Statcast xStats: Using Sabermetrics for Fantasy Baseball

Rick Lucks breaks down Statcast Expected Statistics such as Expected Batting Average (xBA) as his series on making sabermetrics more accessible to fantasy managers continues.

Statcast is a valuable tool for fantasy analysis, and it can be easy to look at a stat called "Expected Batting Average" and blindly use it as your projection moving forward. Of course, proper use of these metrics is a little bit more nuanced than that.

First, a disclaimer: This article is about the "Expected Stats" found on Baseball Savant. It is 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 of them would involve far more math than this column is intended to get into.

Expected Statistics is yet 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 the 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 fallen in for a hit since Statcast was introduced in 2015. For example, a line drive to the outfield that has historically fallen in for a hit 80 percent 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 Expected Stat 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. That said, the adjustment feels like it may be too light in certain circumstances, so you may still want to make a slight adjustment upward for true jackrabbits. The metric also seems to underrate the Coors effect on batting average, in this author's experience.

Next up is the Expected Slugging Percentage or xSLG. It is calculated in the same manner as 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 get good use out of this stat.

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. This is the stat with the most real-world value but doesn't translate that 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 the actual batting average would be expected to improve his average moving forward, while the opposite is true if a player's batting 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. Nicky Lopez of the Kansas City Royals was the biggest overachiever in 2021, posting a .300 batting average against am xBA of just .239. Lopez is fast enough that we should expect him to beat his xBA but his figure is so low that he may not be able to repeat his surprising production in 2022. His struggles could also open the door for Bobby Witt Jr. to debut more quickly than expected.

Going the other way, Max Kepler posted the best positive differential with a .255 xBA against an actual batting average of .211. These advanced stats don't understand that certain players are more susceptible than others to the shift, so you should check those numbers before you blindly project improvement. Kepler is shifted nearly every time up and hit just .222 against the traditional shift last year, suggesting that his average will continue to hurt fantasy managers unless he brings his 12 Oppo% on grounders way up.

Pitchers illustrate another problem with xBA. Jack Flaherty of the St. Louis Cardinals was the "luckiest" pitcher according to the metric in 2021, posting an xBA of .248 despite a batting average against of .199. The metric doesn't consider a defense behind a pitcher, however, so outstanding glovework could help sustain such a gap moving forward. The Cardinals led baseball with 49 OAA last season, so at least some of Flaherty's success was based on his teammates rather than luck.

League-wide, major leaguers posted a .244 batting average and .242 xBA in 2021, a two-point differential that had declined in each full year of Statcast's existence before matching 2019's difference last year. This trend suggests that the technology is getting better, but also that it isn't foolproof. It is always best to utilize Statcast Expected Stats as part of a broader analysis, rather than using them as 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 the opposing defense out of the calculus. This can give you a better sense of a player's true talent level, but there are limitations on what you can do with it. Stay tuned for more great advice on how advanced metrics can help you throughout the fantasy baseball season!

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