What Are Statcast xStats? Using Sabermetrics for Fantasy Baseball (2025)

Welcome RotoBallers to our overview of Statcast Expected Statistics (xStats). This article is a deeper dive into xStats and is part of our ongoing series "Using Sabermetrics for Fantasy Baseball."

In this article, we'll explain what Statcast's xStats are and how they work in layman's terms anyone can understand. We'll also look at how well xStats predicted sleepers and busts last season.

You can find our entire sabermetrics glossary, which includes links to many other sabermetric stats as part of this series. Each stat deep dive will be released over the next few days. Stay tuned!

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What Are Statcast's xStats? Sabermetrics Glossary

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 assume it's a projection. Of course, proper use of these metrics is 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 xStats are and how they work.

How To Use Statcast's Expected Metrics In Fantasy

The first is xBA, or Expected Batting Average. This statistic is calculated using Hit Probability, which measures 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 percent of the time counts as 80 percent of a hit by Hit Probability. xBA is simply a batting average produced using Hit Probability, actual K rate, and official at-bats. 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 groundball. The adjustment feels a little light, though, so you may still want to adjust upward for true jackrabbits.

Next up is 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 slugging percentage. It has 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 remove luck and defense (and therefore actual results), allowing a player to be judged solely on his contact quality.

Putting xBA to Work for Hitters

We'll assume you play 5x5 roto and stick with xBA from here on. 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 samples is easy. The three biggest xBA overachievers of 2024 were:

Jose Altuve is a fantasy mainstay thanks to his high average, but xBA suggests he didn't deserve that reputation last season. His 27.1 feet/second Statcast Sprint Speed was right on the MLB average of 27.0, so the speed he was once known for is gone.

Altuve might not deliver the average fantasy managers expect from him this year, especially with the uncertainty of a position switch thrown in.

Perdomo's 27 ft./sec is also average, so we shouldn't expect much from him in fantasy. Tyler Fitzgerald (30 ft./sec, 100th percentile), Connor Wong (28.4, 79th), and Ezequiel Tovar (28.1, 71st) all have the wheels to beat xBA, though probably not by enough to maintain fantasy relevance. Tovar stands out as a fade, considering his horrific plate discipline.

Going the other way, Brandon Drury and MJ Melendez tied for the highest negative differential of -0.o33. However, their xBAs were .202 and .239, respectively, which still isn't that appealing in fantasy.

Vladimir Guerrero Jr. posted the best positive differential in 2023 with a .299 xBA against an actual batting average of .264. He enjoyed a breakout in 2024 with 30 homers and a .323/.396/.544 slash line.

You may be wondering if any of this is predictive. In 2023, xBA identified Altuve, Nolan Jones, and Brandon Marsh as fades. Altuve was outstanding again, but his average slipped from .311 to .295, with the risk for a more significant drop-off as noted above.

Jones had a disastrous 2024 that saw his batting average fall by 70 points. Similarly, Marsh went from .277 in 2023 to .249 in 2024. xBA went three-for-three on potential regression candidates last year while identifying Vladito as a sleeper.

Putting xBA to Work for Pitchers

The "luckiest" pitcher by xBA (minimum 250 PAs) last season was Emmanuel Clase, who posted a .154 batting average against and a .214 xBA. xBA doesn't consider team defense, and Cleveland excelled last season with 11 Outs Above Average (OAA) overall (ninth in MLB) and five with Clase pitching. However, Andres Gimenez and his 21 OAA were shipped to Toronto, so Clase won't receive the same defensive support.

The "unluckiest" pitcher was Camilo Doval, who allowed a .241 average despite an xBA of .187. Doval will probably be better in 2025, though that doesn't mean Ryan Walker will give him the closer's job back.

League-wide, major leaguers posted a .243 batting average and expected batting average last year. While exciting, the technology isn't foolproof. It's always best to utilize Statcast xStats as part of a broader analysis rather than your sole data point.

Conclusion

xStats 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.