Batted Ball Location and BABIP

In recent months, Eno Sarris has talked a lot about going to the opposite field and how a hitter who sprays the ball to all fields may have a higher BABIP than those who primarily pull the ball. Furthermore, last summer Jeff Zimmerman updated an older BABIP formula and shared with us an xBABIP spreadsheet. Simply copy and paste a couple of lines of numbers from a player’s page and the calculator spits out an expected BABIP. The formula incorporates a hitter’s power, speed and batted ball distribution and does a darn good job of it. But with Joey Votto crediting his ability to go to all fields as a major factor behind his always near league-leading BABIP marks, I felt that it was time to start doing the research to determine if he was indeed on to something.

I looked at the cumulative totals for all hitters from 2002-2013 that recorded at least 100 plate appearances with all three of the following batted ball types: pull, center and opposite. That of course means pulled balls, those hit up the middle and then balls hit the opposite way. I was left with 841 players in my sample and the correlations with BABIP are as follows:

Pull: -0.28
Center: 0.26
Opposite: 0.17

Now in the more visually attractive graphical format:

Pull % vs BABIP

Center % vs BABIP

Opposite % vs BABIP

Though the correlations aren’t very strong, it is clear that the location of the batted ball plays a role. From the charts, we find that batters with higher pull percentages generally have lower BABIP marks. Hitting the ball up the middle appears to be the best, while going the opposite way also positively impacts a hitter’s BABIP.

These correlations make it very clear that there is a lot more to determining a batter’s true talent BABIP than just looking at where on the field balls are hit to. This point is rather obvious given the current incarnation of the xBABIP formula. But the correlations are still meaningful and suggest that perhaps the location of a hitter’s batted balls should be incorporated into the formula as well. As such, we are going to be working on improving the xBABIP formula and spreadsheet, as this could be one of the few remaining missing links.





Mike Podhorzer is the 2015 Fantasy Sports Writers Association Baseball Writer of the Year and three-time Tout Wars champion. He is the author of the eBook Projecting X 2.0: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. Follow Mike on X@MikePodhorzer and contact him via email.

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tz
11 years ago

Cool stuff Mike. I’m thinking that a good portion of the correlation would be driven by teams that aggressively shift against dead pull hitters, shrinking the zones where they can deposit a hit on balls in play.

Would the correlation show up strongly if you regressed BABIP to a control variable that was set to +1 for pull, 0 to center, and -1 to opposite?

Eno SarrisMember since 2020
11 years ago
Reply to  tz

This is exactly why Votto posited the theory. He said extreme pull hitters are easy to defend. You know where they are going to hit the ball.