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Friday, September 25, 2009

Putting Linear Weights in Context, 2009 Edition

About a year ago, I wrote a post about putting linear Weights in context. The linked post has a detailed description of the hows and whys of doing this, so I'll just summarize the process briefly here. I found the spreadsheet I used to calculate that, so I figured I would re-run it for 2009.

Linear weights assigns run values to events based on their average impact to a team's run scoring. For example, a single is worth something like 0.47 to 0.49 runs on average. However, that same hit in context can actually be more or less valuable than that. If there is no one on base, a single is only worth about 0.29 runs on average. If the bases are loaded, that exact same single would be worth 1.38 runs on average.

A player can't control the context of when he bats, so looking at something like contextual linear weights should not be used as a way to evaluate a player's talent. However, it can be somewhat useful in looking at how the season has unfolded for that player and/or his team.

So, here's a table showing the Yankees' hitters, their PAs and triple slash stats, their wOBA, then two more columns. The first is context-neutral batting runs using linear weights (cnBR). The next column is also for batting runs, but this time adjusted for whatever baserunners are on base when the player hit (cBR). You can go even further into that by also accounting for the number of outs, but that changes my spreadsheet from eight worksheets to 24, so I don't do that. Fangraphs does calculate these using base out state, which I believe they call wRAA.

The final column (diff) is just cBR - cnBR. A positive number here means the player was better in situations with men on base, a negative number means that he was worse. I'm sure you can guess who's going to be have the largest difference without even looking at the table, but here it is.

One note, the data source I use for this (David Pinto's day by day database) does not split players by team, so players like Eric Hinske and Jerry Hairston Jr. will have their combined stats represented below. Also note that these numbers are NOT position-adjusted, and are compared to AVERAGE, not replacement level.

player pa avg obp slg wOBA cnBR cBR diff
Mark Teixeira 676 .292 .383 .567 .376 43.3 39.7 -3.6
Hideki Matsui 499 .278 .371 .525 .367 24.8 31.1 6.3
Alex Rodriguez 508 .283 .402 .519 .375 29.2 26.2 -3.0
Nick Swisher 573 .251 .368 .495 .354 21.3 22.9 1.6
Johnny Damon 598 .285 .366 .497 .358 22.1 21.3 -0.8
Jorge Posada 419 .283 .360 .529 .355 16.4 20.3 4.0
Derek Jeter 684 .329 .399 .460 .367 26.8 14.4 -12.4
Brett Gardner 257 .279 .354 .397 .327 1.2 6.7 5.5
Eric Hinske 211 .242 .351 .444 .331 4.2 4.4 0.2
Robinson Cano 645 .320 .350 .515 .352 19.2 0.5 -18.8
Freddy Guzman 1 .000 .000 .000 .000 0.0 0.0 0.0
Juan Miranda 1 1.000 1.000 1.000 .900 0.0 0.0 0.0
Shelley Duncan 10 .200 .200 .200 .180 -1.3 -0.7 0.6
Xavier Nady 29 .286 .310 .429 .303 -0.8 -0.9 -0.1
Ramiro Pena 108 .282 .315 .359 .292 -3.3 -1.7 1.5
Melky Cabrera 511 .273 .335 .416 .313 -1.5 -2.2 -0.7
Francisco Cervelli 89 .279 .292 .349 .276 -3.6 -2.4 1.2
Kevin Cash 28 .231 .250 .308 .235 -2.1 -2.6 -0.5
Cody Ransom 86 .190 .256 .329 .244 -6.0 -3.7 2.3
Angel Berroa 53 .143 .208 .184 .168 -7.1 -5.9 1.2
Jose Molina 136 .221 .294 .270 .259 -9.1 -7.2 1.9
Jerry Hairston 415 .251 .313 .397 .300 -5.1 -8.0 -3.0
Total 6103 .284 .361 .479 .366 168.8 152 -17


wOBA:Weighted on base average
cnBR:Context-neutral batting runs using linear weights
cBR:Batting runs adjusted for base runner state
diff:cBR - cnBR

I expected Cano to look pretty bad here, but not quite this bad. Jeter's number surprised me, considering he's so clutchy and all. At first I thought my calculations must have been wrong, but in actuality, the Yankees component stats on offense say they should have scored something like 20-30 runs more than they have to this point, which this data support (a cumulative total of -17).

On the positive side, you have Hideki Matsui, TSBG and Jorge Posada leading the pack. Most of the rest of the team is clustered right around average, which is what we should expect.

I totally forgot that Kevin Cash was a Yankee this year.

Just for the hell of it, here are the top 100 players in baseball sorted by cBR.

player pa avg obp slg wOBA cnBR cBR diff
Albert Pujols 660 .330 .447 .676 .399 77.5 79.6 2.2
Prince Fielder 671 .297 .408 .595 .385 55.1 58.6 3.6
Jason Bay 604 .267 .387 .549 .378 36.6 52.2 15.6
Joe Mauer 552 .371 .442 .606 .416 55.6 49.5 -6.1
Derrek Lee 595 .308 .392 .588 .388 43.1 49.2 6.2
Hanley Ramirez 621 .350 .414 .553 .387 46.7 48.6 1.9
Ryan Braun 659 .315 .384 .541 .380 38.5 46.7 8.2
Adam Dunn 627 .280 .410 .556 .381 45.9 45.4 -0.5
Chase Utley 651 .294 .412 .530 .390 45.4 45.2 -0.2
Kevin Youkilis 553 .302 .410 .542 .387 38.4 42.0 3.5
Matt Holliday 637 .312 .391 .520 .370 34.9 40.4 5.5
Mark Teixeira 676 .292 .383 .567 .376 43.3 39.7 -3.6
Miguel Cabrera 630 .332 .402 .556 .382 41.0 39.7 -1.3
Pablo Sandoval 590 .326 .381 .545 .366 34.2 34.7 0.5
Ryan Howard 660 .272 .353 .564 .359 32.0 34.1 2.1
Ben Zobrist 557 .287 .400 .523 .378 34.0 33.6 -0.4
Adrian Gonzalez 641 .274 .399 .554 .367 40.2 33.4 -6.8
Adam Lind 631 .300 .366 .541 .361 29.6 32.9 3.4
Joey Votto 503 .314 .408 .543 .380 34.5 32.0 -2.5
Hideki Matsui 499 .278 .371 .525 .367 24.8 31.1 6.3
Manny Ramirez 400 .298 .420 .553 .367 31.1 30.1 -0.9
Kendry Morales 591 .303 .349 .560 .352 26.1 29.9 3.8
Jayson Werth 628 .271 .376 .516 .360 29.5 29.9 0.4
Jason Bartlett 531 .319 .382 .494 .364 24.2 29.3 5.1
Torii Hunter 480 .303 .371 .521 .361 22.2 29.0 6.8
Justin Upton 553 .304 .371 .545 .369 28.1 28.9 0.9
Todd Helton 602 .317 .409 .480 .371 31.6 28.8 -2.7
Justin Morneau 590 .274 .363 .516 .345 24.0 28.6 4.6
Lance Berkman 521 .268 .395 .504 .357 26.9 27.4 0.5
Victor Martinez 636 .299 .377 .473 .355 21.9 27.3 5.4
Aramis Ramirez 325 .322 .391 .521 .377 17.0 26.5 9.5
Alex Rodriguez 508 .283 .402 .519 .375 29.2 26.2 -3.0
Carlos Pena 570 .227 .356 .537 .347 25.4 25.9 0.5
Chipper Jones 553 .268 .391 .436 .335 18.7 24.9 6.2
Bobby Abreu 636 .293 .393 .424 .348 19.5 24.6 5.1
Brian McCann 510 .284 .347 .497 .341 12.5 24.3 11.8
Andre Ethier 651 .279 .364 .525 .352 26.2 23.9 -2.3
Ichiro Suzuki 634 .355 .388 .472 .351 27.3 23.7 -3.5
Shin-Soo Choo 643 .303 .397 .481 .366 30.7 23.1 -7.6
Nick Swisher 573 .251 .368 .495 .354 21.3 22.9 1.6
Jim Thome 427 .248 .368 .485 .350 14.5 22.9 8.3
Casey McGehee 362 .302 .365 .503 .355 12.2 22.6 10.4
Yunel Escobar 553 .299 .378 .441 .349 12.2 22.4 10.2
Mark Reynolds 625 .266 .357 .560 .365 30.7 22.4 -8.3
Nick Johnson 558 .291 .421 .407 .364 21.5 22.3 0.8
Paul Konerko 596 .283 .354 .503 .347 19.1 21.4 2.3
Jason Kubel 532 .300 .370 .530 .356 24.7 21.4 -3.3
Johnny Damon 598 .285 .366 .497 .358 22.1 21.3 -0.8
Brian Roberts 670 .286 .355 .458 .336 15.8 21.2 5.4
Evan Longoria 632 .283 .364 .532 .352 24.3 21.2 -3.1
Andrew McCutchen 443 .281 .354 .472 .340 12.3 20.8 8.5
Matt Kemp 628 .304 .360 .500 .349 21.0 20.6 -0.4
Adam LaRoche 584 .283 .360 .505 .344 20.6 20.6 0.0
J.D. Drew 520 .267 .387 .495 .362 24.5 20.5 -4.0
Raul Ibanez 533 .277 .347 .565 .353 23.0 20.4 -2.6
Jorge Posada 419 .283 .360 .529 .355 16.4 20.3 4.0
Chone Figgins 686 .301 .399 .401 .354 19.7 20.0 0.3
Josh Willingham 466 .272 .380 .520 .368 22.2 19.9 -2.3
Ryan Zimmerman 651 .290 .361 .518 .352 23.6 19.9 -3.7
Luke Scott 476 .252 .338 .486 .331 10.8 19.9 9.1
Christopher Coghlan 520 .314 .385 .452 .356 18.3 19.8 1.5
Carlos Beltran 328 .332 .421 .512 .374 20.9 19.4 -1.5
Troy Tulowitzki 587 .288 .370 .538 .365 26.8 18.9 -7.8
Brad Hawpe 558 .285 .385 .506 .361 25.1 18.6 -6.6
Seth Smith 367 .302 .387 .528 .371 20.5 18.2 -2.4
Alberto Callaspo 592 .301 .355 .451 .334 9.8 18.0 8.2
David Wright 587 .310 .395 .448 .354 20.0 17.6 -2.5
Matt Diaz 396 .318 .391 .494 .371 17.0 17.4 0.4
Marco Scutaro 675 .282 .379 .409 .344 14.4 17.1 2.7
Aaron Hill 686 .286 .328 .492 .335 10.6 17.1 6.5
Billy Butler 629 .299 .358 .483 .345 15.8 16.4 0.6
Ryan Ludwick 506 .271 .334 .449 .324 4.9 16.4 11.4
Shane Victorino 648 .295 .363 .448 .342 15.6 16.4 0.8
Nate McLouth 538 .267 .355 .447 .337 10.6 16.2 5.6
Nelson Cruz 504 .262 .335 .525 .339 15.4 16.1 0.6
Russell Branyan 504 .251 .347 .520 .343 18.0 16.0 -1.9
James Loney 616 .288 .364 .413 .324 7.1 15.9 8.9
Carlos Lee 624 .304 .349 .498 .343 16.8 15.7 -1.1
Denard Span 611 .305 .388 .409 .347 15.4 14.9 -0.5
Michael Young 573 .322 .375 .523 .368 26.1 14.8 -11.3
Ian Kinsler 594 .249 .320 .481 .326 7.6 14.7 7.2
Derek Jeter 684 .329 .399 .460 .367 26.8 14.4 -12.4
Dustin Pedroia 666 .300 .374 .446 .347 16.3 14.0 -2.3
Miguel Montero 439 .298 .358 .479 .340 12.4 13.9 1.5
Rajai Davis 383 .319 .376 .435 .348 8.5 13.3 4.8
Garrett Jones 310 .301 .371 .594 .374 20.3 13.1 -7.2
Felipe Lopez 637 .309 .380 .429 .345 16.9 13.0 -3.9
Marlon Byrd 569 .282 .325 .468 .322 5.8 12.8 7.0
Scott Rolen 509 .308 .367 .452 .345 15.0 12.6 -2.4
Cody Ross 598 .273 .323 .473 .326 3.2 12.1 8.9
Lyle Overbay 465 .269 .374 .470 .345 15.6 12.1 -3.5
Nick Markakis 668 .293 .344 .448 .332 9.2 12.1 2.8
David DeJesus 619 .283 .349 .436 .332 7.5 11.9 4.4
Asdrubal Cabrera 545 .305 .360 .436 .336 7.5 11.8 4.3
Adam Jones 519 .277 .335 .457 .326 4.3 11.6 7.3
Casey Blake 554 .280 .365 .472 .339 16.2 11.2 -5.0
Dan Uggla 629 .240 .353 .458 .337 13.7 10.7 -3.1
Nolan Reimold 411 .279 .365 .466 .348 11.3 10.7 -0.7
Jonny Gomes 302 .268 .341 .543 .351 10.4 10.6 0.2
Michael Cuddyer 599 .276 .336 .519 .343 13.6 10.0 -3.6


When I run these esoteric type stats, there are always names that jump out at me. In this case, it's Jason Bay.

And Albert Pujols is so good in the National League, he could probably hit league average in the AL.

One last table, showing players with an ABS(diff) >= 5.0.

player pa avg obp slg wOBA cnBR cBR diff
Jason Bay 604 .267 .387 .549 .378 36.6 52.2 15.6
Aubrey Huff 571 .245 .310 .394 .289 -11.2 0.9 12.1
Brian McCann 510 .284 .347 .497 .341 12.5 24.3 11.8
Ryan Ludwick 506 .271 .334 .449 .324 4.9 16.4 11.4
Gary Matthews Jr. 343 .247 .335 .357 .300 -4.9 5.8 10.7
Casey McGehee 362 .302 .365 .503 .355 12.2 22.6 10.4
Yunel Escobar 553 .299 .378 .441 .349 12.2 22.4 10.2
Pedro Feliz 584 .262 .308 .381 .290 -13.7 -3.5 10.2
Edgar Renteria 505 .250 .307 .328 .273 -21.3 -11.8 9.5
Aramis Ramirez 325 .322 .391 .521 .377 17.0 26.5 9.5
Luke Scott 476 .252 .338 .486 .331 10.8 19.9 9.1
Cody Ross 598 .273 .323 .473 .326 3.2 12.1 8.9
James Loney 616 .288 .364 .413 .324 7.1 15.9 8.9
David Eckstein 515 .260 .320 .333 .287 -15.4 -6.5 8.9
Andrew McCutchen 443 .281 .354 .472 .340 12.3 20.8 8.5
Kaz Matsui 481 .252 .301 .354 .280 -15.3 -7.0 8.4
Jim Thome 427 .248 .368 .485 .350 14.5 22.9 8.3
Alberto Callaspo 592 .301 .355 .451 .334 9.8 18.0 8.2
Ryan Braun 659 .315 .384 .541 .380 38.5 46.7 8.2
Kurt Suzuki 581 .269 .308 .411 .301 -9.4 -1.5 7.9
Randy Winn 571 .260 .317 .353 .288 -13.7 -6.1 7.6
Adam Jones 519 .277 .335 .457 .326 4.3 11.6 7.3
Ian Kinsler 594 .249 .320 .481 .326 7.6 14.7 7.2
Kevin Kouzmanoff 556 .257 .304 .421 .297 -12.0 -4.9 7.1
Jason Giambi 350 .204 .349 .391 .320 1.0 8.1 7.0
Marlon Byrd 569 .282 .325 .468 .322 5.8 12.8 7.0
Josh Anderson 272 .240 .279 .306 .258 -17.0 -10.1 6.9
Torii Hunter 480 .303 .371 .521 .361 22.2 29.0 6.8
Nick Punto 385 .232 .332 .291 .285 -12.1 -5.6 6.6
Aaron Hill 686 .286 .328 .492 .335 10.6 17.1 6.5
Hideki Matsui 499 .278 .371 .525 .367 24.8 31.1 6.3
Chipper Jones 553 .268 .391 .436 .335 18.7 24.9 6.2
Derrek Lee 595 .308 .392 .588 .388 43.1 49.2 6.2
Rod Barajas 425 .231 .264 .409 .270 -14.3 -8.2 6.1
Chase Headley 574 .264 .340 .402 .316 -3.4 2.5 6.0
Mark DeRosa 549 .256 .324 .447 .320 1.5 7.4 5.9
Nate McLouth 538 .267 .355 .447 .337 10.6 16.2 5.6
Brett Gardner 257 .279 .354 .397 .327 1.2 6.7 5.5
Matt Holliday 637 .312 .391 .520 .370 34.9 40.4 5.5
Brian Roberts 670 .286 .355 .458 .336 15.8 21.2 5.4
Victor Martinez 636 .299 .377 .473 .355 21.9 27.3 5.4
Gabe Gross 311 .239 .341 .373 .309 -1.7 3.5 5.3
Brandon Inge 585 .232 .323 .418 .314 -3.2 2.0 5.2
Khalil Greene 187 .205 .278 .355 .265 -8.3 -3.1 5.1
Casey Kotchman 404 .271 .342 .391 .306 -1.8 3.3 5.1
Jason Bartlett 531 .319 .382 .494 .364 24.2 29.3 5.1
Bobby Abreu 636 .293 .393 .424 .348 19.5 24.6 5.1
Jeff Mathis 250 .206 .288 .309 .265 -12.1 -7.1 5.0
Gerardo Enrique Parra 462 .292 .327 .408 .310 -6.4 -1.3 5.0
Alex Gonzalez 388 .239 .276 .354 .259 -17.5 -12.5 5.0
Carlos Ruiz 363 .253 .353 .423 .316 3.8 8.7 5.0
Placido Polanco 616 .284 .330 .404 .312 -5.2 -0.2 5.0
Casey Blake 554 .280 .365 .472 .339 16.2 11.2 -5.0
Rafael Furcal 641 .264 .331 .367 .303 -10.5 -15.6 -5.1
Wladimir Balentien 279 .233 .308 .382 .290 -5.8 -11.1 -5.3
Yadier Molina 527 .291 .366 .383 .328 -1.9 -7.2 -5.3
Chris Dickerson 295 .277 .373 .375 .329 2.8 -2.8 -5.6
Brendan Harris 436 .262 .310 .364 .290 -14.2 -20.2 -6.0
Luis Valbuena 359 .234 .284 .387 .279 -12.7 -18.7 -6.0
Fernando Tatis 351 .267 .328 .415 .308 -3.4 -9.5 -6.0
Curtis Granderson 652 .247 .328 .447 .319 6.0 -0.1 -6.0
J.J. Hardy 453 .228 .300 .356 .283 -16.3 -22.3 -6.1
Joe Mauer 552 .371 .442 .606 .416 55.6 49.5 -6.1
Dexter Fowler 472 .270 .371 .414 .337 9.0 2.9 -6.1
Carl Crawford 640 .305 .363 .452 .345 15.3 8.7 -6.6
A.J. Pierzynski 516 .307 .339 .436 .320 1.1 -5.5 -6.6
Brad Hawpe 558 .285 .385 .506 .361 25.1 18.6 -6.6
Cameron Maybin 159 .218 .296 .345 .272 -5.8 -12.4 -6.6
Adrian Gonzalez 641 .274 .399 .554 .367 40.2 33.4 -6.8
Garrett Jones 310 .301 .371 .594 .374 20.3 13.1 -7.2
Ryan Hanigan 275 .268 .360 .339 .299 -2.8 -10.0 -7.3
Shin-Soo Choo 643 .303 .397 .481 .366 30.7 23.1 -7.6
Troy Tulowitzki 587 .288 .370 .538 .365 26.8 18.9 -7.8
Mike Napoli 410 .268 .346 .481 .340 9.6 1.7 -8.0
Skip Schumaker 556 .304 .363 .396 .329 5.3 -3.0 -8.2
Mark Reynolds 625 .266 .357 .560 .365 30.7 22.4 -8.3
Dioner Navarro 384 .219 .260 .319 .247 -26.5 -34.9 -8.4
Fred Lewis 323 .265 .356 .403 .321 2.3 -6.3 -8.6
Jeff Francoeur 597 .277 .307 .411 .293 -10.1 -19.0 -9.0
Vernon Wells 639 .262 .315 .402 .300 -10.4 -20.1 -9.7
Carlos Gonzalez 283 .280 .353 .520 .348 10.8 1.0 -9.8
Michael Young 573 .322 .375 .523 .368 26.1 14.8 -11.3
Derek Jeter 684 .329 .399 .460 .367 26.8 14.4 -12.4
Robinson Cano 645 .320 .350 .515 .352 19.2 0.5 -18.8


Again, I'll reiterate that this doesn't necessarily tell us anything about the skill of these players. All it tells us is the timing of their hits/walks/outs with respect to the state of baserunners when they occurred. It doesn't care about the score of the game, or how many outs there are. A two run single in the first inning of a 15-0 blowout would be worth the same as a two run single that turned a 3-2 deficit into a 4-3 walkoff win. Also, as I stated earlier, these are not position-adjusted and are compared to average, not replacement level. So knock down 1B and corner OFs some and boost catchers and middle infielders.

--Posted at 6:29 am by SG / 44 Comments | - (151)


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