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Using Sabermetrics for Fantasy Baseball: Pitcher Statcast

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

Jorge Soler of the Kansas City Royals finished with a league-leading 70 Barrels hit in 2019. Mike Leake led MLB pitchers by allowing 59, a significantly lower number than Soler's total. Neither performance was an outlier, so it seems to take fewer Barrels to lead pitchers in Barrels given up than it does to lead hitters in Barrels hit. This fits well with DIPS theory, which states that batters can do more to influence batted balls than pitchers can.

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

Editor's Note: Our incredible team of writers received five total writing awards and 13 award nominations by the Fantasy Sports Writers Association, tops in the industry! Congrats to all the award winners and nominees including Best MLB Series, NFL Series, NBA Writer, PGA Writer and Player Notes writer of the year. Be sure to follow their analysis, rankings and advice all year long, and win big with RotoBaller! Read More!

 

How to Interpret Statcast Contact Quality Allowed

Bieber is by far the biggest name on the list above, so let's focus our analysis on him. He allowed his 48 Barrels in 554 batted ball events for a rate of Brls/BBE of 8.7% last season. Back in 2018, Bieber allowed 24 Barrels in 342 batted balls for a Brls/BBE of 7%. These metrics completely contradict the popular perception of him, as he was hit hard in 2018 (4.55 ERA despite 3.30 xFIP) before living up to his peripherals last season (3.28 ERA, 3.23 xFIP). Last season saw Bieber post a 7.2% rate of Brls/BBE despite otherworldly performance in everything else. His Statcast metrics differ from his fantasy line.

Using the Brls/BBE leaderboard might seem like a better bet than raw Barrel totals, but again we find a contradictory example within 2019's top five. David Hess (13.2% Brls/BBE), Jeff Hoffman (12.9%), Erik Swanson (12.3%), and Derek Holland (12.2%) are all obvious fantasy avoids, but Josh Hader (12.6%) is the first RP off of the board in most drafts.

Hader had contributed obscene amounts of strikeouts, saves, and an ERA that starts with a 2 for two straight seasons. His rate of Brls/BBE was slightly elevated in 2018 as well (10.6%), but there's no reason to think that it's predictive of a drop-off considering that Hader has already succeeded with it twice. Hader's ERA ballooned to a still perfectly reasonable 3.79 in less than 20 IP last year, and an elevated 14.7% rate of Brls/BBE didn't stop him from striking out nearly 40% of his opponents. If anything, you should be concerned that his BB% nearly doubled.

Maybe we need to simplify this and just use average airborne exit velocity? Unfortunately, the 2019 leaderboard in average airborne exit velocity is a total dumpster fire: Hess (96 mph), Chad Bettis (95.9 mph), Chad Green (95.6 mph), Felix Hernandez (95.5 mph), and Edwin Jackson (95.4 mph). We don't need Statcast to figure out that we really don't want to roster these guys, making it superfluous at best.

 

Conclusion

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

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




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