clock menu more-arrow no yes mobile

Filed under:

2008 Defense Behind Pitchers By PMR

Team: PMR / RAA | 1B: PMR / RAA | 2B: PMRRAA | 3B: PMRRAA | SS: PMR / RAA | LF: PMR / RAA | CF: PMR / RAA | RF: PMR / RAA | C: PMR / RAA | P: PMR / RAA |
D Behind P: PMR / RAA

Each season, David Pinto releases his Probablistic Measure of Range (PMR) ratings based on play-by-play data from Baseball Info Solutions.  PMR measures how many plays above or below expected each team or player made based on batted ball characteristics like velocity and location. Here at Beyond the Box Score, we're translating the play numbers into runs (following a method developed by LA Black Hawk of Waterloo).  More information can be found in this post.

Along with the position-by-position numbers, David shares how each pitcher was affected by his defense during the season.  He follows a very similar methodology, determining the number of outs that should have been converted, and comparing those to the outs that were actually converted.

Player Team IP In Play Actual Outs Predicted Outs Outs Delta Runs Delta ERA Diff
Fausto Carmona Cle 120.67 405 273 288.06 -15.06 -14.194251 1.06
Adam Eaton Phi 107 356 236 248.23 -12.23 -11.175789 0.94
Darrell Rasner NYY 113.33 387 257 269.56 -12.56 -11.837967 0.94
Andy Pettitte NYY 204 641 420 439.26 -19.26 -18.152807 0.8
Ian Snell Pit 164.33 522 335 347.6 -12.6 -11.513895 0.63
Livan Hernandez Min 139.67 525 339 349.78 -10.78 -9.850777 0.63
Carlos Villanueva Mil 108.33 320 220 228.02 -8.02 -7.3286857 0.61
Garrett Olson Bal 132.67 451 295 304.47 -9.47 -8.9256013 0.61
Tom Gorzelanny Pit 105.33 332 225 231.65 -6.65 -6.076778 0.52
Andrew Miller Fla 107.33 336 216 222.12 -6.12 -5.5924634 0.47
Jonathan Sanchez SF 158 442 297 306.08 -9.08 -8.297315 0.47
Odalis Perez Was 159.67 507 337 345.85 -8.85 -8.0871407 0.46
Mark Buehrle CWS 218.67 699 466 477.66 -11.66 -10.989705 0.45
Cha Seung Baek SD 111 353 238 243.4 -5.4 -4.9345265 0.4
Luke Hochevar KC 129 430 291 297.11 -6.11 -5.7587565 0.4
Barry Zito SF 180 576 393 401.59 -8.59 -7.8495524 0.39
Brett Myers Phi 190 554 379 388.08 -9.08 -8.297315 0.39
Brandon Backe Hou 166.67 512 341 348.41 -7.41 -6.771267 0.37
Brian Burres Bal 129.67 460 309 314.46 -5.46 -5.1461228 0.36
Brian Bannister KC 182.67 603 408 415.51 -7.51 -7.0782751 0.35
Randy Wolf SD 119.67 348 237 242.07 -5.07 -4.6329721 0.35
Kevin Millwood Tex 168.67 569 360 366.45 -6.45 -6.079211 0.32
Mark Hendrickson Fla 133.67 439 302 307.04 -5.04 -4.6055581 0.31
Nick Blackburn Min 193.33 658 445 451.38 -6.38 -5.8300517 0.27
Pedro Martinez NYM 109 337 225 228.38 -3.38 -3.0886481 0.26
Jorge de la Rosa Col 130 361 240 243.99 -3.99 -3.6460668 0.25
A.J. Burnett Tor 221.33 613 405 411.37 -6.37 -6.0038099 0.24
John Maine NYM 140 399 286 290.11 -4.11 -3.755723 0.24
Kyle Davies KC 113 361 248 251.2 -3.2 -3.0160427 0.24
Mike Pelfrey NYM 200.67 652 446 450.98 -4.98 -4.55073 0.2
Edinson Volquez Cin 196 511 350 354.63 -4.63 -4.2308996 0.19
James Shields TB 215 641 448 452.73 -4.73 -4.4580881 0.19
Justin Verlander Det 201 598 415 419.47 -4.47 -4.2130346 0.19
Randy Johnson Ari 184 531 359 363.22 -4.22 -3.8562411 0.19
Ricky Nolasco Fla 212.33 606 432 435.96 -3.96 -3.6186528 0.15
Carlos Silva Sea 153.33 564 365 367.36 -2.36 -2.2243315 0.13
Clayton Kershaw LAD 107.67 306 204 205.65 -1.65 -1.507772 0.13
Jo-Jo Reyes Atl 113 361 241 242.79 -1.79 -1.6357042 0.13
Nate Robertson Det 168.67 563 365 367.59 -2.59 -2.4411095 0.13
Kenny Rogers Det 173.67 598 400 402.42 -2.42 -2.2808823 0.12
Zach Duke Pit 185 669 445 447.62 -2.62 -2.3941592 0.12
Ubaldo Jimenez Col 198.67 572 395 397.49 -2.49 -2.275365 0.1
Brandon Webb Ari 226.67 671 458 460.45 -2.45 -2.238813 0.09
Ervin Santana LAA 219 605 422 424.34 -2.34 -2.2054812 0.09
Jason Bergmann Was 139.67 445 310 311.45 -1.45 -1.3250118 0.09
Joe Blanton Oak 127 440 303 304.31 -1.31 -1.2346925 0.09
Daniel Cabrera Bal 180 594 409 410.64 -1.64 -1.5457219 0.08
Bronson Arroyo Cin 200 605 408 409.76 -1.76 -1.6082901 0.07
Chris Sampson Hou 117.33 383 267 267.83 -0.83 -0.758455 0.06
Andy Sonnanstine TB 193.33 632 432 433.24 -1.24 -1.1687165 0.05
Tim Redding Was 182 572 397 397.98 -0.98 -0.8955252 0.04
Wandy Rodriguez Hou 137.33 393 266 266.71 -0.71 -0.6487989 0.04
Ted Lilly ChC 204.67 574 412 412.67 -0.67 -0.6122468 0.03
Zack Greinke KC 202.33 587 399 399.62 -0.62 -0.5843583 0.03
Cliff Lee Cle 223.33 670 462 462.5 -0.5 -0.4712567 0.02
Chad Billingsley LAD 200.67 556 370 370.36 -0.36 -0.3289684 0.01
Jarrod Washburn Sea 153.67 512 350 350.13 -0.13 -0.1225267 0.01
Mike Mussina NYY 200.33 613 409 409.01 -0.01 -0.0094251 0
Gil Meche KC 210.33 611 420 419.79 0.21 0.1979278 -0.01
Manny Parra Mil 166 499 322 321.73 0.27 0.24672633 -0.01
Aaron Laffey Cle 93.67 316 217 216.67 0.33 0.3110294 -0.03
Boof Bonser Min 118.33 382 249 248.24 0.76 0.71631013 -0.05
Greg Maddux SD 153.33 511 360 359.16 0.84 0.76759302 -0.05
Jon Lester Bos 210.33 632 438 436.2 1.8 1.696524 -0.07
Brad Penny LAD 94.67 311 212 211.06 0.94 0.85897314 -0.08
Johnny Cueto Cin 174 500 344 341.79 2.21 2.01950067 -0.1
Tim Lincecum SF 227 562 385 382.12 2.88 2.63174748 -0.1
Aaron Harang Cin 184.33 552 379 376.37 2.63 2.40329718 -0.12
Joel Pineiro StL 148.67 505 342 339.9 2.1 1.91898254 -0.12
Javier Vazquez CWS 208.33 598 405 401.92 3.08 2.90294107 -0.13
Jose Contreras CWS 121 402 280 278.09 1.91 1.80020047 -0.13
Gavin Floyd CWS 206.33 625 450 446.51 3.49 3.28937153 -0.14
Jason Marquis ChC 167 554 390 387.25 2.75 2.51295333 -0.14
Matt Cain SF 217.67 630 436 431.93 4.07 3.71917092 -0.15
Jair Jurrjens Atl 188.33 589 401 397.07 3.93 3.59123876 -0.17
Kevin Correia SF 110 382 248 245.75 2.25 2.05605272 -0.17
Miguel Batista Sea 115 379 257 254.22 2.78 2.62018707 -0.21
Braden Looper StL 199 653 453 447.51 5.49 5.01676864 -0.23
Carlos Zambrano ChC 188.67 570 404 398.66 5.34 4.87969846 -0.23
Dan Haren Ari 216 610 421 414.6 6.4 5.84832774 -0.24
Jamie Moyer Phi 196.33 625 437 431.36 5.64 5.15383882 -0.24
Jered Weaver LAA 176.67 513 355 350.05 4.95 4.665441 -0.24
Todd Wellemeyer StL 191.67 579 419 413.37 5.63 5.14470081 -0.24
Dana Eveland Oak 168 519 351 346.09 4.91 4.62774047 -0.25
Jon Garland LAA 196.67 684 462 456.1 5.9 5.56082867 -0.25
Doug Davis Ari 146 457 303 298.15 4.85 4.43193587 -0.27
Hiroki Kuroda LAD 183.33 598 418 412.03 5.97 5.45539322 -0.27
Jeff Suppan Mil 177.67 589 407 401.18 5.82 5.31832304 -0.27
Kyle Lohse StL 200 650 453 446.33 6.67 6.09505407 -0.27
Aaron Cook Col 211.33 725 489 481.78 7.22 6.59764474 -0.28
Edwin Jackson TB 183.33 582 401 394.74 6.26 5.90013347 -0.29
Felix Hernandez Sea 200.67 577 391 384.12 6.88 6.48449173 -0.29
Oliver Perez NYM 194 527 380 373.11 6.89 6.29609034 -0.29
Johan Santana NYM 234.33 668 476 467.22 8.78 8.02317462 -0.31
Derek Lowe LAD 211 644 453 444.85 8.15 7.44747986 -0.32
John Danks CWS 195 569 396 388.39 7.61 7.17252647 -0.33
Micah Owings Ari 104.67 312 220 215.84 4.16 3.80141303 -0.33
Roy Halladay Tor 246 713 501 491.48 9.52 8.97272693 -0.33
Scott Baker Min 172.33 497 354 347.21 6.79 6.39966553 -0.33
Scott Olsen Fla 201.67 640 463 454.69 8.31 7.59368806 -0.34
Jeff Francis Col 143.67 469 321 314.83 6.17 5.63815347 -0.35
Matt Garza TB 184.67 560 399 391.43 7.57 7.13482593 -0.35
Paul Maholm Pit 206.33 621 437 428.22 8.78 8.02317462 -0.35
Scott Feldman Tex 151.33 488 344 337.73 6.27 5.9095586 -0.35
Cole Hamels Phi 227.33 635 464 453.13 10.87 9.93301915 -0.39
David Bush Mil 185 567 422 413.33 8.67 7.92265649 -0.39
Jake Peavy SD 173.67 459 331 322.53 8.47 7.73989625 -0.4
Jeremy Guthrie Bal 190.67 587 428 417.45 10.55 9.94351567 -0.47
Josh Beckett Bos 174.33 492 333 322.69 10.31 9.71731247 -0.5
Vicente Padilla Tex 171 524 356 345.93 10.07 9.49110927 -0.5
Kevin Slowey Min 160.33 480 340 330.37 9.63 9.0764034 -0.51
Ben Sheets Mil 198.33 589 417 404.45 12.55 11.4682052 -0.52
John Lannan Was 182 560 401 389.21 11.79 10.7737163 -0.53
Jorge Campillo Atl 158.67 490 347 336.39 10.61 9.69543084 -0.55
Zach Miner Det 118 385 276 268.08 7.92 7.4647056 -0.57
Adam Wainwright StL 132 404 289 279.63 9.37 8.56231734 -0.58
Dustin McGowan Tor 111.33 337 228 220.26 7.74 7.2950532 -0.59
Ryan Dempster ChC 206.67 572 406 391.16 14.84 13.56081 -0.59
John Lackey LAA 163.33 469 329 316.59 12.41 11.6965905 -0.64
Shaun Marcum Tor 151.33 427 317 305.52 11.48 10.8200531 -0.64
Joe Saunders LAA 198 623 445 429.72 15.28 14.4016037 -0.65
CC Sabathia Mil 130.67 353 246 235.49 10.51 9.60405072 -0.66
Brian Moehler Hou 150 509 356 343.33 12.67 11.5778613 -0.69
R.A. Dickey Sea 112.33 374 263 253.88 9.12 8.5957216 -0.69
Scott Kazmir TB 152.33 378 277 264.57 12.43 11.7154407 -0.69
Greg Smith Oak 190.33 578 423 406.63 16.37 15.4289433 -0.73
Glen Perkins Min 151 520 357 343.77 13.23 12.4694514 -0.74
Armando Galarraga Det 178.67 525 391 375.29 15.71 14.8068845 -0.75
CC Sabathia Cle 122.33 334 228 217.23 10.77 10.1508686 -0.75
Paul Byrd Cle 131 446 319 307.48 11.52 10.8577536 -0.75
Kyle Kendrick Phi 155.67 560 380 365.69 14.31 13.0764953 -0.76
Roy Oswalt Hou 208.67 617 436 416.75 19.25 17.5906733 -0.76
Tim Hudson Atl 142 435 317 302.69 14.31 13.0764953 -0.83
Jeremy Sowers Cle 121 409 279 266.73 12.27 11.5646386 -0.86
Justin Duchscherer Oak 141.67 409 308 292.97 15.03 14.1659754 -0.9
Ryan Rowland-Smith Sea 118.33 366 262 249.06 12.94 12.1961225 -0.93
Daisuke Matsuzaka Bos 167.67 449 327 306.07 20.93 19.7268041 -1.06
Tim Wakefield Bos 181 539 405 382.33 22.67 21.3667773 -1.06
Jesse Litsch Tor 176 569 407 382.14 24.86 23.4308815 -1.2
Chien-Ming Wang NYY 95 306 215 200.92 14.08 13.2705877 -1.26

There's a lot of great information here that's just begging for additional analysis.  For example, this data might show which pitchers give up the easiest balls in play to field.  Or we might look at why a defense performs so much differently for a given pitcher as opposed to his teammates (Chien-Ming Wang vs. Andy Pettite and Darrell Rasner for example).   I'm not going to cover those today, and just stick with the same high-level thoughts as the rest of the series.

One additional note; you'll see I went away from the rate stats per 4000 BIP and looking at the runs above average, and added a column describing the effect on ERA (more accurately, RA).  I can make those other numbers available if anyone wants, but I find that scaling results for pitchers to the common ERA scale makes the results more easily accessible.  A positive number means that the pitchers actual ERA was higher than expected, while a negative indicates the defense helped the pitcher do better than expected.

Fausto Carmona was definitely victimized by his defense this season.  He would have had been better than average has his defense performed as expected.  Instead he ended up with a 5.44 ERA and an 82 ERA+.  I'd expect some bounceback  next year from Fausto.  On the other end of the scale, the Yankees defense is much better when Chien-Ming Wang is pitching than anyone else.  This pattern has repeated itself for a few years now.   Boston's defense really helped out Wakefield and Dice-K.  That probably helps to explain why Dice-K was able to do so much better than his peripherals would suggest.