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Statcast is a valuable tool for fantasy baseball analysis, and it can be easy to look at a stat called "Expected Batting Average" and blindly use it as your projection. Of course, proper use of these metrics is a little more nuanced than that.
First, a disclaimer: This article is about the "Expected Stats" found on Baseball Savant. It's not about the various "xStats" developed by fantasy analysts such as Mike Podhorzer or used in projection systems such as Ariel Cohen's ATC. Those tools have value, but any attempt at an in-depth analysis would involve far more math than this column is intended for.
Expected Statistics are another stat accessible via the Leaderboards tab on Baseball Savant. You can sort by players (including hitters and pitchers) and by team. With that out of the way, let's begin by identifying what Expected Metrics are and how they work.
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How To Use Statcast's Expected Metrics In Fantasy
The first is xBA, or Expected Batting Average. This statistic is calculated using Hit Probability, itself a stat measuring how often a batted ball with a particular exit velocity and launch angle has been a hit since Statcast was introduced in 2015.
For example, a line drive to the outfield that has historically been a hit 80% of the time counts as 80% of a hit by Hit Probability. xBA is simply a batting average produced using Hit Probability, actual K%, and official ABs. If you play in a traditional 5x5 roto league, this is the xStat you'll probably use the most.
As of January 2019, the Hit Probability formula was modified to include the batter's Statcast Sprint Speed, more accurately representing his ability to beat out a ground ball. The adjustment feels a little light in certain circumstances though, so you may still want to adjust upward for true jackrabbits.
Next up is the Expected Slugging Percentage, or xSLG. It is calculated like xBA, except that each batted ball is weighted according to its probability of being a single, double, triple, or home run instead of just a hit. If your league counts slugging percentage, you might use this stat frequently.
Finally, we have Expected Weighted On Base Average, or xwOBA. It is calculated the same way xSLG is, except real-world walks and HBP are added to the equation. Each result is also assigned a linear weight with more math than the simple multiplication used to calculate the slugging percentage. It offers the most real-world value, but doesn't translate well to fantasy unless you play in a realistic points format.
The principal value of all three metrics is to take both luck and defense (and therefore actual results) out of the picture, allowing a player to be judged solely on his contact quality.
Putting xBA to Work
We'll assume that you play 5x5 roto and stick with the simpler xBA from here on out. Generally speaking, a player who posts a higher xBA than batting average would be expected to improve his average moving forward, while the opposite is true if a player's average is higher than his xBA.
Baseball Savant's Leaderboards allow you to sort players by the difference between their BA and xBA, so finding some samples is easy. The three biggest xBA overachievers of 2023 were:
Jose Altuve is a fantasy mainstay thanks to his high average, but xStats suggest he didn't deserve that reputation last season. His 26.9 ft./sec Statcast Sprint Speed was a smidge below the MLB average of 27.0, so the speed he was once known for is gone, too. His ADP of 38.58 doesn't seem to account for any of this, making him a good fade in 2024.
Nolan Jones had a promising debut for the Rockies last season, but xStats expect him to lose 48 points of batting average before accounting for his strikeout problems. His Sprint Speed of 28.4 ft./sec is high enough to consistently "beat" his xBA, but not by enough to avoid becoming a batting average drag in fantasy. With an ADP of 54.56, Jones is another fade candidate.
Brandon Marsh can run with a Statcast Sprint Speed of 28.6 ft./sec, and he's slated for a platoon role that should help his rate stats. He's also nearly free with an ADP of 414.46, so we don't have to avoid him because of his xBA.
Going the other way, Vladimir Guerrero Jr. posted the best positive differential with a .299 xBA against an actual batting average of .264. Unfortunately, positive batting average regression is already baked into his 31.53 ADP, so it's tough to call him a sleeper. Vladito isn't legging out many hits with his 26.4 ft./sec Statcast Sprint either.
You may be wondering if any of this is predictive. In 2022, the three biggest xBA overachievers were Paul Goldschmidt, Xander Bogaerts, and Jeff McNeil. All three saw their batting averages fall at least 22 points last season, with Goldschmidt personifying a disappointing Cardinals team while McNeil ended up on waivers in most formats. Statcast xStats identified three busts as busts before the season even started.
Pitchers illustrate another problem with xBA. Matt Manning was the "luckiest" pitcher, according to the metric in 2023, posting an xBA of .269 despite a batting average against of .212. The metric doesn't consider the defense behind a pitcher, however, so outstanding glovework could help sustain a gap moving forward. The Tigers were below average defensively last season with -8 OAA, ranking 20th in the league. However, Manning received two OAA while he was on the mound. The best move is to let somebody else take the chance on Manning's "upside."
League wide, major leaguers posted a .248 batting average and expected batting average last year. While exciting, the technology isn't foolproof. It's always best to utilize Statcast Expected Stats as part of a broader analysis, rather than your sole data point.
Conclusion
In summation, Expected Stats allow you to evaluate a player's performance based on his exit velocity and launch angle, taking variables such as opposing defenses out of the calculus. This can give you a better sense of a player's true talent level, but other factors still matter.
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