Statcast’s use of expected stats can be helpful in evaluating a player’s performance. Expected Batting Average (xBA) is a statcast metric that measures the probability that a batted ball will become a hit. Every batted ball is assigned an xBA on comparable hit balls in terms of exit velocity, launch angle, and sprint speed on topped or weakly hit balls.
Each batted ball is assigned that xBA based on the factors mentioned in the previous paragraph. Using the expected outcomes of each player’s batted ball helps form their season-long xBA. Strikeout totals are factored into the equation, resulting in a player’s overall Expected Batting Average.
A player’s xBA for the season is calculated by taking the sum of all xBA from individual batted ball events. The sum is then divided by all batted ball events. After that, strikeouts are factored in, which results in a season-long Expected Batting Average.
Expected Batting Average can help give us a better picture of a player’s true skill level than batting average itself. xBA removes defense from the equation, meaning the results are based more on the hitter’s skill level. Because hitters can influence exit velocity and launch angle to an extent, xBA is useful. Once the ball leaves the bat, a hitter cannot control the outcome.
Many were quick to point out early in the season that the unknowns with the baseballs led to some wonky expected stats. Throughout the season, numbers have stabilized, though. League-wide batting average sits at .242, while xBA is .255.
Statcast Expected Batting Average Overperformers
Using statcast and looking at expected stats can give us an idea of some players that could see regression soon. It is worth noting that some players will constantly run high expected stats and are consistent overperformers. But I have compiled a list of the top-ten overperformers according to statcast and will discuss whether I believe regression is coming for several of these hitters.
| Player | Team | BA | xBA | Diff |
|---|---|---|---|---|
| Paul Goldschmidt | STL | .340 | .284 | .056 |
| Luis Gonzalez | SF | .302 | .251 | .051 |
| Xander Bogaerts | BOS | .318 | .271 | .047 |
| Manny Machado | SD | .318 | .277 | .041 |
| Juan Yepez | STL | .281 | .241 | .040 |
| Luis Arraez | MIN | .348 | .309 | .039 |
| Jeff McNeil | NYM | .318 | .279 | .039 |
| Michael Taylor | KC | .274 | .236 | .038 |
| Josh Rojas | ARI | .268 | .230 | .038 |
| Brendan Donovan | STL | .295 | .258 | .037 |
Paul Goldschmidt, 1B, St. Louis Cardinals
Paul Goldschmidt has been one of the best hitters in all of baseball this year and checks in at number two among all players on the Razzball Player Rater for Fantasy. He currently checks in with a .340/.422/.620 slash line with 19 home runs and three stolen bases. Despite nearing 35 years old, Goldschmidt is performing as he did in his prime. His statcast expected batting average suggests regression could be coming, but what does the rest of his profile offer?
It does not seem likely that Goldschmidt will keep this torrid pace, but that is okay. His prior career-best batting average of .321 came in 2015. He is also carrying a career-best slugging percentage and ISO. A large part of Goldschmidt’s batting average is thanks to his .390 BABIP.
Goldschmidt is making consistent contact, and the quality of contact is excellent as well. His zone contact is the best of his career, and all of Goldschmidt’s quality of contact metrics rank very well.
Goldschmidt likely does not sustain a .340 batting average throughout the rest of 2022. Even with some regression and a potential .290 batting average rest of the season, Goldschmidt would still finish the season with a batting average between .315 and .320.
Xander Bogaerts, SS, Boston Red Sox
Xander Bogaerts has done Xander Bogaerts things this season. He has posted a high batting average which he has historically done with average game power. During the Red Sox game tonight, he hit his 7th home run of the season. It was his first home run since June 3, over one month ago.
Much like Goldschmidt, Bogaerts’ batting average has been fueled by a high BABIP at .389. His expected batting average checks in at .271, but Bogaerts has been a consistent xBA overperformer. His highest career xBA was .280, which was last season.
Bogaerts’ contact quality is not quite the level of Goldschmidt, but you can expect a solid performance rest of the season. His consistent line-drive rate plus strong contact rates give Bogaerts the ability to sustain high batting averages and consistently outperform his xBA, which is likely drug down by his lack of hard-hit balls.
Manny Machado, 3B, San Diego Padres
Manny Machado has been stellar this season but checks in as the fourth-highest xBA overperformer. Is there concern for his performance the rest of the way? I don’t think so.
Machado currently has a .318/.392/.528 slash line with 12 home runs and seven stolen bases. If it were not for an ankle injury that kept him out 11 days, Machado would likely have a higher power/speed output.
But for his batting average, Machado has been inconsistent throughout his career. Since 2016, he has posted batting averages of .294, .259, .297, .256, .304, .278, and then .318 this season. You can see his rolling graph below. Machado has posted solid batting averages every other season, so 2022 is the year for another high batting average. Nothing in Machado’s profile suggests significant batting average regression, so you can expect high-end production moving forward.
Expected stats are not perfect by any means, but hopefully, this article gives you an idea of how to use them and what players could see a change in performance moving forward. But as with any statistic, they are just a small tool in the toolshed and do not make absolute opinions on players based on statcast data. Be sure to head to the FantraxHQ home page to check out all our other great content.
Statistical References: Fangraphs, Baseball Savant