11 Hitter BABIP Surgers For 2018

A year ago, I introduced the latest and greatest version of my hitter xBABIP equation, this time incorporating shift data. Even though it was leaps ahead of any previous iterations and attempts at an xBABIP equation, it still only resulted in an adjusted R-squared of 0.5377. There’s still a whole lot more work to be done here! I would have liked to spend some time doing more research in the hopes of unveiling a further improved equation before the season begins, but alas, I haven’t had the time.

So we’ll stick to the current equation and begin by identifying 11 fantasy relevant hitters whose xBABIP marks sat significantly above their actual BABIP marks. Assuming similar skills driving my BABIP equation, these are the guys who should enjoy a spike. Be careful not to confuse this with a batting average spike, as there’s more to a batting average than just BABIP. Both strikeout and home run rate will affect batting average, so this is just one of the drivers.

2018 BABIP Surgers
Rhys Hoskins 23.8% 41.2% 4.0% 46.0% 3.4 1.4% 9.3% 0.241 0.335 -0.094
Miguel Cabrera 27.3% 32.1% 0.8% 42.5% 1.1 1.8% 8.4% 0.292 0.354 -0.062
Ian Kinsler 20.6% 39.8% 6.7% 37.0% 5.6 1.8% 12.6% 0.244 0.301 -0.057
A.J. Pollock 23.3% 28.1% 4.0% 35.0% 7.5 2.7% 7.3% 0.291 0.343 -0.052
James McCann 28.2% 31.2% 3.0% 38.2% 3.3 2.3% 10.7% 0.300 0.349 -0.049
Russell Martin 23.7% 24.5% 3.6% 30.2% 2.2 5.0% 20.7% 0.261 0.310 -0.049
Gregory Bird 17.9% 46.2% 5.7% 36.5% 1.3 16.7% 72.4% 0.194 0.241 -0.047
Brad Miller 16.5% 33.9% 2.2% 38.4% 4.6 5.3% 36.1% 0.265 0.307 -0.042
Yasmany Tomas 20.5% 31.7% 0.8% 41.9% 2.3 2.4% 9.3% 0.294 0.332 -0.038
Ryan Braun 18.9% 29.0% 2.9% 39.0% 5.3 1.5% 5.2% 0.292 0.330 -0.038
Nick Castellanos 24.5% 37.6% 0.6% 43.4% 4.6 4.9% 21.3% 0.313 0.351 -0.038
Unweighted Avg**** 20.3% 32.3% 3.4% 31.9% 3.8 4.9% 22.3%
*True FB%
**True IFFB%
***Pull GB While Shifted%
****Averages not weighted by PA and only from my population set of 435

And now you have more context for why I selected Rhys Hoskins 37th overall during last week’s LABR Mixed draft. I noted in my recap that my batting average projection is higher than the rest of the systems, and this is why. While Hoskins is a fly ball hitter, he hit a high rate of line drives, didn’t pop up too frequently, hit the ball ridiculously hard, and rarely got shifted. Perhaps my favorite part of Hoskins’ profile is his contact ability. For a power hitter, a 7.1% SwStk% is fantastic. Sure, it came in a small sample, but he posted single digit SwStk% marks at Double-A and Triple-A as well.

Another day, another “bad luck” list that Miguel Cabrera appears on. What’s important to note is that he has not been a consistent xBABIP underperformer. Since 2012, his BABIP marks have remained rather close to his xBABIP, with the lone exception coming in 2015, when he vastly outperformed his xBABIP. But at this point, I’m not questioning an offensive rebound, I’m just wondering about his health. That’s going to be the determinant of whether he ends up a bargain at his current ADP (94.5).

Ian Kinsler appears to be a bargain this draft season. I’m not entirely sure why, though I’m guessing it has a little something to do with him entering his age 35 season. He has underperformed his xBABIP mark a couple of times, but never anywhere close to this degree. Figure he’ll return to the .280-.300 range.

A.J. Pollock did almost everything right, between hitting line drives, hitting it hard, rarely grounding into a shift, and showcasing his speed. Yet, his BABIP fell below the league average for no reason whatsoever. In fact, his xBABIP was marginally above his 2015 mark when he posted a .338 BABIP and above both his 2013 and 2014 marks when his BABIP was comfortably above .300. He’s a near lock to push that BABIP back over .300.

It’s rare that you see an xBABIP of .349 from a catcher, but that’s exactly what James McCann posted. Don’t get so excited though as it was largely due to an unsustainable 28.2% LD%. How’d he do that and post just a league average BABIP?!

This was Russell Martin’s highest xBABIP since I have been calculating it from 2012. His LD% spiked to the highest mark of his career, and that’s not going to be sustainable. So while his BABIP should rebound off .261, it’s not going to rise all that much, and certainly not to the level of his xBABIP.

Okay, so even Gregory Bird’s xBABIP is terrible. He knocked a ton of fly balls, wasn’t a fan of the line drive, and grounded into the shift often. Of course, literally anyone could predict his BABIP will jump from .194. I figured that he’ll be a bit less extreme this year and hopefully health won’t be holding him back this time.

Brad Miller is one of those that breaks xBABIP. He has underperformed that mark every season since 2013, though this was easily the most dramatic underperformance. I’m more fascinated by the fact that he suddenly discovered home run power in 2016 and then gave it all back, and yet his Hard% actually went up!

Who would have though that slow-footed, power hitting Yasmany Tomas was worthy of a .332 BABIP?! Amazingly, his BABIP skills have remained remarkably consistent, as he has posted xBABIP marks between .332 and .336 each season since his 2015 debut. Oddly, his actual BABIP has been all over the place and in free fall, dropping from .354 to .310 to.294. The humidor certainly won’t help him rebound, but he should still get back over .300.

Strangely, Ryan Braun significantly outperformed his xBABIP marks back in 2012 and 2013, but has now underperformed for four straight seasons. His 2017 marked the most dramatic underperformance, though. His age, injury history, and outfield logjam in Milwaukee scare me enough though that even assuming a BABIP rebound, I’m not too excited.

Man, if you thought I’ve gotten tired talking about Miggy Cabrera on these poor fortune lists, how about the poster boy, Nick Castellanos? But unlike HR/FB rate, Castellanos hasn’t been a consistent underperformer — he actually outperformed in both 2015 and 2016. He owns a near elite batted ball profile with lots of line drives and few pop-ups, so he should remain well above .300 in BABIP.

Mike Podhorzer is the 2015 Fantasy Sports Writers Association Baseball Writer of the Year. He produces player projections using his own forecasting system and is the author of the eBook Projecting X 2.0: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. His projections helped him win the inaugural 2013 Tout Wars mixed draft league. Follow Mike on Twitter @MikePodhorzer and contact him via email.

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Hey Mike, there was a lot of talk about Detroit’s tracking software not working correctly last year. Does this impact your thoughts on the two Tigers on this list?

Justin C
Justin C

Four Tigers, don’t forget Kinsler’s data for 2017 is from when he was a Tiger. I would think this has to have an impact on the above list.


Saw somewhere it was mostly right field that is off, which makes sense given that Miggy and to a lesser extent Castellanos go that way quite a bit for righties.


Two tigers? Try 4…