## xBABIP Adjusted Lines for Rays Batters in 2009

Thanks to B Ray for posting the link to Chris Dutton's xBABIP calculator.  I wanted to take a look at which guys posted an actual BABIP that was close to or way off from their xBABIP.  As usual, this led me down some other interesting roads to get an idea of which guys over/under performed their expected lines.  First off, here is a link to the google.doc HERE and a link to the .xls download:   xBABIP Corrected Statistics

Let's start by looking at the xBABIP vs. Actual BABIP, sorted by highest xBABIP, for all Rays with >=30 AB:

 Player
 xBABIP
 BABIP
 0.356 0.338 0.327 0.327 0.324 0.324 0.323 0.322 0.318 0.317 0.307 0.306 0.302 0.299 0.296 0.292 0.292 0.291
 0.346 0.312 0.33 0.368 0.294 0.355 0.267 0.319 0.274 0.304 0.348 0.319 0.276 0.259 0.32 0.253 0.233 0.136

More fun stuff continues, after the jump.

It makes sense that the guys that you think of as speed guys have the higher xBABIP's, while the inverse is true for some of the slower guys.  I think you can get a good idea of guys that seemed overly lucky (Bartlett, Iwamura) and those that were unlucky (Pena, Navarro, Upton) just by giving the list a quick perusal.  To extend on this, we can assume that the difference between the xBABIP and BABIP times AB should give an idea of how many hits a guy was robbed of or lucked into:

 Player
 AB
 Diff
 #H
 Dioner Navarro Carlos Pena B.J. Upton Willy Aybar Pat Burrell Gabe Gross Gabe Kapler Carl Crawford Michel Hernandez Matt Joyce Evan Longoria Fernando Perez Joe Dillon Gregg Zaun Ben Zobrist Reid Brignac Akinori Iwamura Jason Bartlett
 376 471 560 296 412 282 205 606 99 32 584 34 30 94 501 90 231 500
 -0.059 -0.039 -0.026 -0.044 -0.026 -0.03 -0.04 -0.01 -0.056 -0.155 -0.003 -0.013 0.024 0.013 0.003 0.041 0.031 0.041
 -22 -18 -15 -13 -11 -8 -8 -6 -6 -5 -2 0 1 1 2 4 7 21

In this case, a negative number implies that the batter was robbed of that many hits, conversely, a positive number shows how many the batter lucked into.  It looks like a lot more of our guys were unlucky than lucky at first glance.  So what does this all mean to some of the basic statistics?  First off, here are the players' actual slash line statistics from 2009:

 Player
 AVG OBP SLG OPS
 Ben Zobrist Carlos Pena Evan Longoria Jason Bartlett Carl Crawford Gregg Zaun Joe Dillon Matt Joyce Gabe Kapler Willy Aybar Reid Brignac Akinori Iwamura B.J. Upton Pat Burrell Gabe Gross Michel Hernandez Dioner Navarro Fernando Perez
 0.297 0.405 0.543 0.948 0.227 0.356 0.537 0.893 0.281 0.364 0.526 0.89 0.32 0.389 0.49 0.879 0.305 0.364 0.452 0.816 0.287 0.323 0.489 0.812 0.3 0.4 0.4 0.8 0.188 0.27 0.5 0.77 0.239 0.329 0.439 0.768 0.253 0.331 0.416 0.747 0.278 0.301 0.444 0.745 0.29 0.355 0.39 0.745 0.241 0.313 0.373 0.686 0.221 0.315 0.367 0.682 0.227 0.326 0.355 0.681 0.242 0.292 0.323 0.615 0.218 0.261 0.322 0.583 0.206 0.206 0.206 0.412

If we assume that every one of the hits that a player was robbed or lucky on was a single, then we can adjust these to show what each batter should have looked like:

 Player
 AVG OBP SLG OPS
 Ben Zobrist Carlos Pena Evan Longoria Jason Bartlett Carl Crawford Gregg Zaun Joe Dillon Matt Joyce Gabe Kapler Willy Aybar Reid Brignac Akinori Iwamura B.J. Upton Pat Burrell Gabe Gross Michel Hernandez Dioner Navarro Fernando Perez
 0.294 0.402 0.54 0.942 0.266 0.388 0.576 0.965 0.284 0.366 0.529 0.895 0.279 0.353 0.449 0.802 0.315 0.373 0.462 0.835 0.274 0.311 0.476 0.787 0.276 0.379 0.376 0.755 0.343 0.404 0.655 1.059 0.279 0.364 0.479 0.843 0.297 0.37 0.46 0.83 0.237 0.261 0.403 0.665 0.259 0.328 0.359 0.686 0.267 0.336 0.399 0.736 0.247 0.338 0.393 0.73 0.257 0.352 0.385 0.737 0.298 0.345 0.379 0.724 0.277 0.316 0.381 0.697 0.219 0.219 0.219 0.438

This can be a lot to try to sort through, so lets just take a look at actual wOBA (AwOBA) vs. expected wOBA (XwOBA):

Player XwOBA AwOBA
 Matt Joyce Ben Zobrist Carlos Pena Evan Longoria Carl Crawford Gabe Kapler Willy Aybar Joe Dillon Jason Bartlett Gregg Zaun Gabe Gross B.J. Upton Pat Burrell Michel Hernandez Akinori Iwamura Dioner Navarro Reid Brignac Fernando Perez
 0.44 0.398 0.389 0.366 0.363 0.359 0.357 0.347 0.345 0.337 0.328 0.325 0.321 0.321 0.307 0.3 0.284 0.191
 0.319 0.4 0.36 0.364 0.355 0.328 0.322 0.366 0.377 0.349 0.304 0.304 0.301 0.274 0.331 0.251 0.32 0.18

Bear in mind, this is the original formula for wOBA that doesn't include stolen base numbers.  I have omitted ROE as well.

Guys that appear to benefit quite a bit are Carlos Pena, Gabe Kapler, Willy Aybar, Gabe Gross, B.J. Upton, Pat Burrell, and Dioner Navarro.  Guys that seem like they were quite a bit lucky are Jason Bartlett, Gregg Zaun (includes time with Tampa Bay and Baltimore), and Akinori Iwamura.  Weird that 2 of those guys are now gone.  Also, check out Matty Joyce doing a Pujols!  IF ONLY WE ACTUALLY PLAYED HIM11!!!!111 To correct for asinine statements like these that are sure to come, we can look at wRAA, which will factor in PA as well as the league average wOBA of .321:

Player XwRAA AwRAA
 Carlos Pena Ben Zobrist Evan Longoria Carl Crawford Jason Bartlett Willy Aybar Gabe Kapler Matt Joyce Gabe Gross Gregg Zaun Pat Burrell B.J. Upton Joe Dillon Michel Hernandez Reid Brignac Akinori Iwamura Fernando Perez Dioner Navarro
 33.9 40 26.3 24.8 11.6 10.5 7.9 3.8 1.9 1.4 0.1 2.1 0.8 0 -3 -3.3 -3.9 -7.5
 19.6 41.2 24.9 20.1 27.7 0.3 1.5 -0.1 -4.7 2.4 -8.3 -9.3 1.4 -4.3 -0.1 2.3 -4.3 -24.9

Suddenly Navi does not look as bad, once we've stripped some of the unluckiness out of his balls in play.  Same can be said for Pena, who now looks like a stud, contributing 4.25 wins with his bat alone.  Another reoccurring theme is the Jason Bartlett normalization.  It suddenly appears that a hot-shot rookie that plays substantially better defense could replicate those runs.  Lastly, we can just look at the difference of the wRAA's as a kind of continuum:

Click to embiggen

(Updated XwRAA & Continuum at 11:14 on 1/8/10)

Something that I didn't touch on throughout this was the fact that guys like Crawford, Longoria, and Zobrist a.k.a. THE CORE, were not relatively lucky either way.  They had genuinely good to great seasons according to this.  If this statistic has any predictive value then we can look forward to more of the same next year.  Also, I just realized that I forgot to include Kelly Shoppach, so I will post some of his relevant items in the comments.  Haters wanna hate?

Here are the Kelly Shoppach lines, I apologize for not doing this in the main stuff, but I'm not creating this post all over again.

 xBABIP 0.328 BABIP 0.286 Diff -0.042 #H -11 aAVG 0.214 aOBP 0.335 aSLG 0.399 aOPS 0.735 awOBA 0.327 awRAA 1.6 eAVG 0.256 eOBP 0.370 eSLG 0.441 eOPS 0.811 ewOBA 0.358 ewRAA 10.5 DiffwRAA 8.9

As you can see, Shopp was quite a bit unlucky in 2009.  Hopefully, he has a big bounce-back as a 0.811 OPS out of the catcher spot could really put this team over the top.

## Trending Discussions

forgot?

As part of the new SB Nation launch, prior users will need to choose a permanent username, along with a new password.

I already have a Vox Media account!

### Verify Vox Media account

As part of the new SB Nation launch, prior MT authors will need to choose a new username and password.

We'll email you a reset link.

Try another email?

### Almost done,

By becoming a registered user, you are also agreeing to our Terms and confirming that you have read our Privacy Policy.

### Join DRaysBay

You must be a member of DRaysBay to participate.

We have our own Community Guidelines at DRaysBay. You should read them.

### Join DRaysBay

You must be a member of DRaysBay to participate.

We have our own Community Guidelines at DRaysBay. You should read them.