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Welcome RotoBallers to our overview of BABIP (batting average on balls in play) for hitters. This article is a deeper dive into BABIP for batters, and is part of our ongoing series "Using Sabermetrics for Fantasy Baseball".
In this article we'll explain what BABIP is, specifically for hitters, and provide a definition that is hopefully easy for anyone to understand. We'll also explain how to utilize BABIP for fantasy baseball and improve your fantasy baseball analysis skills.
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 is BABIP (for Hitters)? Sabermetrics Glossary
The most accessible of the fantasy-relevant advanced stats is BABIP or Batting Average on Balls In Play. It simply measures a player's batting average on balls in play, with outcomes such as strikeouts and home runs removed from consideration. The league average generally hovers around .300, a nice round number to remember. However, it has been trending downward in recent years with 2024's figure coming in at .291.
Many know BABIP as an approximation of luck, with either a very high or very low number indicative of major batting average regression in the future. That is partially correct -- the stat can be used to predict batting average fluctuations. However, a player's skills may allow him to consistently run a better-than-average BABIP, or doom him to consistently below-average figures.
There are two primary sources to look up a player's BABIP: FanGraphs and Baseball Reference. They don't always have the same numbers, and FanGraphs is preferred because the site lets you look at BABIP by batted ball type (more on that below). Just type in a player's name in the search bar provided and his BABIP is displayed in the first chart. Now that you know where to find BABIP, let's explore how to use it.
The Above-Average BABIP Formula
If you want an example of a batter who sustainably runs high BABIPs, look no further than Bobby Witt Jr. Witt hit .332/.389/.588 with 32 HR and 31 SB in 2024 thanks in part to a .354 BABIP, more than 50 points better than the league average. If we regressed his BABIP to .291, Witt wouldn't be worth a first-round pick.
Fortunately for Witt, much of his BABIP boils down to sustainable skills and not dumb luck. As the 31 SB suggests, Witt can fly. He can turn groundouts for other players into singles, giving him a consistent source of base hits to prop up his BABIP and overall value. Of course, running fast doesn't mean Witt couldn't be fortunate or unfortunate in any given season. How can fantasy managers tell the difference?
Looking at BABIP by batted ball type can be a great tool for examining this. Witt gets his speedster hits exclusively on grounders, as footspeed does nothing to prevent a fielder from catching an airborne ball.
While the league averaged a .245 BABIP on grounders in 2024, Witt posted a .387 mark on them. His career rate is strong at .332 but not quite as high. Therefore, we can conclude that Witt should continue to overperform the league average BABIP on ground balls in 2025 but not as much as last year.
Witt's wheels won't help his BABIP on fly balls or line drives. His .129 BABIP on flies beat the league's .110 mark, so there could be slight regression this year. His .773 BABIP on line drives bested the league's mark of .693, likely costing Witt a few more hits. We should expect Witt's overall BABIP to decrease while still beating the league's mark handily.
BABIP takes multiple seasons to stabilize (or become predictive), and you should avoid rushing to conclusions when using it. A rookie who posts a .380 BABIP should not be expected to keep it up because that's suddenly his baseline. That said, an established player's baseline is more predictive of future performance than the league average, barring any changes.
The Below-Average BABIP Formula
The same trend is possible in a negative way. For example, fantasy managers know Rhys Hoskins as a potential power source who will drain your roster's batting average thanks in large part to a consistently low BABIP. Last season, Hoskins posted a BABIP of just .250 and a batting average of .214, creating batting average upside if you think it'll regress to .291. That isn't happening.
Hoskins hasn't posted a league-average BABIP in his entire MLB career:
While Witt's speed grants him base hits, Hoskins' poor speed means he is retired on grounders that others can beat out. He also hit just 4.8% of his ground balls to the opposite field, allowing opposing defenders to cheat to one side every time up. The result was a .231 BABIP on grounders in 2024, substantially better than his .200 career mark. If anything, we should expect negative BABIP regression.
That's not the end of Hoskins' BABIP problems, though. He also posted a 48.4% FB% and 13.5% infield fly-ball percentage (IFFB%), which are pop-ups. Pop-ups are nearly always caught with minimal difficulty, so players who hit a ton of them tend to run low BABIPs. Sure enough, Hoskins' career BABIP on flies of .107 looks great compared to the .081 he put up last season.
It's easy to see why Hoskins struggles with BABIP season after season. That won't change in 2025.
Conclusion
To conclude, BABIP can be used to indirectly measure a player's batting average luck by comparing it not to the league average, but to an established player's career number. Younger players without an established baseline are generally regressed to the league average, but these predictions are less reliable than those based on a player's personal history.
Footspeed, batted ball authority, line drive rate, and defensive positioning all give players some ability to manipulate BABIP. Players with these skills may still overachieve, and this regression can be analyzed by examining BABIP by batted ball type. Our next installment will look at HR/FB and why it is sometimes called the BABIP of power.
