Today we’ll look at a statistic that is interesting for both the offensive and defensive side of baseball. When a ball is put in play, how often does it go for a hit?
A ball in play is defined as any ball hit into fair territory, where the defense must make a play. The, we wish to calculate among all the times a ball was put in play by the batter, how frequently did that result in a hit? We call this Batting Average on Balls in Play, or BABIP.
The formula is simple enough. We start with the batting average formula, H/AB, and adjust terms as needed. We want to ignore any home runs from the hit and at-bat count, because those weren’t balls in play. Similarly, we take away strike-outs from the at-bat count, and add back sacrifice flies.1As discussed before, sacrifice flies tend to be “accidental”, so they are a ball in play. A sacrifice bunt is typically purposeful, and would almost never result in a proper hit. So we keep ignoring those.
\text{BABIP} = \frac{\text{H}-\text{HR}}{\text{AB} -\text{HR}-\text{K} + \text{SF}}BABIP operates as a moderately-advanced statistic that obliquely considers two factors in what makes a good hitter (or pitcher): quality of contact and hit location.
If a batter consistently hits the ball in a way that makes it difficult for the defense to field against — hitting the ball very hard on a line drive, spreading the ball around the field, or both — we would expect their BABIP to increase. It’s certainly possible for BABIP to increase due to dumb luck, or (less randomly) playing frequently against teams with poorer defenses, but it’s still indicative of some level of skill.
Let’s consider the defensive side of things as well. If a pitcher has high-quality pitch options, and can locate in the zone to induce poor contact, the result is an increased frequency of balls in play that are much easier for the defense to handle. Typically, BABIP is actually a better statistic for comparing pitchers (at least pitchers with a somewhat comparable defense behind them) and making conclusions about some of their skills.
BABIP, though being a reasonably good indicator of everything discussed above, is a noisy statistic. There are many other factors that make it a little convoluted to use it as a player comparison in a particular season; it’s better to look over a long span of several seasons. In addition, the distribution of BABIP among players in a season looks relatively uniform, rather than a normal distribution around the average that we see with standard batting average.
Finally, and these are where we’ll share some specific statistics, there can be some hilarious anti-correlations between BABIP and BA. Since sacrifice flies don’t dramatically change, this is an indication of a lot of strikeouts (high BABIP, low BA) or a lot of home runs (high BA, low BABIP).
- The highest BABIP since 1969 for a qualified hitter who finished with a BA lower than .300 is Jose Hernandez, who had a .288 BA, a .404 BABIP, and a league-leading 188 strikeouts.
- Conversely, the lowest BABIP since 1969 for a qualified hitter who finished with a BA of at least .300 is Hank Aaron in 1969, with a BABIP of .261 and a BA of exactly .300.
- Close behind Hank Aaron, but more extreme, was Barry Bonds in 2001 when he hit his 73 HR and was walked 177 times. He finished with a .328 BA and .266 BABIP.
Continue to Day 8 – Weighted Runs Above Average and Runs Created
- 1As discussed before, sacrifice flies tend to be “accidental”, so they are a ball in play. A sacrifice bunt is typically purposeful, and would almost never result in a proper hit. So we keep ignoring those.