In this video, we will be discussing a variation of the metric, Batting Average, by explaining Batting Average on Balls in Play (BABIP).
While batting average accounts for all official at-bats for a player throughout a season, BABIP serves to look more closely at how players fared on only balls put into play and can help shine a light on why a player might be underachieving or overachieving.
BABIP Explained
BABIP works similarly to batting average, but as the name suggests, it only accounts for batted balls put in play. This means that events like home runs, strikeouts, and walks are excluded. More specifically, BABIP is represented by this equation:
(H – HR) / (AB – K – HR + SF)
In practice, here is how it works. Let’s say a hitter goes 1 for 4 with a strikeout, single, and 2 flyouts. While their batting average would be .250, their BABIP would be .333, since in this instance we exclude the strikeout.
Application
One of the ways BABIP can be used is to account for “luck” when evaluating a hitter’s or pitcher’s performance. Luck can refer to the randomness of outcomes that happens during games, such as the slow-rolling dribbler that finds a hole or the hard-line drive hit directly at a fielder that more often than not is a base hit.
It’s possible that a hitter will make hard contact consistently over a period of a couple of months, get a little unlucky, and have a well-below-average BABIP (or even batting average). In his potentially small sample size, we can use BABIP to evaluate those recent outcomes as a way to grasp the amount of “luck” or randomness that may have occurred depending on how far he deviates from his career BABIP numbers or against the league average.
Because there are so many factors that can influence the outcome of a batted ball, BABIP helps us account for the elements of randomness, defensive positioning, ballpark factors, and ultimately, small sample sizes, etc.
Data shows that balls put in play in Major League Baseball fall for hits roughly 30% of the time, or have close to a .300 BABIP. Knowing this, we can determine whether a hitter is above or below the league average and we can even take their career BABIP numbers and compare it against a recent stretch to better evaluate their recent batted ball outcomes.
Most of the time, a player’s BABIP will regress to the mean when looking at a sample size closer to an entire season and more. Because of this, BABIP can be a valuable tool to evaluate future performance.
For example, a hitter who has an average BABIP of .325 throughout the previous four seasons may display a BABIP of .430 during the first half of the season. These numbers could lead us to think that this is an outlier compared to his previous performance versus the league average, which might be an indicator that he is benefitting from some lucky outcomes and be due for regression during the second half.
Summary
BABIP is a helpful tool for looking at season-to-season metrics when attempting to better evaluate current and future performance. This stat can be used in conjunction with other advanced metrics to understand why players are performing the way they are in a particular season.
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