy owners is how this changes the fabric of personal drafts strategies.

In this light, this article takes on the question of “should you punt steals?” By “punt” we mean, avoid drafting, and instead prioritize other categories, at the expense of steals. This is mostly for roto leagues but steals count for points as well, so some applicability for all owners. 

With that said, read along with the Rotoballer team as we help you prepare for drafts entering the 2019 season. Read other articles to review different strategies to help you win your leagues, and gain that edge by getting in on strategy, new and old.


The Relative Value of the Steal

In 2018, 139 batters qualified for the batting title, meaning that they averaged 3.1 PAs per game their team played. While this artificially limits out some players, it also provides a stable baseline for players who were on the field for the entire year. Players who missed weeks due to injury, or are not playing every day, did not break this threshold and require more nuanced player evaluations to gauge value. While some of those names will appear later in this piece, for the time being, the core of the data set comes from this group of players.

Of the 139 players listed, the average hitter batted .265, hit 20 homers, drove in 73 runs, scored 77 runs, and stole nine bases. To put a finer bow on it, only 24 players qualified for the batting title and stole over 20 bases in 2018. Compare this to 40 players with more than 25 homers, and 50 batters with more than 80 RBI. This means that steals are coming from fewer sources, or are coming from players that are not playing enough to qualify for the batting title.

Only 47 qualified hitters stole 11 or more bases, and even more surprisingly, 13 qualified hitters stole zero bases. For comparison, in 2014, 146 players qualified for the batting title, and the average was ten steals over the campaign. That same year, homers were down to 15, runs to 70, and RBIs to 67. Only 21 stole over 20 bases, and 17 stole zero bags.

So then, based on these two samples, steals are down a fraction, but overall production is up. This makes sense as if fewer managers are running, those who play on teams that do run will see their numbers jump in comparison. Also, with younger players, there is just more speed, so the outfielder who might steal is now 23 and should run a bit more than his veteran teammate.


Draft Stock of the Rabbit

The infamous “rabbit” still dominates fantasy projections, meaning that steals still are on the minds of fantasy analysts. To forward a formal definition of the “rabbit,” by this we mean: “a player who does nothing but steal bases and might hurt other statistical areas.” Billy Hamilton always springs to mind, but others have been added to that list. For this sample, the set was expanded to non-qualifying batters, but players who stole more than 20 bases. While this is admittingly an arbitrary cut-off point, Adam Engel’s 16 steals did not seem to qualify him for the category, even with regular playing time, and a below average batting line.

Based on this, 10 players fit the profile of primarily being a steals threat, but perhaps, a liability elsewhere in scoring categories. They were: Jonathan Villar, Billy Hamilton, Dee Gordon, Ender Inciarte, Tim Anderson, Amed Rosario, Ian Desmond, Adalberto Mondesi, Michael Taylor, and Delino DeShields. This set offered, on average, 27 steals with a .248 batting average. The surprising piece was that players like Ian Desmond also fit into the grouping with his steals output, and a declining batting average, but would not be considered a speedster. And, owners are not drafting Desmond for his speed, but he still makes the list, showing the state of the position.

Readers might be questioning this definition of the rabbit, as often these are players with crazy steals lines, making them worth the lack of batting average. This is where things get a bit interesting for comparisons. Seven players stole 33 bases or above in 2018, with the order as follows: Whit Merrifield, Trea Turner, Mallex Smith, Jonathan Villar, Jose Ramirez, Billy Hamilton, and Starling Marte. Ramirez is an elite fantasy option without the steals, and Merrifield is emerging as one of the most well-rounded fantasy assets as well. Smith might be a rabbit but also hit close to .300 with 65 runs. Turner hit 19 homers and scored 103 runs. This list demonstrates that the steal-heavy player does not appear without other assets or fantasy options. Even Hamilton dropped down the list with only 34 steals, making his .236 batting line even worse in comparison.

Going back to the gang of 10 from the top of this section, those players, or the modern-day rabbit, have a current ADP of 177, with only Mondesi going in the top 100. Taking him out, the ADP falls to 193. Hamilton, on his own, is being drafted at 176. In 2017 he was averaging 59, and his fellow rabbit, Dee Gordon, was going at 31. Gordon this year has slotted in at 112. This means that steals are theoretically cheaper this upcoming draft season, or there are fewer reaches needed to add a stop steals threat.

So then returning to the central question of this piece, it is hard to prioritize steals, or punt them for that sense, when the “rabbit” might not be a viable draftable category anymore. Even for owners who want to add Hamilton, they do not need to take him before the mid-teens in standard drafts, and at that point, he is just an OF3, so not a real extra value. At the same time, punting steals makes no sense when there is no incentive to reach for steals. Punting in this world would be drafting power hitters for the sake of ignoring steals, but even those players have value. Edwin Encarnacion, for example, is only projected for two steals in 2019, but the 30 homers ease that. And, his replacement in Cleveland, Jake Bauers, is projected for a 20/20 season, adding a new way to add speed in drafts, without losing power.


Running a Mock

To investigate the relative value of the steal based on draft slot this next section will run a mock draft, taking the ADP as they currently stand. This would be a team that took the players, regardless of position, where they are presently being drafted. This exercise assumed a 12-team league, mixed leagues eligibility, and standard roto scoring. Our draft will slot this team at the sixth pick for a solid, average squad. Also included are the estimate steals according to Steamer.

1.6 J.D. Martinez (OF, BOS) - 4
2.19 Trevor Story (SS, COL) - 19
3.30 Juan Soto (OF, WAS) - 7
4.43 Rhys Hoskins (OF, PHI) - 6
5.54 James Paxton (SP, NYY) - N/A
6.67 David Dahl (OF, COL) - 12
7.78 Jose Berrios (SP, MIN) - N/A
8.91 Brad Hand (RP, CLE) - N/A
9.102 Jonathan Villar (2B, BAL) - 30
10.115 Luis Castillo (SP, CIN) - N/A

Admittingly, some of these players are slotted into their current ADPs based on the value of speed that they bring, but still, this exercise offers a valuable idea on whether owners need to reach for speed, or can look to current ranking. With that, of the six batters, drafted, the average for steals was 13 per player, with a total of 78 total steals. This means that not moving from the current draft ranking, this team would be above average concerning speed, compared to qualified batters from 2018.

And yet, looking to these players, only Villar is a potential “rabbit,” with other like Story and Dahl being appealing without speed and more for power and runs. Also, this pitching staff is strong, and prioritizing speed might have hurt that push. Villar is perhaps the best option for owners targeting speed, but again, is projected to chip in 15 homers and 70 runs to compliment 35 steals. And, even in drafts where the ADP is up based on players potentially targeting speed, this mock team got him in the ninth round.



Punting steals is not a valuable strategy on its own, as there are plenty of options that can help boost steals category scoring without selling out for those options. When there are fewer steals in general, but more players are adding double-digit steals, adding well-rounded players still seem to be the option. This means that without looking to add steals, owners can end up in the middle of the pack with a mixture of players who will add eight or more over the season, which is the new average. Again, to punt steals means to intentionally look away from players with speed, but if speed is only valued with the other categories, this means purposely avoiding well-rounded players.

Second, when players like Hamilton are dropping in mocks, this means that owners can add speed on the cheap, and also aim to end in the middle of the steals table. You also do not need to avoid drafting a second starting pitcher in the fourth round just to add speed. Not targeting steals, but also not punting steals, can let owners move to a more balanced draft and value players for multiple category contributions.

Third, with the recent trend of younger players starting earlier, adding a hitter like Mondesi mid-season can also add to the speed totals on a team. With many prospects appearing later in the year, adding those names and stashing them until after they are called-up seems to be another way to add reasonable speed to boost stats.

Punting steals is much harder when there is little value being assigned to speed-only players, so this would mean passing on players that can help elsewhere. For example, Christian Yelich is a top player, who also stole 22 bases, meaning he can help any team. Without being too blunt, the rabbit is dead in fantasy baseball. 

While every strategy should be taken within league context, at the end of the day, based on research for this article, it does not seem that punting steals is a valuable strategy due to the relative value of steals in current drafts. While it might sound like the easy answer, the ideal way to approach steals seems to be a middle path, with no direct focus on adding steals, but no attempt to ignore them as well.

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2019 Points League Draft Strategy - Fantasy Baseball

When discussing fantasy baseball. An often neglected-but-entertaining format is the points league. These exist in both cumulative season-long and weekly head-to-head formats.

While existential debates about scoring categories and their true depiction of player worth are endless, points leagues arguably get closest to the objective of sabermetrics. Points leagues attempt to define a player’s contribution (or detraction) in greater depth. For example, we know a triple is more valuable than a single, and these leagues acknowledge that.

Fundamentals are the same, but there are some unique strategies associated with points leagues. We want to ensure you’re acquainted with these aspects before your draft. On behalf of RotoBaller, here is the fantasy baseball 2019 Points League Primer.


How to Win Your Points League

There is a high degree of overlap with standard leagues, but the below table illustrates an overview of this scoring system. We’ll discuss four primary difference that could alter a manager’s strategy on draft day and during the season.

Note scoring weights and categories differ by league. Some leagues overweight wins or underemphasize saves. Others might have additional categories like quality starts or HRs allowed. Since this is a basic outline, we’ll operate under our assumptions, but remember to check the settings of your particular league.


1) Strikeouts and Walks Matter

Hitting-wise, in common leagues, strikeouts are a non-event and hitters only receive indirect credit for a walk if he tallies an RBI or eventually scores. Points leagues instantly gratify hitters for getting on base, the essence of offense. Likewise, since a hitter is wholly responsible for striking out, he is punished.

A key metric in points leagues is BB/K. Out of 140 qualified hitters in 2018, the median BB/K was 0.45. Jose Ramirez was an elite outlier at 1.33, and the poorest was Dee Gordon at 0.11. Even though Aaron Hicks struck out at a 19.1% clip last season, his 15.5% walk rate gave him the 10th-best 0.81 BB/K. Same story with Matt Carpenter. The 23.3% K-rate appears high, but considering his walk tendencies (15.1%), a 0.65 BB/K becomes much more palatable. On the flipside, Javier Baez was a revelation in standard leagues last year. But despite the breakout season, he suffered massive value destruction in points leagues with 167 strikeouts and just 37 walks. Standard league players will accept Baez’s weak on-base abilities as long as he cranks 34 homers again, but the trade-off isn’t as attractive when strikeouts are explicitly taxed.

Earning walks skews a player’s value positively. Carlos Santana, Joey Votto, and Andrew McCutchen were walk-friendly players that saw a spike in their points league value despite relatively disappointing seasons. By targeting a BB/K around 0.5, owners should enjoy a positive benefit from drafting patient hitters.

Since there is a positive relationship between strikeouts and slugging, managers should also analyze the strikeout in exchange for amassing points via power.


2) Slugging is More Important than Average

An important consideration in points leagues is a player’s slugging ability. Instead of treating all hits equally as AVG does, netting points for total bases rewards hitting for power.

Mookie Betts hit 47 doubles and five triples in 2018. These contributions went ignored in standard leagues. Because of his high average and HR production, Betts’ value in points leagues was comparable to his rank in standard ones. Meanwhile, Xander Bogaerts (48 doubles+triples), Freddie Freeman (48) and Anthony Rendon (46) were all more relevant from a total bases standpoint. Even replacement-level guys like Marcus Semien and Yolmer Sanchez received bumps in relevance from their non-HR slugging.

Incorporating walks, slugging and BB/K complements AVG and HR, painting a better picture of a player’s true worth. Since wOBA isn’t a fantasy stat (yet), points leagues get us close to that representation.


3) Pitching Stamina Helps, Losses Hurt

Pitcher durability is a key ingredient to strikeouts, ERA and WHIP. More innings pitched means increased chances to rack up Ks and achieve a steady state in ratios. In points leagues, rate stats are converted into counting stats by penalizing earned runs and walks. Pitchers also receive points for each inning recorded. It’s vital to consider IP alongside standard measurements like K/9, especially when innings limits are concerned

The theme rings true for Jose Berrios and Rick Porcello, whose strikeout prowess and ability to pile on innings offset frustrating ratios. Despite a disappointing 3.74 ERA, 1.31 WHIP and pedestrian K/9 for Dallas Keuchel in 2018, his seventh-best 204 2/3 IP buoyed his value in points leagues. While Kyle Gibson and Reynaldo Lopez won’t dominate fantasy headlines, their durability made them relatively more valuable in points leagues. Even James Shields with his ugly 4.53 ERA held some worth simply due to his 204 2/3 IP.

Losses are also significantly detrimental. In standard leagues, you either win or you don’t. In points leagues, a pitcher’s outcome is critical even while evaluating his individual ability. Players like Tanner Roark and Cole Hamels suffered from losses despite serviceable seasons last year. Getting tagged with losses can negate otherwise strong starts by pitchers and is a much more meaningful swing factor than just wins.


4) Scoring is Category-Agnostic

Fantasy managers are trained to draft a balanced team to address our 5x5 needs. In points leagues, that is irrelevant. A double is worth as much as a steal, and six strikeouts count the same as a home run. Buck the traditional mentality, take stats where you can find them.

Points leagues have the unique characteristic of allowing managers to evaluate players on their overall body of work as opposed to select niche areas. A simple comparison covers doubles and stolen bases. In 2018, there were 8,264 doubles hit and 2,474 steals in the majors. In standard leagues, owners are fighting for share in a stolen base commodity that is getting scarcer. In points leagues, the argument is to just ignore steals and accumulate stats where there is excess supply like doubles and homers. There’s no harm in rostering a squad of sloths.



Points leagues show considerable overlap with standard leagues. It’s still just baseball. But, they better-represent the evolving appreciation of advanced statistics. It creates depth in a player’s profile (i.e. walks, triples, innings pitched) and more closely embodies the real value of that player on the diamond. Customization is another perk of points leagues. Categories and their corresponding weights are discretionary, so it gives leagues more flexibility in determining which stats they value.

In our experience, points leagues are more challenging and require extra strategy, but hopefully, that’s why we all play the game in the first place!

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Using Sabermetrics For Fantasy Baseball Part 4 - 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 the case.

Why would this be? The answer, of course, comes down to batted ball distribution and the manner in which batters make contact.

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


How to Interpret Batted Ball Distribution

Let's first look at how all major leaguers fared on each of the major types of batted ball in 2018. Grounders generated a BABIP of .236. Flies were not as productive, posting a .117 figure. This makes sense, as popups 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 .672 BABIP. The difference between liners and anything else is startling. Batters want line drives.

Matt Kemp's resurgence provided a good illustration of what a few extra liners can do in 2018. He posted a .290/.338/.481 triple slash line thanks in part to a 26.8% line drive rate. Kemp was an afterthought in real and fantasy baseball terms heading into 2018 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. Kemp has a 22.5% LD% over his career, so luck was almost certainly the primary driver of his 2018. 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 .352 BABIP is driven by his career 25.8% 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 Mookie Betts BABIP credit for his blinding speed. This distinction has to be earned over numerous full seasons, however. Most LD% surges are more fluky Matt Kemp than sustainable Joey Votto.

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 2018, grounders offered a slugging percentage of .258, only slightly higher than the .236 BABIP they posted. Flies had a .690 slugging percentage, easily offsetting the lower BABIP for most fantasy players. Sluggers like Khris Davis 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 3.4% HR/FB despite a favorable home park 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 .900 slugging percentage to go with the .672 BABIP in 2018, 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. Next up, we'll look at the other major component of a player's batting average: plate discipline.

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Using Sabermetrics For Fantasy Baseball Part 3 - Statcast for Hitters

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 2018 season was struck by Giancarlo Stanton. It was clocked at 121.7 mph and left the ballpark. However, his teammate Gary Sanchez made an out with the second hardest-hit ball of the 2018 season, clocked at 121.1 mph off the bat. Clearly, it is possible to torch a baseball only to make an out.

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 2018 was 87.7 mph, but that stat is of little value. Exit velocity on airborne balls (both flies and line drives) 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 (or its even worse approximation, Hard%) to evaluate HR/FB and BABIP. You really shouldn't do that unless you believe that a grounder has a chance of going over the fence. So how do you figure out what's useful among these sabermetric measures?


How to Interpret Batted Ball Statistics

Baseball broadcasts will 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.

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

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 the 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, Khris Davis led baseball in Barrels last year with 70. He was followed by J.D. Martinez (69), Joey Gallo (66), Stanton (63), and Mookie Betts (61). This group passes the sniff test, as it seems like a collection of guys who consistently make high-quality contact. Likewise, Billy Hamilton managed only two 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. Gallo topped this list in 2018 with a 22.5% Brls/BBE figure, followed by Luke Voit (20%), Davis (17.2%), Max Muncy (16.9%), and Eric Thames (16.7%). Guys like Voit and Thames didn't have the raw BBEs to crack the Barrels leaderboard, but the rate stat suggests that they could be intriguing sleepers 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 last season (40 HR).

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 percent 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% last year.



Statcast is an interesting tool, but it's not yet enough to form the sole basis of your analysis. Exit velocity is one thing that goes into BABIP, but many other factors also play a part. Batted ball distribution is one of the most important among them, which we'll take a closer look at in Part 4!

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Using Sabermetrics For Fantasy Baseball Part 2 - HR/FB for Hitters

Using BABIP to predict a player's batting average is great. Average is a category in many league formats, and every hit is an opportunity to steal a base or score a run. But most owners find the long ball sexier.

Every HR comes with a guaranteed run scored and at least one RBI. Many owners build their teams around power for this reason. Yet fluky HR campaigns can happen just as easily as fluky batting average ones.

How do we tell the difference between a legitimate breakout and a fluke?


How to Interpret HR/FB

HR/FB measures the percentage of fly balls that leave the park. Last year, 12.7% of all fly balls ended up in the seats. Like BABIP, an experienced player's personal benchmark in the stat is a better indicator of his future performance than the league average. For example, Khris Davis is generally regarded as one of the top sluggers in the game today. His HR/FB was 24.1% in 2018, nearly double the league-average rate. If this number regressed to the league average, Davis wouldn't be very good. However, he has a career rate of 23.6%. Clearly, above-average power is something Davis just does. He should continue to crush bombs with regularity.

Large spikes or dropoffs in HR/FB are generally temporary, meaning that the stat is usually not predictive of a power breakout. Fantasy owners want to know the next power breakout, so this may be somewhat disappointing. Future power production may be predicted, however, by an increase in fly ball rate, or the percentage of a batter's flies as opposed to liners or grounders. There are limits here, as Billy Hamilton is never helping a fantasy team with his power no matter how many fly balls he hits. Still, FB% is generally the stat you want to look at for power potential.

Elite sluggers generally post a fly ball percentage of around 40%. Subjected to this test, Davis had a 48.8% fly ball rate in 2018 and a career mark of 42.2%. These rate stats, combined with a consistently above average HR/FB, make Davis the fantasy player he is.

Davis doesn't really illustrate the distinction between HR/FB and FB% because he excels at both. For a predictive illustration, consider 2018 NL MVP Christian Yelich. His HR/FB last season was an unbelievable 35%, powering fantasy rosters with a total of 36 long balls. Imagine how many long balls he could have hit if his FB% was higher than 23.5%.

Unfortunately, it seems unlikely that Yelich will be able to replicate his 2018 success in the power department. His career HR/FB is only 20.3% including his monster campaign last season, suggesting that significant regression is in order. Meanwhile, his career FB% (20%) is actually slightly lower than his 2018 rate. A dramatic swing change to join the proverbial "fly ball revolution" seems especially unlikely coming off an MVP season, setting Yelich up as a potential fantasy bust in 2019.

The recently retired Joe Mauer provides the best illustration of trusting HR/FB without regard for FB%. In 2009, Mauer went bonkers with a .365/.444/.587 line and 28 bombs. His HR/FB% spiked to 20.4% that season, but nothing in his history indicated he could maintain a level that high as his previous career best was 10.8% in 2006. Meanwhile, his 29.5 FB% was far too low to expect any real power production moving forward. He received first-round attention from fantasy owners in 2010, and the Twins gave him an extension they could not really afford. Mauer morphed back into the singles hitter we know him as, ruining many 2010 fantasy seasons and saddling the Twins with one of the worst contracts in MLB.

If you're looking for the 2019 version of 2010 Mauer, Eric Hosmer (19.4% HR/FB, 19.7% FB%), Shohei Ohtani (29.7% HR/FB, 32.9% FB%), and Ian Desmond (24.7% HR/FB, 21.5% FB%) all seem like strong candidates for power regression (in addition to Yelich). All three of the players listed here last year (Hosmer, Tommy Pham, and Domingo Santana) disappointed fantasy owners who drafted them in 2018, so consider yourself warned.



HR/FB is considered the BABIP of power because it can be used to evaluate whether a given player is outperforming his true talent level. A player with a large spike or decline in HR/FB should generally be expected to return to his established baseline moving forward. Ballpark factors may alter HR/FB, but in general raw fly ball percentage is a better tool to identify potential power breakouts.

Of course, it is possible for a batter to legitimately change his approach and permanently boost his HR/FB. Statcast allows us to measure precisely how hard a player is hitting the ball, potentially validating a performance that would otherwise be labeled a fluke. We'll take a closer look in Part 3!

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Using Sabermetrics For Fantasy Baseball Part 1 - BABIP for Hitters

Hello fellow RotoBallers! Sabermetrics have become an integral tool for fantasy baseball draft prep, but a concise resource for understanding the basics can be difficult to find.

This series attempts to define and explain all of the metrics fantasy owners may find useful, citing examples of how to use them in the process. Twenty degrees in applied mathematics are not required to use advanced metrics effectively, and this will be a no-math zone. We also won't bring in many of the metrics that are synonymous with advanced stats, most notably the fantasy-useless WAR, or Wins Above Replacement.

Instead, the focus will be on sabermetric statistics and ideas that are useful for predicting the standard stats the vast majority of leagues care about, such as batting average.


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 Mookie Betts.

Betts has been a fantasy force for a while now, but he took it to a new level with his MVP slash line of .346/.438/640 in 2018. A .368 BABIP helped him compile those numbers, and Betts loses a lot of value if we regress that all the way to .300. Should we really do that?

Betts is an elite speedster--he managed to steal 30 bases last season, after all. It makes sense that someone with Betts'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. Betts's career BABIP is .315, clearly indicating a sustainable ability to beat the league average .300. Of course, .315 is still a lot lower than his .368 figure from last season. If we assume Betts can beat the average BABIP, how do we know if he was, in fact, fortunate?

The answer is to look at BABIP by batted ball type. Betts 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, Betts posted a .374 mark on them last year. His career rate is only .316. Therefore, we can conclude that Betts will continue to outperform the league average on ground balls because his .316 career BABIP is much higher than the league average. However, he is unlikely to do so to the same extent he did in 2018.

Comparing BABIPs by batted-ball type year over year, Betts also benefited from more fortunate fly balls and line drives in 2018. His fly balls had a BABIP of .152 against a career mark of .138, while his line drives beat their career average by a whopping 75 points (.747 vs. .662). Regression should be expected to reduce Betts's BABIP toward his career .315 rate, but he still projects to beat the league average mark of .300 by a considerable margin.

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 dead last in Statcast's Sprint Speed metric last year. These factors figure to hurt his BABIP on grounders, and Pujols's .160 last year indicates that it did. This is not a new trend, as he hit .192 on grounders 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 .247 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, LD%, 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. Next time, we'll look at a stat called the BABIP of power, HR/FB.

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RotoBaller Early Mock Draft Analysis (Rounds 3-10)

A group of 10 RotoBaller fantasy baseball experts recently came together to conduct a slow mock draft for the 2019 season. Was it way too early? That all depends on who is asking. But with it complete, we can start to look at where players ended up on the board.

This is the first staff mock draft but will not be the last prior to the start of the MLB season. I'll take a look at rounds 3-10 to analyze where the values were found and where some of the biggest reaches were made.

If you have any questions or comments, feel free to Tweet me @RowdyRotoJB


Early 2019 Mock Results

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The third round started with Anthony Rizzo, followed by the gnarliest of SP runs you'll ever see. Carlos Correa and Kris Bryant joined Rizzo in the Ignored but Not Forgotten Club, followed by a Whit Merrifield sighting at #30 overall. Clayton Kershaw dropped all the way to #33 overall, and Juan Soto was taken by yours truly a full two rounds later than fellow NL ROY finalist (well, the winner) Ronald Acuna. The first RP was drafted in the 5th round, but at least it was the correct RP in Edwin Diaz, and the AL Cy Young Award winner Blake Snell lasts until pick #50. The Yankees kind-of-still shiny new toy James Paxton was drafted in the 6th round, two picks after Playoffs stud Walker Buehler, and Mitch Haniger went at #66 immediately following his teammate Nelson Cruz. The first Catcher, the Kraken, was taken in the 8th round, and the first non-closer RP Josh Hader was taken for ratio help at #85. The 9th round finished with 2nd half breakout-rookie Adalberto Mondesi, and we finish up with Brian Dozier as this article's Mr. Irrelevant at #100 overall.


Favorite Picks

Blake Snell, TB - SP13 (#50 Overall)

The guy is 25 years old, won the AL Cy Young award, and finished 2018 as the SP4 (12th overall) in 2018 fantasy leagues. All of this, and Troy was able to scoop him up at the end of the 5th round as the 13th SP off the board? What were the rest of us smoking? His xFIP was a run and a half higher than his ERA due to a .241 BABIP and 88.0 LOB%, but I don't think anyone doubts the legitimacy from this season. I think this will actually be a fairly common draft spot for Snell in 2019, just due to guys looking to grab just one ACE in the early rounds generally, and despite the breakout Cy Young campaign Snell just isn't instilled in peoples minds as a true fantasy ace yet. *Whispers, He is though.

Vladimir Guerrero Jr., TOR - 3B14 (#87 Overall)

Despite all of the hype, and seeing the fantasy impact Juan Soto and Ronald Acuna had immediately upon their big league arrivals, Little Guerrero dropped all the way down to Ellis in the ninth round. The kid mashed all the levels of Minor League this season, hitting 20 total HR in just 408 PA, and hitting .402 across 266 PA in AA and .336 through 128 PA in AAA. Steamer projects Guerrero with a 75/22/77/.306 line in 2019, which basically makes him Anthony Rendon on a bad team, drafted four rounds later with massive upside.

Adalberto Mondesi, KC - 2B10 (#90 Overall)

After massively disappointing in his two previous big league stints, the spawn of Raul Mondesi defined the word BREAKOUT this season. In just 291 PA, the 23-year-old amassed 14 HR, 32 SB, and a .276 BA. Simple math exaggeratedly shows us 28/64 potential from Mondesi over a full season. WHAT?! This absurd ceiling alone is enough to warrant a draft pick much earlier than where Troy got him in the 9th round. I've seen him go as early as the SECOND round in early mock drafts this offseason.


Least Favorite Picks

Kenley Jansen, LAD - RP2 (#57 Overall)

Who the hell took a closer that needs offseason heart surgery, allowed a 5.71 ERA in his last 17.1 IP, and blew back to back saves in the World Series? was me. Looking back, I probably should have taken Zack Greinke, but I am a sucker for relief pitchers. I don't even pay attention to saves; I just want the ERA/WHIP dominance and the steady sprinkle of strikeouts. I usually can't pass up elite bullpen arms. But with the "down" season he had in 2018, the unknown of how the irregular heart-beat actually affects his game, or whether or not the surgery will actually fix it, I think you let Jansen drop to a decent value or let another manager take the risk where I took him. I'd much rather snag Blake Treinen two rounds later.

Marcell Ozuna, STL - OF19 (#58 Overall)

Ozuna reverted right back to his pre-2017 ways this season, almost repeating his 2016 numbers, and finished the year as the 77th ranked player in fantasy. As of now, I have to assume the 23.4 HR/FB% that led to 37 HR and .355 BABIP that produced a .312 BA in 2017 were career outliers and the 69/23/88/.280 line is more of what we can expect again in 2019. It's a safe pick with his '18 numbers being the floor for the past three seasons, but I would rather take every OF that went in the following round: Eddie Rosario, Tommy Pham, Nelson Cruz, Lorenzo Cain, Justin Upton, and Mitch Haniger.


Sneakiest Values

Zack Wheeler, NYM - SP24 (#91 Overall)

I love taking any chance I get to talk about Zack Wheeler, my fellow East Paulding High School alum. Zack took a massive step forward in 2018, setting a career-high in K% and a career-low in BB% while posting a 3.25 FIP over 182.1 IP. But what was most impressive was managing to cut his Hard% from 32.8 in 2017 down to 24.8 - second lowest in the league in 2018. Wheeler found success by increasing his fastball usage and doing away with the sinker. He threw the fastball 8% more this season and finished with a 22.7 wFA which was fifth-highest among starters. The cheese was devastating, and it got better as the season wore on. After posting a 4.44 ERA over the first half of the season, Wheeler was quite possibly the best pitcher in baseball after the All-Star break, posting a 1.68 ERA which was slightly better than even his Cy Young-winning teammate. There are big things coming in 2019 for the pride of Paulding County, GA.

Corey Seager, LAD - SS10 (#67 Overall)

After injuries ruined the end of his 2017 season, many of us expected Lil Seager to bounce back to his 2016 form where he finished as the 43rd ranked player in fantasy. Instead, the poor guy needed Tommy John surgery before the month of April was over. Steamer projects a repeat of his shortened 2017 campaign this upcoming season, which is fair considering the question of when exactly Seager will be back in the lineup every day. Even if that is the relative floor, then Ellis scooped him up at a fair value. But if he comes out of this recovery and regains that 2016 stuff, or even takes a step forward as most 24-year-olds tend to do, then what a steal for the MIF slot.


Biggest Reaches

Whit Merrifield, KC - 2B5 (#30 Overall)

Does Whit Merrifield warrant a draft pick in the top 30 after what he did this season? Absolutely. He finished 2018 as the 19th ranked player in fantasy. He led the league in SB (45) and had a higher BA (.304) than the next seven speedsters behind him - Mookie Betts was the eighth. But as he enters his age 30 season, you got to assume the legs start to slow down, and that BABIP that jumped 50 points after 2017 has to come back to the norm. Not to mention, the Royals will continue to be a hot mess in 2019, so the run scoring possibilities remain limited. So does he warrant the pick, yes. Should he be taken that early, no. Especially considering the two 2B behind him on the draft board are super-hyped rookie phenoms, I feel you can wait to pull the trigger on Merrifield. Ozzie Albies was taken 38th overall and Gleyber Torres was taken 59th.

Matt Carpenter, STL - 1B4 (#35 Overall)

Again, another example of a player being drafted where he technically should based on 2018, but leaves zero room for value in 2019. Also, I may be the worlds biggest non-Cardinal supporting Matt Carpenter fan. In fact, I predicted the massive season back in March (pay no attention to any of the other predictions). The dude just turned 33, but we want to draft him exactly where he finished the 2018 season ranked and ahead of young studs like Rhys Hoskins and Cody Bellinger? Jesus Aguilar is five years younger, and finished just two spots behind Carpenter in 2018. Try to find his name in the top 100 of our draft....I'll wait. In light of more context, Connelly looks to have drafted him as his second baseman (and he did draft Bellinger the next round) so it's better than I'm making it sound. But even then, as a second baseman we go right back to my point with Whit Merrifield. Reaching for the age before the young beauties even get picked is bold. Are these two picks bad? No, I love Carpenter and Merrifield. I would just rather let the field take the new shiny toys and scoop up my reliable studs later to maximize value.


Best Team

Tie - Ellis/ Brendan

I love both teams for separate reasons. Ellis executed my usual fantasy baseball draft strategy flawlessly. 1. Draft stud hitters early focusing on MIF and OF, which he did with Altuve, Judge, Benintendi, and Story covering all categories. 2. Make up for lack of pitching by getting a huge upside young SP with a couple of excellent RP to counter the ERA/WHIP baggage your late round SP fill-ins will carry: enter Buehler, Diaz, and Treinen. 3. Ignore CIF early, as they tend to be the deepest offensive positions. He grabbed Vladimir Guerrero Jr (as mentioned above) for 3B, and having a leg up at the Catcher position from Realmuto partly makes up for not having an "elite" first baseman.

Brendan, on the other hand, played my alternate draft strategy perfectly, typically reserved for keeper leagues or leagues I know all the other managers and I know I won't get the guys I want based on their predicted reaches/biases. That strategy is to sit and enjoy the draft, and take what the field gives me. Almost every stud that dipped in value from a "down" season in 2018, Brendan gladly gobbled up. Paul Goldschmidt, Bryce Harper, Carlos Correa, Clayton Kershaw, Noah Syndergaard, Justin Turner, and A.J. Pollock all present fantastic return on investment potential from where he drafted them. For the record though, not a fan of Goldy over JD Martinez or Christian Yelich.

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RotoBaller Early Mock Draft Analysis (Rounds 1-2)

I know what you are probably thinking as you click this link, who is doing fantasy baseball drafts in October and November?! Well, the answer to that is 10 Rotoballer Fantasy Baseball enthusiasts who are already longing for the long hot days of summer and the return of everyday baseball.

This is the first of many staff mock drafts that you will see appearing on the site over the coming months. Today I am going to be breaking down the first two rounds to look at early strategies and who might be surprise first rounders this season. I will also be looking at where feels like the right place to take the first pitcher and who it should be.

If you have any questions, comments or just want to tell me how wrong I am, feel free to Tweet me @benrolfe15


Early 2019 Mock Results

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Round 1

1.01 Mookie Betts, OF, BOS

1.02 Mike Trout, OF, LAA

It was no surprise to see Mookie Betts and Mike Trout go off the board with the first two picks. I was hoping one of them would fall to three, but it was not to be. I could have easily made a case for either of these guys as the first overall pick. However, with Betts being in the slightly better offense and coming off a monster .346 batting average this is the way I would have gone with pick #1.

If this was an OBP league, I would have leaned to Trout, because despite Betts superior average Trout had a higher OBP at .460 and has been over .400 each of the last three years. Even in a standard league, if you want a sure-fire cannot miss pick at #1, then Trout is probably your guy, but Betts might just offer that slightly higher ceiling in that standard format.

1.03 Jose Ramirez, 2B/3B, CLE

1.04 Francisco Lindor, SS, CLE

This was another either/or for me with the number three pick. I very very nearly leaned to Lindor for the shortstop eligibility and later in the draft I kind of wish I had. Ramirez had the advantage in steals last season and had a plus .300 batting average more recently, so he is perhaps the slightly safer pick. However, as much as improved as the shortstop position is I found myself scrambling later in the draft and for that reason, I wish I had gone Lindor at three. If Ramirez is eligible at second base in your league, then that might just swing the pendulum back his way but if not then I would now lean Lindor.

1.05 Nolan Arenado, 3B, COL

1.06 Manny Machado, 3B/SS, FA

It is always going to be hard to ignore Arenado while he plays baseball in Colorado. The boost that park gives takes him from being very good to being one of the absolute elite. He can help you in four categories, and he never seems to miss time recently. The lack of steals should not concern you because there are not many five categories studs outside the top four.

Machado was a little bit of a reach in my opinion given the uncertainty of where he plays baseball next year. However, I have already discussed locking up shortstop early and the benefit that brings. There is a good chance picking in the six spot that none of Machado, Turner or Bregman are going to be available in round two. Therefore, I have no issue if you want to gamble on where Machado lands, lock up shortstop and get really solid four category production.

1.07 Jose Altuve, 2B, HOU

1.08 Paul Goldschmidt, 1B, ARI

There are two things that stand out about this pair of hitters. Firstly, their struggles at times in 2018 are great evidence for why the safety Trout brings should make him the number one overall pick. Both of these guys have been discussed in that #1 spot in recent years and have had struggles. Secondly, this is a story of lost stolen bases. Altuve's steals nearly halved from 2017 to 2018, and that is a major loss. Of all the declines he had last season that one concerns me the most. The numbers are there to suggest it was maybe injury and bad luck which brought down the home runs, runs and RBI. However, generally, players decide whether to steal or not and the fact those numbers are down worries me. Again injuries may play a part, but if it is a philosophy change from Altuve and the team, then he loses quite a lot of value. This pick sort of splits what he could be. If he gets everything clicking and steals his bases, then he is a top-five selection. If he does not, then he is closer to being a second-round selection.

Goldschmidt also saw his steals drop off for a second year running and that is enough to drop him from top three contention to back end of the first round. He got there in a weird way, but the rest of the numbers are fairly similar, so it is just the difference between a five-category contributor and a four-category guy that means this is not the bargain you might have thought a year ago.

1.09 JD Martinez, OF, BOS

1.10 Christian Yelich, OF, MIL

I think this is a bargain for Martinez. He is essentially Arenado in terms of production, and he is arguably in a better offense. If he were DH-only, then I would see him going down here, but for me, he should have been the pick at six. I can see why scarcity of the middle infield was valued first, but he definitely should have been above Goldschmidt.

If Yelich repeats 2018's numbers in 2019, then we will be talking about him with Trout and Betts next year. He had a monster year, and power was the big differentiation mark for him from the past. Now the question is whether that is a park effect or an aberration. If it was a park effect, then we could very easily be seeing this as a tremendous value by the end of 2019. I love this pick and Yelich is the reason why I want to pick in the back half of the first round in 2019.


Round 2

The young infielders

I love pairing Alex Bregman with Yelich to give such an incredibly balanced start to a draft. It really allows you to go anywhere in the rest of the draft and means you are not chasing statistics in the next few rounds. The same goes for getting Trea Turner to pair with Martinez. You have the power, and now you have the steals without taking a zero in the power column.

Towards the back end of the second round was Javier Baez. He has a lower floor than either Turner or Bregman, and we have only really seen him do it all once. However, locking up your middle infield with Lindor and Baez is a fantastic way to start your draft and means you will have a better middle infield than anyone else in the draft and follows the Major League model of building strong up the middle.

The outfield run

We had a run on outfielders in the middle of the second round. Hopefully, Harper continues his yo-yo effect of the last few years with his batting average so we can see him climb back over .300. If he does, then you are probably getting first-round numbers in the middle of the second round. If he doesn't, then at least you are unlikely to have a complete bust.

Aaron Judge and Ronald Acuna have some similarities. Both have a lot of swing-and-miss in their game, but both have a ton of talent. Both can put up per game numbers equivalent to a first round pick, but as with any young player, there is a chance the bottom falls out somewhat. Combining Judge and Altuve could be a great pair if Altuve gives you the steals and Judge the power. Grabbing Acuna when you have Arenado is a great case of adding incredible ceiling to superb safety.

We end with Charlie Blackmon who saw some decline last year. At 32 age is against him bouncing back but things were not wildly out of whack last season, so it is not beyond the realm of possibility that he bounces back. If he does, then you have a nice little five-category contributor in the middle of the second round.

The first pitcher!

I could not believe Max Scherzer fell to me at this spot! I was actually looking at the Chris Sale, Corey Kluber, Jacob deGrom group but happily gobbled him up when he got to me. Your strategy at pitcher should depend on the size of the league. In 10-team leagues, my strategy is to get a couple of really good ones early, grab some nice upside in the middle and then stream at the bottom end, because in shallow leagues there is a lot of pitching depth throughout the season. In the same vein, in 10-team leagues, you can often find contributing hitters on the waiver wire during the season. This draft played perfectly into my hands, but I am not sure I would be this lucky again. However, if this was Sale in this spot, I would still have taken a pitcher here. I would actually have taken Scherzer with pick 11 if I had been able to get Yelich at 10.

The elder statesmen

Both of these pics are absolutely fine ways to end the round. Stanton has the incredible upside but even what he did last year is more than enough on the swing. I am not sure I want to start my draft with two outfielders, but the ceiling of Stanton in New York means I understand why you would do it.

Freeman is frankly a little boring but that is not a bad thing. You can feel fairly safe with what you are getting, but unfortunately, the power is now a little underwhelming. However, first base is really ugly once it gets a little deeper, so I understand wanting this safety to combine with the also safe option of Trout.


The Final Word

I love some of the pairs in these two rounds. Yelich and Martinez could be the steals of the draft that late in the first round, as could Scherzer. Acuna and Judge perhaps have the biggest bust potential just simply because of their strikeout rate. However, their upside means they are worth the second-round gamble. The lesson for me here is that there is a lot of value in locking up shortstop at some point in these two rounds. I would not reach for any of them, but if you are between two players, then the positional element is a nice tiebreaker.

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Two-Start Pitchers: What Are They Really Worth?

The idea of the “two-start pitcher” makes an appearance on most fantasy baseball podcasts, articles, sites, and newsletters as players are ranked and recommended to owners and teams.  Selecting pitchers based on match-ups, park factors, and opponents over the scoring week is a regular debate as owners plan their rosters. At the same time, other than knowing that these pitchers offer an additional start each week, often owners do not understand what these pitchers do to their line.  How do they add to subtract from ratios and counting stats? What does a bad start do to the overall line?

That is where this article takes up the conversation: what exactly does a two-start pitcher do to a fantasy team?  Specifically, this piece highlights three findings that can be taken from the two weeks of data studied. While this data is only generalizable to the sample size, as pitchers change week to week, it still offers some insight into the process of selecting a starting pitching strategy.  

One word before walking into this piece, no matter what lessons owners can learn, all lessons should be taken within the league context of each team. While the article will try to offer some advice to both roto and points leagues, owners are the best guides to their team and strategy. With that, onto the data.  


What to Make of Two-Start Pitchers

Before diving into the findings in this article, it is worth taking a step back to put the generic two-start pitcher in some context.  Over the course of fantasy baseball’s 10th and 11th week of games, a total of 80 pitchers were expected to make two-start pitching appearances.  These numbers slanted a bit to the previous week when 49 were on the docket, but overall, the numbers fluctuate based on plenty of variables and events.  For example, with the new allotment of off-days this season due to the CBA, some teams play only five games in a week, whereas others, already affected by weather, might play all seven days.  

Of those planned two-starts, a total of 81% ended up happening as planned.  The change in schedules means that one out of every five pitchers will not make that second start.  The variance will also change week to week, but in general, all two starts will not happen for the factors listed before.  That being said, for the sake of argument, there are a total of 150 starters in the majors at any one point, each week approximately 27% will be scheduled to make two starts.

The other piece to add to the data and context is that not all two-start weeks are created equal, as some weeks the starting pitcher is Corey Kluber, and some weeks they are Homer Bailey.  The variation means that even when comparing week to week, the fluctuations are apparent based on the match-ups. For the sake of the data used in this article, two full weeks of data offer a broad enough sample size to make general findings that should support the underlying baseline findings.  At the same time, not every team has a Corey Kluber in their rotation, so knowing what the average two-starter does is, in some ways, more valuable to the fantasy owner trying to figure out who to start.


Finding #1: Two-starts are at best equal to league average one-start pitchers

Over the course of all 65 of the two-start weeks that occurred in weeks 10 and 11, the average pitcher worked for 11.21 innings, producing an ERA of 3.76, a WHIP of 1.24, and striking out 10.26 batters. At the same time, each pitcher only averaged 0.77 wins, meaning that the starter just won two out of every five starts over the sample size.  

To factor in the variance in pitching quality, a second survey was run on the data during which the aces, or consensus top 20 starters, were removed from the data sample.   Under this sample, the following averages appeared over the same sample timeline: 11.07 innings, an ERA of 4.19, a WHIP of 1.24, and 9.59 strikeouts.

Without the top pitchers, two-start weeks average close to the same number of innings but add close to a half earned run over that week.  What does stand out from the comparison is that the WHIP stays the same, but these non-aces lost close to a K a week for their owners. When the Major League average for ERA sits at 4.06 so far this season, the average two-start starter is 3.2% worse than a league average starter.  League average WHIP this season sits at 1.30 meaning that the ace-less two-starters are a bit better than that mark with their rate of 1.24. Strikeouts appear to be a bit higher, or right around average when comparing the data set to season norms.

In this way, the average two-start pitcher is worse than league average regarding runs but better or average with WHIP and K numbers.

Why might this be the case?  When pitching twice over the course of the week, it makes sense that one good start and one average start ould result in closer to the average mark, whereas one bad start and one good start would equalize out to at best average and at worst, a worse average over the week.  It is not uncommon for even the best starters to have a bad outing which is magnified during one week of data.

An excellent example from the data was Tyler Skaggs, who against Detriot gave up five earned runs in five innings, but rebounded again the Rangers to throw six scoreless innings.  Owners would love the last start but perhaps winced when seeing the first performance. At the same time, Michael Fulmer gave up five earned in 3.1 innings, and four in six versus the Angels and Blue Jays.  These results, even if not a two-start week, would not have been excellent for most teams.

What this means is that in roto leagues the two starts matter much less than in points leagues, as that one bad Kluber start equals out over the 30+ starts that he will make in a season.  In a points league or any weekly scoring league, the bad start is magnified. At the same time, if that Kluber start happens without a second start, then it hurts the overall line more than the averaging out or weakening of the gains from a two-start week.  Owners should already be looking to both match-ups when setting line-ups, but also recognize that there is no unique benefit from having two starts in a week unless innings count in match-up specific scoring.

BALLER MOVE: Prioritize good one-start weeks over average two-start weeks in non-innings leagues


Finding #2: Road Pitchers are Better than Home Pitchers

Perhaps the most exciting piece of insight that comes from this sample of two-start pitchers was the variance in performance if the starter in question made both of their starts at home or on the road.  In a vacuum, it would seem that the average pitcher at home would perform better than on the road, but that turns out not to be the case. Over the course of the two weeks of data collected, 14 pitchers made both of their starts at home and 19 pitchers who made both of their starts on the road.

For the pitchers making both of their starts at home, the gross average pitching line for both of their starts was: 10.95 innings, 4.64 ERA, 1.41 WHIP, and 9.07 Ks over that time.  These numbers are much worse than league average by 0.6 earned runs and 0.5 Ks over both of those starts. Also, two-starts at home only posted 0.36 wins which is much lower than the expected total.

For pitchers making both of their starts on the road, the gross numbers were: 11.54 innings, 3.57 ERA, 1.15 WHIP, and 10.95 Ks.  At the same time, the average road-only pitcher earned 0.84 wins over their two starts. Road only pitchers were more than an earned run better than the home-only set and lowed their WHIP by 0.3.   

Why might this be the case?  Looking to the pitchers and the match-ups there is no skew concerning top pitchers in either grouping, and the parks seem to be much the same.  The road slate did feature Chris Archer and Jake Arrieta, but those two on their own, should not have affected the large sample enough. Arrieta also pitched a dud in San Francisco for his second start, hurting his case over that scoring period either way.  Even if taking these pitchers out of the equation, the road starters still were a bit better than the home-group, which is still unusual based on standard fantasy ideas of park factors. The road starts also had more starts at Coors which should affect the overall line, but not in the way that was expected  

BALLER MOVE: Prioritize road-only pitchers making multiple starts in a week


Finding #3: Two-start pitchers struck out more in their second start than their first start on average  

Of all the factors listed, this might be the most context-dependent observation, and something that this study will return to at a later date, but also shows a clear trend over two weeks of data. For context, in both weeks there were top starters and fill-ins, and the data trends still existed with that context.  The other reason this trend stands out is that it appears in both weeks with a noticeable gap, so not unique to one slate of starters.

For week 10 starters, in their first game pitchers averaged 4.48 Ks, and in the second, 5.56 Ks.  For week 11 starters, in their first game, pitchers averaged 4.41 Ks, and in the second, 6.07 Ks.

The numbers are even starker when removing the aces from the data with a week 10 jump from 4.15 to 5.24, and in week 11 the increase went from 3.96 to 5.82.

Why might these numbers be the case?  Typically a second start in the week occurs on a weekend date which might account for some of the increase in Ks, as some pitchers are better during afternoon games on Sundays, or even better in Saturday night games. At the same time, with days off, there is a higher chance that two-start pitchers are on their regular schedule, and are not getting an extra day of rest in between starts which might also account for the change in numbers.   

Weekend games are also more likely to see reserve hitters due to wear and tear, but should not seem to account for all the difference. The best “proof” here would be starting catchers getting a day off after a night game, and the backup catcher on most teams is mostly glove and no bat.  Attendance factors could mean there are more aggressive hitters at play, which would support more strikeouts across the board. While still a mystery this is one of the most actionable findings and should influence owners moving forward.

BALLER MOVE: When in doubt, two-start pitchers are most valued for high strikeout match-ups in their second game; prioritize these match-ups. Also, one clear value to two-start performances is the gross number of Ks that they can provide for teams and owners.


Next Steps

While stated in the introduction, this data should only be used to understand what happened during the 10th and 11th fantasy weeks, but this does offer a step to begin to add more context to two-starters moving forward.  The plans will be to release two additional articles to support this process. The first will dig into the pitchers highlighted here, and identify who stood out and who surprised based on match-ups.

Second, the plan is to check in at least once, if not twice, over the season to see if the trends form these weeks appear to continue. While frustrating, this article leaves owners with more questions than firm answers, but if the trends in this article are accurate across multiple data sets, this could change the strategy of approaching starting pitchers based on more than just match-ups.     

What can be said is that two-start pitchers might not be as valuable as they appear on the surface, and when in doubt owners should rely less on the multiple starts as opposed to the pitching pedigree itself.  This means do not shoehorn a pitcher into the line-up due to two starts as the results are not much better than an average one start, but the risk is much higher.


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Using Sabermetrics For Fantasy Baseball Part 15 - Minor League Stats

Once you've grown accustomed to having advanced tools to help make fantasy decisions, it can feel disorientating to be without them. Prospects are increasingly becoming a focal point in both real and fantasy baseball, but the minors simply do not have all of the data available for MLB players. For example, advanced plate discipline stats, Pitch Info, and anything Statcast-related are all currently unavailable for minor league campaigns.

Does this mean we go back to looking at ERA and batting average as the only indicators of future performance? Of course not! Instead, we do our best to work with what we have. The process begins by looking at the environment. Higher levels of competition result in more accurate data, so you should start by excluding anything lower than Double-A if a player's track record allows it.

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


How to Interpret Minor League Stats

The first point to remember is that the baseline for certain predictive metrics is different on the farm. Mike Podhorzer of has an excellent article detailing the specifics. For example, Double-A hitters collectively posted a .306 BABIP last year, while their Triple-A counterparts managed a .317 figure. Both marks are significantly higher than MLB's .300 BABIP, making a performance that looks fluky actually league-average.

Another common sticking point is IFFB%. Double-A batters posted a ludicrous 21.6% IFFB% on their fly balls last year, while their Triple-A counterparts were only slightly better (20.8%). This leads many fantasy owners to conclude that EVERY minor league prospect has a massive pop-up problem, but this is not the case. The stat is calculated differently on the farm, and you need to halve it to get something approaching an MLB projection.

Like MLB, each minor league and ballpark also has its own unique quirks and tendencies. For example, the Pacific Coast League is a Triple-A league notorious for inflating offensive statistics. Imagine if an entire league played in Coors Field every game. That's basically the PCL.

For PCL players, a batting line may look good at first glance, but really represent only an average performance. Likewise, pitchers may put up dreadful numbers even after they are ready for the Show. For instance, a certain PCL pitcher put up a 9-7 record with a 4.60 ERA in 133 IP in 2014. His K% was a robust 24.9%, but none of his other stats screamed MLB ready.

However, some fantasy owners noticed that his BABIP against was a ludicrous .378, a number that would almost certainly regress in a different environment. The pitcher never ran a BABIP that high in any other minor league stop. His LOB% of 67.2% would likely climb as the BABIP dropped. We have FIP for minor leaguers, and this pitcher's was 3.70--still not great, but much better than his ERA.

Despite ugly Triple-A results in 2014, this pitcher pitched in the majors for 150 innings in 2015. His 9-7 record repeated itself, but his ERA fell to 3.24, right in line with a FIP of 3.25. The K% he flashed in the PCL translated to the majors, where he posted a strong 27.5% rate. His name is Noah Syndergaard, and he definitely had owners kicking themselves by the end of 2015 for trusting minor league surface stats. Nothing changed in 2016, as Syndergaard went 14-9 with a 2.60 ERA and 29.3% K%. Injuries limited him last year, but he was still elite in his 30 1/3 IP (2.97 ERA, 1.31 FIP, 27.4% K%).

If memorizing each league's tendencies is too overwhelming for you, you can look at Weighted Runs Created Plus (wRC+) as a shortcut. This metric sets 100 as the league's average offensive output, with each number higher or lower representing a one percent difference in either direction. This means that a wRC+ of 95 is five percent worse than league average, while a mark of 110 is 10 percent better. While the formula does not directly translate to fantasy value, park and league adjustments are already included in the calculation.

Another common problem with minor league statistics is sample size. It is easier to run an unsustainable BABIP or HR/FB in a small sample than a larger one. The minor leagues compound this problem by allowing a healthy player to be called up or demoted multiple times in one season, leaving us with two or more partial season samples instead of one full season of statistics. Astros shortstop Carlos Correa illustrates this, as he had a grant total of 246 PAs at Double-A and Triple-A combined before his MLB call up in 2015.

Due to the small sample, Correa's BABIP was unreliable. In this situation, I like to examine the player's plate discipline numbers because they stabilize (or become predictive) more quickly. At Double-A, Correa had an 11.3% BB% against an 18.8% K%, indicating a strong knowledge of the zone. Triple-A saw his BB% drop slightly to 10.6%, but a drop in K% to 12.4% made his overall plate discipline profile stronger.

Correa posted a 9.3% BB% and 18.1% K% en route to his Rookie of the Year award in 2015. Correa was even more willing to walk in 2016 (11.4% BB%), but struck out a little more often as the league adjusted to him (21.1% K%). These trends held steady last season, as Correa posted a 11% BB% and 19.1% K%.

Plate discipline is harder in the majors than the minors, and we don't have the additional information provided by metrics such as O-Swing%. Still, Correa seemed to possess strong discipline in the minors and managed to take it with him as soon as he was called up to the bigs. In general, a player won't be completely overmatched in the majors if he had strong plate discipline numbers in the minors.

The examples above were chosen because they now have more than one season of MLB data confirming their minor league trends, but this methodology could have helped you in 2017. For example, Rhys Hoskins combined stellar BB% marks (13.5% at Triple-A last year, 12.1% at Double-A in 2016) with sky high FB% (48.6%, 51.6%) and HR/FB (18.2%, 19.9%) rates to profile as an impact power bat with enough plate discipline to avoid hurting your batting average. Owners who took a chance on him got a .259/.396/.618 line with 18 HR in 212 PAs.

By contrast, blindly believing minor league surface stats could have pointed you in Dominic Smith's direction. He slashed .330/.386/.519 with 16 HR at Triple-A Las Vegas before his MLB debut. However, Las Vegas is the Coors Field of the PCL, helping him compile a 28.3% LD% and .380 BABIP nobody could sustain in New York. He was also allergic to fly balls (26.2% FB%), making power difficult to project. He ended up slashing .198/.262/.395 with nine dingers, burning owners who counted on him for the stretch.

Stealing bases is easier in the minors, but elite success rates are still something to look for when projecting fast players. Age is also a factor for minor leaguers, as a 28-year-old dominating a bunch of teenagers at Rookie ball isn't really that impressive.



To conclude, the fact that we do not know a minor leaguer's average airborne exit velocity or BABIP on ground balls does not prevent us from analyzing minor league players for fantasy purposes. We have tools such as BABIP and BB% for hitters and FIP and LOB% for pitchers. We can still place these numbers into context by examining any given league's tendencies. Finding rookie breakouts before they happen is still challenging, but that's what makes it a worthy endeavor.


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Approaching Rookies and Prospects in Redraft Leagues for Success

Everyone wants to be the guy to say they hopped on the bandwagon of the next up-and-comer before he comes up and breaks out. This often causes younger players to be overvalued, particularly in single-season leagues where some youngsters may not even see meaningful playing time.

Identifying the rookies that will actually get playing time, though they may not have as much potential as guys in the lower minors, is a necessary skill for managers in redraft leagues.

The first thing you have to do is forget that any player below Double-A exists. Vladimir Guerrero Jr., Bo Bichette, and Brendan Rodgers are all very interesting prospects with high upside but you’re better off letting a foolish league mate stash them until they inevitably realize that none of those guys are going to be making an impact in the majors in 2018.


Approaching Prospects in Redraft

Players in the high minors are another story. Any blue-chip prospects in Triple-A can be stashed, but they might not make an impact in the majors right away. Whether you should be targeting these players late in the draft, scooping them up via free agency, or not touching them at all depends on whether you are playing in a H2H or Rotisserie league.

In H2H leagues, the goal should not necessarily be to dominate the regular season, but to make the postseason with the best roster of any postseason team. If this means getting in as the last playoff team, so be it. In H2H leagues with a playoff at the end of the year, teams generally have a lot more leeway to stash prospects so long as their team is on track to make the playoffs. The fortunate part about playing in H2H leagues is that teams can draft guys like Nick Senzel, who probably will not begin the year in the major leagues and stash him. If your team is succeeding without Senzel in the big leagues then there is no reason to not hold him, but if your team is struggling and he’s close to being promoted, attempting to deal him to a team near the top of the standings who can afford to harbor a prospect in return for an asset that would be of more immediate help is a wise strategy.

Down the stretch, stashing prospects becomes more imperative in leagues that have playoffs. Blue-chip prospects that are in Triple-A often make their debuts in the middle of the summer and these are guys that you do not want to miss out on. Stashing them a few weeks prior to their eventual call up will bolster your team down the stretch for playoff runs for a relatively cheap price.

In Rotisserie leagues, stashing prospects is an entirely different ballgame. Since there is no playoffs, prospects that do not get called up until mid-August have relatively minimal impact and can be ignored for the most part; if you can afford to stash a prospect until he comes up in the last two months of the season, you probably do not need the help. On the other hand, if you scoop one of the prospects hoping to hit a home run in mid-to-late August and rocket up the standings, chances are that it’s going to be too little too late. In H2H leagues, stashing prospects is a far easier and safer game than in Roto.


Handling Rookies

Rookies and prospects aren’t that different; the fundamental distinction between the two is that prospects are not yet in the majors and rookies are more guys who are being drafted and will be starting the season in the bigs. For example, Austin Hays is being drafted as a rookie whereas a guy like Kyle Tucker is being drafted as a prospect. Tucker has an outside shot at making an impact this season and Hays is guaranteed some playing time due to starting the year in the majors.

This brings me to my next point: sometimes, opportunity is more valuable than skill. There are very few people that will tell you that Hays is a better ballplayer than Tucker, but that does not necessarily mean you should be scooping up Tucker in your redraft leagues. Guys who are guaranteed to start the year in the majors and get decent playing time like Hays, Lewis Brinson, Ronald Acuna, and Willie Calhoun, to name a few, are far better draft targets than the Vlads and Eloys of the world.

So what about pitchers? In general, I like to invest in rookie pitchers that are pitching well and try to flip them near the deadline for guys who will pitch down the stretch. Yes, you might have to take a discount for them, but in H2H leagues compiling the best roster for the playoffs is your end goal. Guys like Jake Faria and Luis Castillo were far less impactful in last season’s playoffs than pitchers like Trevor Bauer, Mike Leake, and CC Sabathia. The latter names are not pretty, but pretty doesn’t win you fantasy championships (which, by the way, doesn’t stop me from drafting Kris Bryant and Kevin Kiermaier in every league of mine. If I got points for best eyes I’d have every league locked up).

In Rotisserie leagues, rookie pitchers are more valuable because you can start them while they are pitching and dispose of them once the innings limit passes in favor of a wire arm. H2H leagues do not afford you this luxury, so be sure to know your league settings heading into the year so you can best strategize how to approach rookies and prospects. Being active on the waiver wire is a crucial aspect of winning a fantasy championship, and understanding how to manage rookies and prospects goes hand-in-hand with that, so stay vigilant for youngsters who can help your team throughout the season.


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Dollar Day Auction Targets for Fantasy Baseball Drafts

The latter part of an auction draft is arguably the most fun part. All of the obvious players to own are long gone, and now owners must go searching through the coal to find the one diamond that will make the difference for their team.

Owners were patting themselves on the back after finding $1 steals like Eric Thames, Yuli Gurriel, Domingo Santana and Drew Pomeranz last season, and now it's time to search for the next batch of draft day steals.

None of these players should go for more than a dollar or two in auction drafts. If someone is bidding them up, it's best to let them go and look for value elsewhere. But if you can get any of them for a dollar, they should become solid contributors to a championship fantasy team.


I'll Buy That For a Dollar!

Scott Schebler (OF, CIN) — $1

Taking over as a full time starter in 2017, Schebler had a breakout year with 30 home runs — third-most for Cincinnati — and a .791 on-base plus slugging percentage — fourth-highest on the team. His batted ball tendencies show that he was hitting more fly balls and fewer ground balls, while also hitting the ball harder than he ever had in his career.

The two biggest concerns for Schebler right now are his low batting average and his lack of a consistent track record. After hitting .265 in 2016, Schebler's average dropped to .233 last season — the lowest of his professional career — although his .248 BABIP does suggest his average will trend upwards this year. At this point there is no guarantee that he will repeat his breakout performance in 2018. But if Schebler can put up similar numbers he could end up being a solid contributor at $1.

German Marquez (SP, COL) — $1

Coors Field and pitchers — two things that to most fantasy owners do not mix. However, Rockies starter German Marquez is worth taking a look at late in auction drafts after he finished fifth in the NL Rookie of the Year race in 2017. Bringing with him a career 7.9 K/9 in the minors, Marquez went 11-7 last year, with a 4.39 ERA and 8.2 K/9 over 162 innings pitched. With a 21 percent strikeout rate and 14 percent strikeout to walk rate, Marquez was ranked among the top 40 qualifying starting pitchers in 2017.

Obviously his 4.39 ERA as well as pitching half the time at Coors Field drops Marquez's value quite a bit. Looking at his 4.40 FIP and 4.18 xFIP doesn't provide much comfort to fantasy owners either. But for those who are looking for strikeout upside and are willing to take a hit on their ERA, Marquez will be a perfect fit for any team at a dollar.

Yonder Alonso (1B, CLE) — $1

Alonso will be a perfect fit at a corner infield spot or as a first baseman for owners who want to wait to draft one. Alonso finished 2017 setting career-highs in several categories with 28 HR, 67 RBI and 72 runs scored to go along with a .266 average and an .866 OPS. While he did post a career-high 22.6 percent strikeout rate, he also posted a career-high 13.1 percent walk rate — his second time in the past three seasons with at least a 10 percent walk rate.

Alonso will prove himself to be most valuable in OBP leagues, as he is a lock for at least a .300 OBP — hitting that mark in six of the past seven years. The big question will be if he can repeat the power display that he showed in 2017. His 28 HR last year matched his home run total from the previous four and a half seasons, and his 19.4 percent HR/FB rate is more than double his career rate of 9.2 percent. But while he will likely see a regression in his home run output, joining the potent Indians lineup that averaged 5.05 runs per game last year — sixth most in MLB — will likely see his runs scored and RBI totals hit career-highs in 2018.  Of the first basemen ranked around Alonso, he probably has the best chance at giving owners the most bang for their buck (maybe two).

Mike Clevinger (SP/RP, CLE) — $3

Yes, he's not technically a "dollar" player, but he's close enough and he has a shot at providing a lot of value to fantasy owners this year. First things first: Indians manager Terry Francona has said that Clevinger will start the season in the rotation. So now that Clevinger has a lock on playing time at least for the start of the season, what does he bring to the table? Last season over 27 appearances and 21 starts for Cleveland, Clevinger compiled a 12-6 record with a 3.11 ERA and 10.1 K/9. Those numbers closely resemble his career line in the minors, where he has a 3.35 ERA and 8.8 K/9 over seven seasons.

All those numbers look good on paper, so what's the catch? Walks. Over 17 games in 2016, Clevinger averaged 4.9 BB/9 and he followed that up by averaging 4.4 BB/9 in 2017. Among pitchers with at least 120 innings pitched last season, Clevinger's walks per nine innings rate was fifth-worst while his 12 percent walk rate was tied for third-worst. At this point though Clevinger has had less than 200 major league innings under his belt. It's not hard to believe that with a full season in Cleveland, Clevinger could improve his command, cut down on the walks and become an absolute steal in auction drafts.

These are just four of the many bargain players out there in auction drafts that can benefit any team. Most dollar players will likely not contribute anything worthwhile in 2018, but those that do can end up being crucial to a team taking home a league championship, and these four guys have a good shot at being those kind of players.


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Using Sabermetrics for Fantasy Baseball Part 14 - Statcast For Pitchers

Previously, we looked at Barrels, a stat combining exit velocity and launch angle to measure how often a batter makes quality hard contact. As much as batters want to hit a Barrel every time, pitchers want to avoid them at all costs. Yet there is some evidence that pitchers do not have the same influence over Barrels as a batter does.

While Aaron Judge led all of baseball last year with 86 Barrels, Rick Porcello led all pitchers by coughing up 52. 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 Porcello's 2016 was a fluke by any predictive metric. Ian Kennedy allowed the second most Barrels with 51, but fantasy owners don't care about him. Matt Moore came in third with 48, but he hasn't been fantasy-relevant in years. Fourth place Ricky Nolasco (46) is bad, and four arms tied for fifth with 45 Barrels allowed. Kevin Gausman, Jason Hammel, and Ariel Miranda are blah, but Gerrit Cole is interesting. Let's start with him.


How to Interpret Batted Ball Statistics

Cole allowed hard contact in 2017, but nothing in his history suggested that he would before the season started. In 2016, he allowed only 11 Barrels all season. In 2015, he allowed 26. Cole's high number of Barrels allowed may partially explain why he disappointed his fantasy owners last year, but his Barrels allowed look like they came out of a random number generator. There's nothing predictive here.

The rate stat, Brls/BBE, might seem like a better option. Jered Weaver tied for the league lead in rate of Barrels allowed with 11.8%, and he's obviously terrible. The person he tied with was Craig Kimbrel, one of the best relievers in baseball.

The Barrels hardly hurt Kimbrel's final stat line, as he posted an elite 1.43 ERA (1.50 xFIP) with 35 saves last season. Kimbrel had previously been great by Brls/BBE, posting a 5.8% mark in 2016 and 4.7% in 2015, so nothing in his track record should have raised a red flag. Indeed, there's no need for a red flag even in retrospect.

Maybe we need to simplify this and just use average airborne exit velocity? Cesar Valdez (97.2 mph), Sam Dyson (96.1 mph), Brett Anderson (95.5 mph), Scott Alexander (95.4 mph), and Chasen Shreve (95.3 mph) top this list, but none of them are on the fantasy radar. Nate Karns kind of is (also 95.3 mph), but he didn't really struggle with average airborne exit velocity in 2016 (93.3 mph) or 2015 (92.6). Again, there is nothing predictive about these Statcast metrics.

Last year's version of this article cited Chris Archer and Justin Verlander as case studies for the value of these metrics. Archer under-performed his peripheral stats in 2016, posting a 4.02 ERA against a 3.41 xFIP. I speculated that the quality of contact he allowed (46 Barrels, 8.4% Brls/BBE) may be the reason why. Last season proved this to not be the case, as Archer improved both Statcast metrics (29 Barrels, 5.4% Brls/BBE) while still posting an ERA (4.07) above his xFIP (3.35). Archer has some kind of issue, but Statcast metrics are not the way to quantify it.

Likewise, Verlander's 2016 xFIP (3.78) was considerably above his ERA (3.04). He allowed a ton of Barrels (45) and a high rate of Brls/BBE (7.7%), metrics I used to forecast regression. Nothing changed in 2017, as he again allowed a ton of Barrels (40, 7.2% rate of Brls/BBE) while posting an ERA better than his xFIP (3.36 vs. 4.17). The statistics seem to have been proven worthless in both cases.

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. Every fantasy analyst uses contact quality to credit or penalize pitchers, either through the Statcast numbers above or an approximation such as Hard%. 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. Score it as a win for DIPS theory.


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Using Sabermetrics For Fantasy Baseball Part 13 - 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 and what you want from the arm in question. Let's start with fastballs.

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 compliment their whiffs.

For example, Yu Darvish's 4-seam fastball averaged 2,500 RPM in 2017. Its 10.7% SwStr% was elite 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 (40.3% FB%) and a very high IFFB% (26.6%), suggesting that it produces pop-ups as expected as well.

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. Mike Minor was a good example of this last year.

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 than their high-spin counterparts.

There are fewer examples of this type of arm, but Mike Montgomery's 2017 season provides a good illustration. His 4-seamer averaged 1,841 RPM last year, producing a GB% of 59.8%. Montgomery's ERA (3.38) was significantly better than his xFIP (4.35), but his low spin rate suggests that he can continue to beat his traditional indicators and be a nice volume arm in fantasy.

Therefore, high and low spin rates are both good for fastballs. You want to avoid pitchers with average fastball spin rates, as they lend themselves to neither strikeouts nor weak ground balls. For example, we saw Robbie Ray get considerably better last year by abandoning his sinker. It averaged 2,268 RPM in 2016, preventing it from contributing Ks (6.7% SwStr%) or weak contact (46.5% GB%, but .422 BABIP). Hitters have slaughtered the pitch for a .332/.389/.494 line over Ray's career, so 2016 was not a fluke. Pitches like this don't help fantasy owners at all.

Unlike fastballs, changeups usually want a low spin rate to maximize how much they move. For instance, a change is Chris Devenski's signature pitch. Last season, it posted a 24.5% SwStr%, 40.3% Zone%, and 46.3% chase rate--all excellent numbers.

The reason why is spin rate. It averaged 1,514 RPM last year, 492nd in MLB among changeups. To put that number into perspective, R.A. Dickey's knuckleball--a pitch defined by its lack of spin--averaged 1,533 RPM last year. This low spin rate helps Devenski's change move so much that batters can't follow it, often making them look foolish at the plate.

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.

Finally, 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 or the baseball ends up. Sadly, there is currently no way to separate this useless spin from useful backspin or topspin, meaning that spin rate can lie to you.

This means 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 (Darvish's 4-seamer, Devenski's change) or if it was probably a fluke.



To sum up, spin rate is measured in RPM. Fastballs are good with high or low spin rates, but the area in between offers no benefit. 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, useless spin can distort spin rate readings, meaning that you should always combine spin rate with other metrics in your analysis.

Next time, we'll take a look at what Statcast metrics such as Barrels and average exit velocity mean for pitchers.


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Using Sabermetrics For Fantasy Baseball Part 12 - 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 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.

In this article, we'll look at how to effectively use this data to give you an edge in your fantasy baseball league throughout the season.


How to Interpret Pitch Info Data

The first data point, and the easiest 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, Mike Minor shifted to a relief role and increased his average fastball velocity from 91.8 mph over his career to 95 mph last season, striking out more batters (21.5% career K% to 28.7% last year) as a result. His overall effectiveness benefited immensely (2.55 ERA vs. 3.93 career).

The average major league heater was 92.8 mph in 2017, though of course a pitcher's established baseline is a better indicator of future performance. Other variables like movement and location also matter, but velocity is a good introduction to using Pitch Info data.

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% or BABIP, 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.

For example, consider Robbie Ray. His K% increased last year relative to 2016, 28.1% to 32.8%. His BABIP declined in the same time frame, from .352 in 2016 to .267 last season. Are these numbers the result of random fluctuation, or did Ray change his pitch selection to bring them about?

Pitch Info tracks each pitch's individual results, so any change in pitch selection can be evaluated by comparing an offering's usage percentage and its performance, in this case SwStr% and triple slash line against.

The biggest change in Ray's pitch selection was that he threw fewer sinkers (from 19.4% to 3.6%) in favor of curves (5.5% to 20.5%) relative to 2016. Ray's sinker had a SwStr% of just 6.7% in 2016, so it wasn't generating many whiffs at all. Ray's curve posted an excellent 18.4% SwStr% last season, providing plenty of evidence that his K% surge was real.

Ray's curve also outperformed his slider when put into play. Ray's sinker was crushed in 2016 (.382/.437/.581), likely serving as the primary culprit for his elevated overall BABIP. By contrast, opposing batters could do virtually nothing with Ray's curve last year (.188/.259/.267). Ray's change in pitch mix seems to support his BABIP improvement too.

That said, there is a price to pay for everything. Ray's sinker was a strike more than half of the time in 2016, posting a Zone% of 52.6%. Ray's curve is almost never a strike (36.2% Zone%), relying instead on hitters chasing it out of the zone (38.7% chase rate). The result was fewer strikes and a higher BB% (10.7% vs. 9.2% in 2016). Still, the change was a net benefit for Ray's fantasy value.

The same type of analysis may be performed for a number of other stats, including 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. Let's have some fun with our example and look at Clayton Kershaw's arsenal.

Kershaw threw five different pitches in 2017: a fastball 46.6% of the time, a slider 34.3% of the time, a curve 16.7% of the time, a sinker 1.2% of the time, and a change 1.2% of the time. The sinker and change were thrown 29 times each over the entire season, so they were probably recording errors or pitches that accidentally slipped out of Kershaw's hand. Regardless, the sample size is too small to consider them in this discussion, leaving three offerings for our analysis.

His fastball registered a Zone% of 55.6% last season, slightly better than average. It recorded a solid 6.6% SwStr% despite living in the zone, allowing batters to hit .255/.287/.455 against it. It was a good pitch, but not enough to make Kershaw the icon he is.

That is what the slider is for. It was only a strike 33.7% of the time, but compensated by making hitters chase it at a whopping 47.6% clip. That helped give it a SwStr% of 24.4%, absolutely obliterating the league's 10.5% SwStr% rate and explaining how Kershaw compiles so many Ks.

Kershaw also has a curveball. It was a strike slightly more often than the slider at 37%, but posted a lower O-Swing% of 38.7%. This gave it a SwStr% of 14.3%--very good, but inferior to Kershaw's slider. Why throw it?

Sometimes, hitters actually put the ball in play. Batters managed a triple slash line of only .149/.155/.327 against Kershaw's curveball in 2017, compared to .207/.258/.277 against the slider and .255/.287/.455 against the heater. All three are well above average, and Kershaw's arsenal is an embarrassment of riches if there ever was one. He's fun to look at, but he can't be a baseline.

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 29.9% in 2017, and most good wipeout-type pitches need to beat this number substantially. The overall Zone% was 45%, including pitches like splitters in the dirt and high fastballs that were never intended as strikes.

The fastball will always be inferior in results to pitches that do not need to live in the strike zone, like Kershaw's slider, 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 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 in the strike zone, but get 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 fastball or cutter to be the strike zone pitch in a pitcher's repertoire.

Personally, I like a 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 15% and an O-Swing% of 40%. Ideally, there is a secondary K pitch, like Kershaw's curve, that prevents the 0-2 pitch 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. The next entry in this series will discuss another variable to consider when determining the potential of a pitcher's repertoire: spin rate.


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Ottoneu Draft Strategy

Ottoneu is a format that only the fantasy baseball obsessed know about. For years I’ve been eyeing an Ottoneu league but was hesitant to take the plunge; the massive rosters, complex scoring system and year-round commitment were overwhelming, to say the least. But this year I’m ready to make the leap, having signed on with some fellow Rotoballers for what promises to be a fun but intense ride.

With that out of the way, it’s important to be mindful that Ottoneu is not just another standard fantasy game. The format is quite different than your average rotisserie or points league and requires some specialized planning, especially in advance of your inaugural draft.

If you're ready to dip your toe in the waters of an Ottoneu league for the first time yourself, here are some guidelines you might find useful.


First things first - know the rules

Before you even begin to look at the player pool you need to know exactly how Ottoneu works and how it can differ from the formats you’re used to playing. There are several scoring setups used in Ottoneu, so whether your league uses standard 5x5 roto categories, 4x4 ‘sabermetric’ categories or one of two points variations your overall draft strategy will change dramatically.

Standard 5x5 speaks for itself, but the 4x4 variation eschews traditional stats like batting average, stolen bases and RBI and replaces them with on-base percentage and slugging percentage (runs and home runs remain in tact). Without the inclusion of thefts, one-category speed superstars like Billy Hamilton become almost useless while the Matt Carpenters and Carlos Santanas see a boost due to their ability to get on base via the walk and hit for some power.

The two points systems are mostly the same for hitters but there are some differences for pitchers. In the FanGraphs points system, pitchers are penalized for hits allowed, which more closely mirrors real life performance. The SABR points format - the original points system - uses a FIP-based scoring system, essentially focusing as much as possible on metrics that reflect the true skill level of pitchers.

These various scoring formats will significantly alter the way you value players. Unless you’re using the standard 5x5 setup, you might as well throw your regular rankings out the window. The Ottoneu-specific scoring formats will require you to do a little more research. The platform itself has a great resource that spits out average salaries by game type (auction drafts are the only option, by the way), so that would certainly be a great starting point to build your rankings.

Just as important as the scoring system is the roster setup. Ottoneu uses a large 40-man roster with 22 starting spots: one catcher; standard infield plus one middle infield slot; five outfielders; one utility; five starting pitchers and five relievers. That leaves 18 bench spots to fill however you please.

This is where the strategy comes into play.

Assuming you’ve done your homework on the rules and player values, your focus should now be on how to get the most out of your 22 starting slots. Here are some things to consider:


Maximize quality innings

Unlike some standard games, Ottoneu prevents managers from loading up on relievers or utilizing starters with RP eligibility, so you have to be strategic with how you fill out your pitching staff. Also factoring into the equation are the innings thresholds: teams cannot exceed 1500 innings pitched in all formats, while 4x4 leagues have a minimum of 1250 IP managers are forced to reach. Grabbing a few reliable arms is a must. While you don’t necessarily need to break the bank for one of the four top tier aces (Clayton Kershaw, Max Scherzer, Chris Sale or Corey Kluber) be prepared to spend some dough on the next couple of SP tiers to solidify your rotation and set a solid base for your 1500 innings. Ideally you want to max these out with as many quality innings as possible, so getting lots of mileage out of your relievers is also key. But spending big on name brand closers isn’t the only way to do that. Anthony Swarzak is far from a household name but but he threw 77.1 innings last season with a 2.33 ERA and 2.74 FIP while striking out 10.59 batters per nine. Chad Green threw a dominant 69 innings with a 1.83 ERA, 1.75 FIP and 13.43 K/9. Neither option is likely to cost a lot but both would help lock in some great ratios while piling up the strikeouts.

Take advantage of daily lineups

Some leagues only allow you to set your lineups once at the beginning of the week but Ottoneu is for the hardcore, allowing you to tinker with your lineup on a daily basis. This requires a much bigger time investment, but if you’re willing and able it can pay huge dividends. That’s because you can now play the matchup game. A prime opportunity to do this is in the outfield. While others are busy filling out their five OF slots early, you can potentially wait on your last couple of outfielders and grab some players with platoon splits who you can plug and play depending on the daily matchups. The five outfield slots cannot exceed 810 total games played (each hitter slot is limited to 162 games) so there’s a certain degree of mixing and matching possible. Hunter Renfroe posted a downright unplayable .202/.244/.393 line versus righties last season but mashed lefties to the tune of .316/.392/.684 in 61 games. Pair him and another lefty killer like Adam Duvall (.279/.352/.571) with a Josh Reddick (.314/.363/.504 versus righties) and you’ve got yourself a little more than an outfielder and a half’s worth of your roster filled with strong peripherals. Players like these tend to see their overall stat lines muted because of their performances against same-handed pitchers and can often be had for cheap. Use this to your advantage.

Don’t overpay for hot prospects

I know, it’s tantalizing to go the extra few bucks on this year’s hot prospect. But for the most part, everything has to break right for these players to return value in the short term. The opportunity cost of reaching for players who are not MLB-ready is high. You will often pass up on players who can help your team now for guys who are at risk of struggling or even being demoted. Balancing the present and the future is a tough assignment, but there will always be new prospects flooding the player pool every year. When other managers are fighting over Ronald Acuna, Victor Robles or Shohei Ohtani, save your dollars for the underappreciated veterans that are sure to slip through the cracks as a result, like Adrian Beltre or Jeff Samardijza. Remember that a guy like Acuna was barely even on the radar as recently as a year ago. Do some research and take a gamble on the next high-rising prospect before he becomes a household name. You’ll pay a lot less and the risk is minimal. Plus, you’ll look like a genius when he vaults to the top of the prospect list next year.

Ottoneu is not for the faint of heart, but if you’re someone who obsesses over draft preparation and lineup optimization, this could be your thing. Sign up on Fangraphs and give it a try!


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Best Ball Sleepers and Late Round Targets for Fantasy Baseball

Best ball leagues are one of the latest variations of fantasy baseball that are quickly growing in popularity. Draft day is the only day of the year where owners will have control over their roster. There is no waiver wire and there are no trades. Owners won't even set daily lineups, as they will instead be chosen automatically by computer. With this added emphasis on having a successful draft in order to have a chance at winning, finding sleepers who will come through in a big way for your team is absolutely crucial.

As mentioned earlier this week in our Best Ball draft strategy overview, consistency in both health and on-field performance will be key to winning in a Best Ball league. Going down this list, we will take a look at one player from each position who has displayed that consistency over the course of several seasons and can be picked up late in drafts.

While these players may not have as high a ceiling as those ranked and drafted ahead of them, they also don't have as low of a floor, which could mean the difference between first place and tenth place in 2018.


Best Ball Sleepers and Draft Targets

Catcher: Yasmani Grandal—ADP 225

Let's play a game. Here are the 2017 stat lines for a pair of catchers:

Player A 129 50 22 58 .247 .308 .459
Player B 129 57 27 80 .268 .297 .495

Player A currently has an ADP of 225, while Player B has an ADP of 97. If you want to wait to draft a catcher, then you might want to pass on Player B — Salvador Perez — and instead pick up Player A — Yasmani Grandal. Since becoming a starter in 2014, Grandal has averaged 124 games per year, with 20 home runs, a .234 batting average and a .768 on-base plus slugging percentage. Grandal set career-highs in 2017 with 108 hits, 27 doubles and 201 total bases, and this uptick in production combined with his already established consistency could point to Grandal being one of the bigger steals in Best Ball drafts this season.

First Base: Ian Desmond—ADP 112

A hand injury followed by a lingering hamstring injury derailed Desmond's 2017 season, as he appeared in only 95 games. Despite that, he was still able to put up decent numbers, stealing 15 bases for the seventh time in his last eight seasons while hitting .274 with seven HR and a .701 OPS. Now that he has had the off season to recover, he should rebound and outperform where he is currently being drafted. From 2012 to 2016, Desmond averaged 151 games per season with 80 runs, 22 HR, 78 RBI and 20 stolen bases. In 2017, there were three first basemen who had at least 80 runs, 20 HR, 75 RBI and 10 stolen bases: Paul Goldschmidt, Edwin Encarnacion and Cody Bellinger. Of those three, only Goldschmidt had at least 15 steals.

Desmond won't put up as high of numbers in some categories as Goldschmidt, Encarnacion and Bellinger, but he can put up numbers that are comparable to theirs. With an ADP of 55 or more picks lower than those three, he could be a significant bargain that allows you to focus on other positions early on in your draft.

Second Base: Ian Kinsler—ADP 187

After spending the last four seasons in Detroit, Kinsler makes his return to the AL West in 2018 as he joins an Angels team looking to take the next step towards a postseason run. While he posted a .236 average and .725 OPS in 2017 — both career-worsts — Kinsler was still able to hit 22 HR and scored 90 runs for the fourth straight season. What's impressive about that is that based on advanced metrics, Kinsler was very unlucky at the plate last year. His .244 BABIP was significantly lower than his career mark of .286, and with negligible changes in his batted ball and contact percentages across the board, signs point to Kinsler rebounding back to number closer to his career averages in 2018. Kinsler has averaged 100 runs, 20 HR and 13 steals with a .275 average and .764 OPS since 2014. Returning back to those numbers in 2018 will cause Kinsler to easily provide more value than his current ADP of 187 suggests.

Third Base: Kyle Seager—ADP 139

Out of everyone on this list, Kyle Seager is probably the most consistent player that owners should look at taking late in a Best Ball draft. Since 2012, Seager has played in 155 games every season except last year when he appeared in only 154. Since 2014, Seager has had at least 70 runs, 25 doubles, 25 HR, 74 RBI and an OPS of .770 or higher. 2017 was the first year of his career in which he did not hit at least .250 — he hit .249. Like Kinsler, Seager's .262 BABIP in 2017 was down from his career .285 BABIP, and it was also the lowest of his career. There really isn't much more to say about Seager. His consistency will likely make him the late round pick that contributes the most to a team's success in 2018.

Shortstop: Elvis Andrus—ADP 59

Andrus isn't as much of a sleeper as others on this list — his ADP of 59 is the highest of anyone on this list — but he makes this list because he can put up numbers as good or better than the four shortstops being drafted 20 or more picks ahead of him. Andrus has at least 20 steals every year of his career, has never hit below .250 and averaged 81 runs and 60 RBI from 2011 through 2016. These numbers are all reasons to own Andrus, but what is most intriguing is the potential he showed at the plate last season.

After reportedly making some adjustments to his batting stance prior to the 2017 season, Andrus set career-highs across the board with 100 runs, 44 doubles, 20 HR (his first season with double-digit home runs) and 88 RBI, while posting an .800 OPS for the second year in a row. It remains to be seen if he will even come close to matching his 2017 campaign, but based on what is known he can do along with the potential he displayed last year, Andrus is worth waiting on to draft as your starting shortstop.

Outfield: Jay Bruce—ADP 161

Selecting Bruce on draft day will likely not get any attention from your opponents. You probably won't have owners complimenting you on a smart pick or complaining that you sniped him just before they could take him. But what drafting Bruce will do is pad your stats in all the right places for a low cost. This is what he has done in six of the last seven seasons: Hit 25 HR and 25 doubles, drive in 85 runs and record an .800 OPS. In 2017 there were only 10 outfielders besides Bruce to put up those numbers, and Bruce is the only one of those who currently has an ADP placing him outside of the first 10 rounds. Drafting Bruce will give you high-end production at a bargain price, and that is the kind of investment you need to look for in a Best Ball league.

Pitcher: Jose Quintana—ADP 72

With 161 starts, Quintana is one of six pitchers to start at least 160 games since 2013 — only Max Scherzer and Jeff Samardzija have started more games during that time. Quintana has averaged 201 innings and 181 strikeouts with a 3.50 ERA over that span, and has also put together an 8.1 K/9 rate. While Quintana has been consistent with 32 starts, 185 innings and 175 strikeouts in each of the last four seasons, what's intriguing about him is that he could be improving. Starting off last season with the White Sox, Quintana was striking out batters at a higher rate than previously in his career. After his trade to the Cubs, not only did he strike out batters at an even higher rate (10.5 K/9 with the Cubs vs 9.4 K/9 with the White Sox) but both his ERA and FIP dropped more than 70 points. Quintana was already a good pitcher to draft in any league, but with his track record and the potential he showed in the second half, he could be on his way to becoming a borderline top 10 starting pitcher.

Each one of these players has shown that they can put up the same numbers year in and year out. Take advantage of their consistency in your drafts, as all of these players will be more valuable in a Best Ball league than in other leagues, and other owners may not realize that come draft day. Players like Mike Trout, Clayton Kershaw and Giancarlo Stanton will carry your team, but it's the players on this list that can make the difference between finishing first or second in your league.


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Points League Primer - Fantasy Baseball Draft Strategy

When discussing fantasy baseball, an often neglected but entertaining format is the points league. These exist in both season-long cumulative and weekly head-to-head leagues.

While existential debates about scoring categories and their true depiction of player worth are endless, points leagues arguably get closest to the objective of sabermetrics. Points leagues attempt to define a player's contribution (or detraction) in greater depth. For example, we know a triple is more valuable than a single and these leagues acknowledge that.

The fundamentals are the same, but there are some unique strategies associated with points leagues that you may want to be acquainted with before you draft. Without further ado, here is your 2018 Points League Primer for fantasy baseball.


How to Win Your Points League

There is a high degree of overlap with standard leagues, but the below table illustrates an overview of this scoring system. We'll discuss four primary difference that could alter a manager's strategy on draft day and during the season.

Note weights and categories differ by league. Some leagues overweight wins or underemphasize saves. Others might have additional categories like quality starts or HRs allowed. Since this is a basic outline, we'll operate under our assumptions but remember to check the settings of your particular league.


1) Strikeouts and Walks Matter

Hitting-wise, in common leagues, a strikeout is a non-event and a hitter only receives indirect credit for a walk if he tallies an RBI or eventually scores. Points leagues instantly gratify hitters for getting on base, which is the essence of offense. Likewise, since a hitter is wholly responsible for striking out, he is punished.

A key unique metric in points leagues is BB/K. Out of 144 qualified hitters in 2017, the median BB/K was 0.48. Joey Votto was an elite outlier at 1.61 and the poorest was Tim Anderson at 0.08. Even though Matt Carpenter struck out at a 20.1% clip last season, his 17.5% walk rate gave him the ninth best 0.87 BB/K. On the flipside, although Rougned Odor was considered a bust in standard leagues, in points leagues he suffered massive value destruction with 162 strikeouts and only 32 walks. Despite 30 HR, the feeble BB/K just wasn't worth the trade-off.

Earning walks skews a player's value positively, Votto was a top-five player in points leagues but finished lower in standard leagues. Carpenter, Kris Bryant, and Shin-Soo Choo were walk-friendly players that saw better year-end ranks in points leagues relative to standard formats. Owners targeting players around 0.50 BB/K or better will enjoy a positive benefit from drafting patient hitters.

Since there is a positive relationship between strikeouts and slugging, managers should also analyze the strikeout in exchange for earning points via power.


2) Slugging is More Important than Average

An important consideration in points leagues is a player's slugging ability. Instead of treating all hits equally as AVG does, netting points for total bases rewards hitting for power.

Jose Ramirez hit 56 doubles and six triples in 2017. These contributions went ignored in standard leagues. Because of his high average and HR production, Ramirez' value in points leagues just barely surpassed his rank in standard ones. Meanwhile, Francisco Lindor (.273 AVG, 48 doubles+triples), Nicholas Castellanos (.272, 46) and Xander Bogaerts (.273, 38) were all significantly more valuable from a total bases standpoint. Even replacement-level guys like Cesar Hernandez and Denard Span received large bumps in relevance from their non-HR slugging.

Incorporating walks, slugging and BB/K complements AVG and HR, painting a better picture of a player's true worth. Since wOBA isn't a fantasy stat (yet), points leagues get us close to that representation.


3) Pitching Stamina Helps, Losses Hurt

Pitcher durability is a key ingredient to strikeouts, ERA and WHIP. More innings pitched means increased chances to rack up Ks and achieve a steady state in ratios. In points leagues, rate stats are converted into counting stats by penalizing earned runs and walks. Pitchers also receive points for each inning recorded. It's vital to consider IP alongside standard measurements like K/9, especially when innings limits are concerned

Despite a disappointing 3.64 ERA and 1.22 WHIP for Carlos Martinez in 2017, his fifth best 205.0 IP buoyed his value in points leagues. The theme rings true for Gerrit Cole and Chris Archer. These three players had disappointing ERA and WHIP, but their strikeout prowess was greatly complemented by piling on innings. Conversely, while Julio Teheran and Ivan Nova are not strikeout artists, their durability made them relatively more relevant in points leagues. Even Clayton Richard with his ugly 4.79 ERA and 1.52 WHIP held some worth simply due to his 197.1 IP.

Losses are also significantly detrimental. In standard leagues, you either win or you don't. In points leagues, a pitcher's team is critical even while evaluating his individual ability. Players like Jeff Samardzija and Mike Foltynewicz suffered from playing on bad teams despite serviceable seasons last year. Getting tagged with losses can negate otherwise strong starts by pitchers and is a much more meaningful swing factor than just wins.


4) Scoring is Category-Agnostic

All fantasy managers are trained to draft a balanced team to address our 5x5 needs. In points leagues, that is irrelevant. A double is worth as much as a steal, and five strikeouts count the same as a win. Buck the traditional mentality, take stats where you can find them.

Points leagues have the unique characteristic of allowing managers to evaluate players on their overall body of work as opposed to select niche areas. A simple comparison covers doubles and stolen bases. In 2017, there were 8,397 doubles hit and 2,527 steals in the majors. For steals, standard leagues owners are fighting for share in a commodity that is getting scarcer. In points leagues, the argument is to just ignore steals and accumulate stats where there is excess supply like doubles and homers. There's no harm in rostering a squad of sloths.



Points leagues show considerable overlap with standard leagues. It's still just baseball. But, they better-represent the evolving appreciation of advanced statistics. It creates depth in a player's profile (i.e. walks, triples, innings pitched) and more closely embodies the real value of that player on the diamond. Customization is another perk of points leagues. Categories and their corresponding weights are discretionary, so it gives leagues more flexibility in determining which stats they value.

In my experience, points leagues are more challenging and require extra strategy, but hopefully that's why we all play the game in the first place!


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Using Sabermetrics For Fantasy Baseball Part 11 - Batted Ball Distribution For Pitchers

The league average batted ball distribution in 2017 was 20.3% liners, 44.2% grounders and 35.5% flies. We have previously seen how pitchers may specialize in either grounders or fly balls.

Fly ball pitchers have a BABIP advantage over their ground ball-inducing counterparts, since fly balls (.130 BABIP in 2017) consistently have lower BABIPs than worm killers (.241). Yet most fantasy owners prefer to roster ground ball pitchers to the point that GB% is frequently cited as a peripheral stat to determine fantasy viability.

Let's get to it!


How to Interpret Pitcher Batted Ball Distribution

The reason for this is slugging percentage. Fly balls had a collective .751 slugging percentage in 2017 despite the lower BABIP, while grounders had just a .262 SLG. As Giancarlo Stanton hits more home runs than most in part by elevating the ball more frequently, fly ball pitchers are liable to give more up by allowing more airborne baseballs. Fantasy owners can live with the odd single through the infield if it means fewer homers allowed.

This line of thinking makes intuitive sense, but I feel it may be overstated at times. Good fly ball pitchers tend to post HR/FB rates a little better than the league average, somewhat limiting the long balls they allow. A pitcher's home park may also help suppress home runs allowed. Once dingers are under control, a fly ball pitcher actually offers several advantages over a ground ball specialist.

For example, fantasy owners may reap the benefits of a lower WHIP by investing in a pitcher that makes his living in the air. If the ball leaves the yard, a fly ball pitcher also has a greater probability of it being a solo shot instead of having to watch a crooked number go up on the scoreboard.

Last season, Minnesota's Ervin Santana was an excellent example of an effective fly ball fantasy pitcher. He posted a 3.28 ERA and 1.13 WHIP thanks to a .245 BABIP that seems way too low to sustain. Yet his 42.5% FB% predisposes him to limiting BABIP, and he induces pop-ups at an above average rate (12.2% IFFB% last year). He can be a little homer prone when he is off his game, but his 11.8% HR/FB was significantly lower than the league's mark (13.7%). Santana's fly ball game is effective even in a neutral park.

To be clear, pitchers in homer-happy locations such as Milwaukee's Miller Park, Yankee Stadium, and Guaranteed Rate Field in Chicago should absolutely be ground ball guys if they are rostered in fantasy. It is also a useful metric to look at when trying to determine if a given pitcher should be active for a road start at these locations. Still, a high GB% alone should not make a guy fantasy relevant.

A specialty in either grounders or flies may allow a pitcher to maximize the team behind him and beat FIP. For example, we already saw how a guy like Byron Buxton can use his defensive prowess to help his team's pitchers suppress BABIP. In fact, Santana's .103 BABIP on fly balls last season was probably at least partially attributable to Buxton's exceptional range.

Buxton helped teammate Tyler Duffey too, as his fly balls allowed posted a .100 BABIP last year. Yet Duffey's overall .326 BABIP was nowhere near as good as his teammate's. The reason is Duffey's FB%, which was only 31.4% last year. He does not use Buxton's platinum glove as effectively as Santana does, and would likely benefit more from an elite infielder instead.

It should be noted that there are some limitations with this kind of analysis. Much like offensive support, defensive support can vary from pitcher to pitcher even if they have the same players behind them. It is a useful piece of the puzzle, but should never be the only thing you look at.

Research also indicates that extreme pitchers gain a small platoon advantage against like bats, so GB pitcher vs. GB hitter favors the pitcher. The effect isn't quite as large as the more traditional handedness platoon split, and is tough to use in weekly formats or daily leagues that cap transactions. Still, it can be useful for DFS and may be cited as a reason to avoid pitchers with an average batted ball distribution.



Both ground ball and fly ball specialists have their uses in fantasy. Ground ball specialists offer lower slugging percentages against and can take full advantage of an elite defensive infield. Fly ball specialists offer superior WHIP and make the best use of an elite defensive outfield. Both gain a minor platoon advantage against hitters that share their specialization, an advantage never enjoyed by arms with no particular tendency. Next time, we'll look at a tool that can forecast and confirm spikes in everything from GB% to K%: Pitch Info.


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