Using Sabermetrics for Fantasy Baseball: BABIP for Hitters

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. In general, the league average hovers around .300, a nice round number to remember.

Many know BABIP as an approximation of luck, with either a very high or very low number indicative of a 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 run a better than average BABIP, or doom him to a consistently below-average figure. One example of this is Christian Yelich.

Let's see how this metric can be used to evaluate one of the most impactful bats in the majors and how you as a fantasy owner should use it to your advantage when preparing for your upcoming drafts.

The Above-Average BABIP Formula

Yelich has been a batting average force for a while now, but the addition of elite power to his profile has made him a consensus top-3 pick heading into 2020. In 2019, Yelich hit an outstanding .329/.429/.671 with 44 HR and 30 SB in just 580 PAs. One of the reasons for his success was a .355 BABIP, so Yelich loses a lot of value if we regress that all the way to .300. Should we really do that?

Yelich's career BABIP is .358, clearly indicating a sustainable ability to beat the league average .300. Considering last year's BABIP of .355 was within three points of his career rate, a repeat is the safest projection. What skills does Yelich possess that allow him to crush the average player?

Yelich is an elite speedster--his 28.7 ft./sec Statcast Sprint Speed was nearly two full ticks above average last year. It makes sense that someone with Yelich's wheels could beat out more base hits than other players, while most catchers would lag in this regard. Therefore, an established player's baseline BABIP should not be the league average .300, but whatever that specific player's career BABIP is.

Looking at BABIP by batted ball type can also be a great tool. Yelich gets his speedster hits exclusively on grounders, as running really fast does nothing to prevent a fielder from catching a ball in the air. While the league averaged a .236 BABIP on grounders, Yelich posted a .292 mark on them last year. His career rate is only .276. Therefore, we can conclude that Yelich will continue to outperform the league average on ground balls because his .276 career BABIP is much higher than the league average. However, he is unlikely to do so to the same extent he did in 2019.

Comparing BABIPs for the other batted-ball types year over year is something of a mixed bag for Yelich. His fly balls found pay dirt much less frequently, posting a BABIP of .133 against a career mark of .201. However, his line drives fared considerably better (.744 BABIP last year) than they have in the past (.690 career). Overall, both figures should be expected to regress to the mean and roughly cancel each other out. When we factor in slight regression based on ground balls above, we should probably expect Yelich to fall just shy of last year's BABIP while still clearing .300 easily in 2020.

The Below-Average BABIP Formula

The same trend is possible in a negative way. For example, Anaheim's slugging DH, Albert Pujols, is well known for being an all-or-nothing batter that pulls the ball at every opportunity. This makes him susceptible to the shift, as the infield defense knows where the ball is likely to go and can set up accordingly. He also lacks the speed to beat out infield hits most other major leaguers can, finishing second to last in Statcast's Sprint Speed metric last year.

These factors figure to hurt his BABIP on grounders, and Pujols's .212 last year indicates that it did. This is not a new trend, as he hit .160 on grounders in 2018, .192 in 2017, .217 in 2016, and .179 in 2015. Clearly, projecting regression toward the league average would be wrong, as his pull tendencies and subpar speed allow the defense to consistently perform better than average against him. Pujols's overall BABIP was .238 last year, a number that should be expected moving forward due to his consistently poor production on ground balls.

Conclusion

To conclude, BABIP can be used to indirectly measure a player's batting average luck by comparing it not to the league average of .300 but to an established player's career number. Foot speed, 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 predicted by examining BABIP by batted ball type. 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. Click on this link to learn more about how sabermetrics can give you an advantage as a fantasy baseball owner!

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