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:

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.

Conclusion

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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