2014 xBABIP Values

This past season, I introduced a xBABIP equation which uses Inside Edge’s hard hit rate and player speed. Well, I have been a little slow on any updates. I have finally gotten around to getting all the 2014 values in one place.

When creating the xBABIP values, I found it correlated more to the next season’s BABIP then any other easily created formulas. Here are the 2014 values with some thoughts on some individual players.

• Highly shifted players (Chris Davis, Mike Moustakas, Brian McCann): I tried with no luck to add pull data to the equation. It didn’t make any difference in the final xBABIP values because just a few hitters are heavily shifted. The shift is definitely part of this trio’s struggles, so their actual BABIP should be less than their expected BABIP.

Josh Harrison: He came out of no where to hit the ball hard. Additionally, he has a decent amount of speed to get some infield hits. The combination led to high BABIP and AVG in ’14, but the results look legit. His BABIP was only 10 points higher than his xBABIP, so he may not see as much regression as some people think in 2015.

Mike Zunino: A BABIP around .300 would be huge for his value. His average would be closer to .250 which would be nice to go with his projected 20 homers.

Lorenzo Cain: The 29-year-old may have had a career season in ’14 with his near .300 AVG supported by a .380 BABIP. His xBABIP was at .305, which is close to his 2012 and 2013 BABIPs which supported an AVG around .260. I could see him as a breakout/trendy pick for 2015 and therefore way over valued.

J.D. Martinez: The 2014 power numbers may be legit, but his BABIP (.389) driven AVG (.315) looks to regress to near his career values (.333, .272) if he .326 xBABIP is to be believed.

Jeff, one of the authors of the fantasy baseball guide,The Process, writes for RotoGraphs, The Hardball Times, Rotowire, Baseball America, and BaseballHQ. He has been nominated for two SABR Analytics Research Award for Contemporary Analysis and won it in 2013 in tandem with Bill Petti. He has won four FSWA Awards including on for his Mining the News series. He's won Tout Wars three times, LABR twice, and got his first NFBC Main Event win in 2021. Follow him on Twitter @jeffwzimmerman.

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9 years ago

Unluckiest (min. 500 PA)
C Davis
M Moustakas
C Carter
B McCann
C Crisp
J Bruce
K Davis
E Encarnacion
M Teixeira
C Santana

Luckiest (min. 500 PA)
A Eaton
C McGehee
C Johnson
J Abreu
C Yelich
Y Puig
J Altuve
JJ Hardy
A Beltre
K Suzuki

9 years ago
Reply to  Andrew

Is there any easy way to factor in distribution of hits and account for the babip-reducing effect of shifts?

9 years ago
Reply to  Andrew

I wouldn’t call your list of “unluckiest” actually the unluckiest. Of those names you listed, almost all of them are dead pull hitters, and get the shift put on them. Because they are hitting into the shift most of the time they get base hits taken away,lowering their xBABIP. I wouldn’t call those hits that were taken away “bad luck.” And so like the writer said, you’d expect these players to have a noticeably lower BABIP than xBABIP. I wouldn’t equate it to luck and I’d expect your entire list to be on the extremely “unlucky” side of things again this year.

9 years ago
Reply to  Andrew

Just because the formula used here (or any formula) does not explain it does not make it luck. (Even if the player cannot repeat the performance does not mean it was luck.)

Variance from a model or formula could be partially due to luck, but it is a lazy assumption that is wrong more than it is right.