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Stripping the "luck" out of luck: Cleveland's 2013 xBABIP

Chisenhall, Gomes sit on the opposite ends of BABIP fortune

Stripping the "luck" out of luck: Cleveland's 2013 xBABIP
Lonnie Chisenhall (Photo: Chuck Crow/The Plain Dealer)
March 15, 2014
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A hitter times the pitcher perfectly and smashes a line drive up toward left field, only for the shortstop to leap up and catch the ball at the apex of his jump.

The next time up, the hitter gets jammed by the same pitcher, only to see his weakly hit fly ball find a way to fall between the third baseman, the shortstop, and the left fielder.

Sometimes baseball just is not fair -- both to hitters and defenders -- and some players are more fortunate than others in any given season. This "luck" is often represented by BABIP, though just chalking a player's BABIP up to luck is too blunt.

Hitters can control their BABIP to an extent. Speedy runners who slap a ton of ground balls to the opposite field will likely be able to sustain a higher BABIP. Same goes for a hitter with a smooth line drive stroke. On the other hand, slower runners who hit a lot of fly balls -- which outfielders have tons of time to catch -- typically end up with lower-than-average BABIPs.

Point being, there is plenty of variation with BABIP and regressing everyone to league-average is too broad of a solution. It's not one size fits all.

So what does this mean for Cleveland in 2014? Well, both good and bad things.

But first, the 2013 xBABIP -- or expected BABIP -- table for the team. xBABIP is a stat that takes the hit types of a hitter and yields what BABIP he should have ended up with. It has its flaws, but it is a better measure of true talent BABIP than BABIP itself.

Name

xBABIP

BABIP

Diff

Yan Gomes

0.295

0.342

0.047

Ryan Raburn

0.295

0.311

0.016

Jason Kipnis

0.340

0.345

0.005

Michael Bourn

0.333

0.338

0.005

Drew Stubbs

0.332

0.319

-0.013

Mark Reynolds

0.296

0.282

-0.014

Carlos Santana

0.315

0.301

-0.014

Michael Brantley

0.324

0.304

-0.020

Nick Swisher

0.312

0.288

-0.024

Mike Aviles

0.283

0.257

-0.026

Asdrubal Cabrera

0.318

0.283

-0.035

Jason Giambi

0.257

0.202

-0.055

Lonnie Chisenhall

0.308

0.243

-0.065

Now for a few observations:

  • IBI's own John Grimm already outlined Gomes and Chisenhall himself in much better detail, so I will not bother repeating it here. Suffice to say, though, that this paints a positive outlook for Chisenhall.  His career xBABIP is a robust .309 compared to his career BABIP of .274; maybe 2014 will be the year the third baseman's results finally reflect his expected ones.
  • As for Gomes, expecting an exact repeat of 2013 was always a little ridiculous. Six or seven WAR players are not common, nor are they frequently traded for Esmil Rogers. I expect Gomes will be closer to average offensively in 2014, though his very good defense would still make him an above-average player in that case.
  • Despite a beautiful swing that garnered him a legion of fans, Brantley's line in 2013 was really just middle-of-the-road (.284/.332/.396 line, 104 wRC+). But given his swing and strong line drive tendencies, it would make sense to see Brantley's BABIP -- and thus overall offensive profile -- be a little higher than this. His BABIP is essentially league-average, but given his higher xBABIP, it would not be a shock to see his offense (and his BABIP) take a jump in 2014. This potential BABIP jump would help take Brantley from middle-of-the-road offensively to, well, better than middle-of-the-road.
  • A potential issue for Cleveland with the members of its 2012-13 offseason signing bonanza is the early performance of Bourn. The outfielder's wRC+ dropped from 105 to 91, a drop-off particularly worrisome if it continues into 2014. Bourn had shown the ability to be closer to average with his offense and his BABIP did fall in 2013 (his BABIP went from .369 in 2011 to .349 in 2012 to .338 last year). But as the table shows, fewer line drives off of Bourn's bat led to the lower BABIP; it was not an unlucky dip. If Bourn is going to improve offensively in 2014 it will need to come from a better performance on the field, not some BABIP luck.
  • One of the best chances for Cleveland to avoid regression from its 92-win 2013 season may come in seeing BABIP bounce backs from Swisher, Aviles, and Cabrera. The two starters fell off significantly in 2013 (Swisher: 128 wRC+ to 116; Cabrera 113 to 95) and though Aviles actually saw his performance rise slightly (75 wRC+ to 80), he was still a well below-average hitter. All three project to play a lot in 2014, and if they are better on offense in line with their xBABIP expectations, it will help counter the likely regressions from players like Gomes.

Even though it aims to correct for some of the randomness of BABIP, xBABIP is still not a perfect tool. One issue is it does not measure weaker contact. It would not surprise me if a player like Jason Giambi's BABIP is so low due to a poor quality of contact rather than bad luck as his xBABIP indicates.

But as a whole, xBABIP helps us understand players even more than just their raw BABIP and regressing to the mean. Because why should we treat Jason Giambi (older, slower, fly ball oriented) and Jason Kipnis (younger, faster, line drive oriented) the same way with regard to their BABIPs?

If you want to follow Jim on Twitter, he’s @JimPiascik. If you want to e-mail him, you can do so at jpiasci1@gmail.com

User Comments

Jim Piascik
March 17, 2014 - 11:06 AM EDT
Here's the formula I used:

xBABIP = (( GB – IFH ) * (GB-IFH constant) + (FB-HR-IFFB) * (OFFB Constant) + LD * (LD Constant) + IFH + BUH ) / (GB + FB + LD + BU + – HR – SH)

As for the percentages, I used the 2009-11 rates of 19.5 percent for groundballs (eliminating infield hits, which are fully credited to the hitter), 13.4 percent for fly balls to the outfield (because infield flies are outs roughly 99.9 percent of the time), and 74 percent for line drives.

But that difference between line drives and fly balls is hard to define. I've scored games with these distinctions and can tell you its very subjective. Which is a big part of why I don't wholly trust line drive rates; way too much open for interpretation in there.

But as a whole, these are useful stats. There is some room for error, but not enough to take Gomes all the way up to a .320 xBABIP or Bourn beyond basically in line with his 2013 BABIP. As long as you don't take them as absolutes and understand there is a margin of error, you can make good judgments using these stats.

Or really, for all stats. Always be aware of the margin of error. :)
Hermie13
March 17, 2014 - 9:08 AM EDT
@Rich

Yes, LD% is part of the xBABIP calc. Like I said, it depends on which method you use to calculate it, but one thing they all seem to agree on is you use LD% in addition to GB% and FB%. Typically they assume around 70-75% of line drives fall for hits, around 20-25% of groundballs go for hits, and around 12-15% of flyballs fall for hits.

One thing that will always be an issue with BABIP....what's the difference between a linedrive and a flyball? At what point does that "looping liner" become a flyball vs an actual linedrive?
Hermie13
March 17, 2014 - 8:53 AM EDT
Curious which formula you used to calculate your xBABIPs here. I've found two commonly used ones and I am getting different numbers than you posted (though not by a ton). I believe there are most than those two methods for determining it as well.


The xBABIP numbers I got show that Gomes should be able to hit .265 and have an OPS over .750. That's pretty solid for any position anymore.
Rich
March 15, 2014 - 3:30 PM EDT
I assume the xBABIP number is calculated by using the line drive rate to some extent? In that case, I can see why players like Giambi and Santana's actual BABIP is lower then the expected value. They are dead pull hitters and opponents shift dramatically on them, so a lot of their line drives are outs.

The fact that they are slow getting down the line means they don't leg out any hits, either, even when Giambi dives into first base.

A great example is Travis Hafner. How many times did he rip a line drive into right field only to be thrown out by the second baseman who was playing 40' back on the grass?

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