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September 7, 2001

Aim For The Head

Quality of Opposition

by Keith Woolner

This week's question comes from Brian Canfield:

While watching my beloved Rangers' Rob Bell get shellacked by the Yankees, it occurred to me that the season that Alex Rodriguez is having is even more impressive when you realize that he doesn't get to hit against the Rangers' pitching staff. Conversely, the stats of the Mariners, A's, and Angels hitters might be a bit less impressive since they get to face the Rangers' pitchers so many times, especially with the new unbalanced schedule, and don't face their own staffs.

Has there been any attempt to take into account the effect on a hitter's stats resulting from his not hitting against his own pitchers? This would obviously work the other way as well by looking at pitchers in relation to the hitters they don't face.

Thanks for a great question, Brian.

It's true that hitters on a bad pitching team get a slight benefit from not having to face their own pitchers. Some analysts have recognized it and incorporated it into their work. For example, Total Baseball uses the fact that hitters don't face their own pitchers in computing their park factors (TB computes separate factors for pitchers and hitters where the imbalance does make a difference, rather than a single park factor used in most cases, where it doesn't).

However, if we're going to go down this path of adjusting hitting stats for one's teammates' pitching quality, we probably ought to consider additional factors. Vagaries of the schedule will mean that some pitchers will face a given opponent more often than their teammates. As Brian notes above, the unbalanced schedule may amplify this effect. The actual players in the lineup vary from day to day as well. A team that plays its rival in consecutive weeks (like the Yankees and Red Sox are about to do) may have a pitcher that completely misses a star hitter who happens to be on the 15-day DL during that stretch.

The number of times a batter faces a pitcher should be considered too. A single pinch-hit appearance needs to be weighted in the "typical opponent" average less than a leadoff hitter who comes to the plate five times.

Let's consider the simple case of a pitcher facing two batters:

A: 5 PA, season averages: .300/.400/.500
B: 2 PA, season averages: .250/.350/.400

Simplistically, you could say that the average of the two batters faced is .275/.375/.450, but that neglects the fact that the pitcher faced batter A more than twice as often. Weighting by the actual number of PA, that combination yields .285/.385/.471, which is a more realistic assessment of the average batter this pitcher faced.

(Side note to the mathematically-inclined reader: I oversimplified in the previous paragraph because AVG and SLG are denominated in AB rather than PA, yet I'm weighting them by PA. In the data that follows, I have converted everything to events per plate appearance, and then back to the familiar batting average and slugging average scales afterwards.)

Though I don't have detailed and complete batter-pitcher breakdowns at this stage of the season, I do have enough data to be able to do a reasonable approximation. We can take each batter's plate appearance total, and allocate it proportionally among the opposing pitchers, according to the fraction of innings in that game that they pitched. For example, in the Braves' September 2 game, Marcus Giles batted five times. The opposing pitchers were Kevin Tapani who threw six innings, and Ron Mahay who pitched two (the Braves won, so there was no ninth-inning pitcher for the Cubs). Without knowing exactly who batted when, we can assign approximate PA shares as follows:

5 PA * 6 IP Total IP = 3.75 of Giles' PA to Tapani
5 PA * 2 IP Total IP = 1.25 of Giles' PA to Mahay

Over the course of a season, this will be a reasonably good (though not perfect) estimate of the plate appearances for each batter and pitcher. Using this approximation, we can weight a batter's full-season rates of production by the estimated number of PA in which he faced a pitcher to get that pitcher's average opposing batter (as in our simple case with A and B above).

I've done just that for all batters and pitchers in 2001 (through 9/2) and calculated the average quality of opponent for each. I've presented data for pitchers with at least 20 games started, and batters with at least 300 PA below. First the pitchers:


Pitcher              Team  GS     IP   BFP   AVG    OBP    SLG    OPS

Woody Williams (SD) SDN 23 145.0 632 .267 .338 .440 779 Steve Sparks DET 27 183.1 790 .268 .340 .435 774 Pat Rapp ANA 27 161.1 687 .269 .339 .434 773 Aaron Sele SEA 28 183.2 771 .267 .338 .435 773 Ramon Ortiz ANA 27 175.0 766 .267 .337 .434 771 Jamie Moyer SEA 27 171.1 699 .266 .335 .434 769 Tanyon Sturtze TBA 22 144.1 694 .265 .336 .432 768 Elmer Dessens CIN 28 169.2 715 .264 .334 .435 768 Jeff Suppan KCA 28 180.0 777 .267 .338 .430 768 Rocky Biddle CHA 20 107.2 547 .264 .334 .434 768 Chris Holt DET 22 127.0 663 .264 .336 .431 767 Eric Milton MIN 28 181.0 781 .267 .335 .431 766 Darren Oliver TEX 24 130.2 590 .268 .340 .426 766 Brad Radke MIN 27 186.0 761 .265 .333 .433 765 Kevin Jarvis SDN 28 169.1 711 .261 .333 .432 765 David Cone BOS 20 109.0 496 .266 .335 .429 765 Denny Neagle COL 25 143.0 636 .260 .333 .431 764 Cory Lidle OAK 25 158.0 647 .266 .335 .429 764 Jarrod Washburn ANA 25 163.2 688 .265 .334 .430 764 Bartolo Colon CLE 28 185.2 783 .267 .337 .427 764 Bryan Rekar TBA 22 123.1 551 .263 .334 .428 762 Frank Castillo BOS 21 107.1 455 .268 .337 .426 762 Tim Hudson OAK 29 196.2 815 .267 .336 .426 762 Esteban Loaiza TOR 27 164.2 747 .265 .334 .428 762 Mark Mulder OAK 29 196.1 791 .266 .333 .429 762 Joe Mays MIN 28 191.2 789 .268 .335 .426 761 Eric Gagne LAN 23 131.1 597 .262 .332 .430 761 Chad Durbin KCA 24 150.2 650 .265 .335 .425 760 Barry Zito OAK 29 176.1 744 .267 .334 .426 759 Chris Carpenter TOR 28 177.1 772 .264 .335 .424 759 Paul Abbott SEA 23 138.0 600 .263 .332 .427 759 Jimmy Anderson PIT 28 163.0 745 .261 .331 .428 759 Kevin Tapani CHN 26 153.0 661 .262 .332 .426 758 Doug Davis TEX 25 154.0 692 .266 .337 .422 758 Jason Johnson BAL 27 167.0 717 .264 .333 .426 758 Ismael Valdes ANA 22 136.1 569 .265 .333 .424 757 Pedro Astacio COL 22 141.0 617 .258 .333 .424 757 Bobby J. Jones SDN 28 172.2 771 .261 .330 .427 757 C.C Sabathia CLE 27 144.2 615 .264 .332 .424 757 Ben Sheets MIL 21 129.2 559 .261 .332 .424 756 Kenny Rogers TEX 20 120.2 552 .263 .333 .424 756 Jeff Weaver DET 28 196.0 838 .263 .333 .423 756 Livan Hernandez SFN 29 195.0 868 .262 .334 .422 756 Roger Clemens NYA 28 189.0 783 .265 .334 .422 756 Luke Prokopec LAN 21 125.2 543 .259 .334 .422 755 Robert Person PHI 28 175.0 733 .262 .332 .423 755 Curt Schilling ARI 30 219.2 873 .263 .333 .422 755 Sidney Ponson BAL 23 138.1 605 .263 .331 .424 755 Mark Buehrle CHA 26 181.2 721 .266 .336 .419 755 Tony Armas Jr. MON 29 173.1 745 .261 .331 .424 755 Mike Thurman MON 21 115.1 524 .260 .333 .422 755 Todd Ritchie PIT 28 176.0 758 .260 .330 .425 755 Scott Schoeneweis ANA 27 174.1 771 .262 .334 .421 754 Hideo Nomo BOS 27 163.2 692 .264 .333 .421 754 Jason Bere CHN 26 158.0 659 .261 .331 .423 754 Albie Lopez (TB) TBA 20 124.2 567 .263 .329 .425 754 Shawn Chacon COL 23 135.0 602 .260 .330 .424 754 Jose Mercedes BAL 27 161.2 741 .264 .332 .422 754 Mike Mussina NYA 29 196.2 791 .263 .333 .420 753 Matt Clement FLO 27 152.3 687 .260 .332 .421 753 Kevin Appier NYN 28 171.3 717 .262 .330 .423 753 Chris Reitsma CIN 27 166.0 725 .260 .330 .423 753 Russ Ortiz SFN 28 186.2 779 .262 .334 .419 753 Freddy Garcia SEA 28 195.2 808 .262 .334 .418 752 Matt Morris SLN 28 182.2 774 .261 .330 .422 752 Kirk Rueter SFN 28 161.0 698 .258 .328 .424 752 Dave Burba CLE 25 129.0 644 .264 .331 .421 752 Rick Reed (NY) NYN 20 134.2 531 .260 .329 .423 752 Jon Lieber CHN 28 196.2 799 .262 .330 .422 752 Ryan Rupe TBA 22 120.1 543 .261 .332 .419 751 Glendon Rusch NYN 28 148.2 662 .262 .329 .422 751 Kerry Wood CHN 23 144.0 617 .258 .330 .420 750 Andy Pettitte NYA 26 179.0 755 .266 .333 .418 750 Tom Glavine ATL 29 180.1 766 .261 .330 .420 750 Scott Elarton HOU 20 109.2 499 .260 .329 .421 750 Rick Helling TEX 29 182.2 800 .263 .332 .418 750 Brian Anderson ARI 21 121.0 523 .259 .331 .419 749 Chan Ho Park LAN 29 198.0 816 .257 .331 .419 749 Randy Johnson ARI 29 207.0 846 .258 .327 .422 749 Jimmy Haynes MIL 28 165.1 713 .258 .331 .418 749 Joey Hamilton TOR 22 122.1 554 .263 .331 .417 748 Dustin Hermanson SLN 28 166.1 716 .259 .327 .421 748 Mike Hampton COL 28 179.2 792 .257 .329 .419 748 John Burkett ATL 29 190.1 775 .259 .328 .419 747 Ted Lilly NYA 20 98.0 463 .264 .333 .413 747 Shane Reynolds HOU 23 150.1 638 .261 .330 .416 747 Brad Penny FLO 26 170.2 698 .259 .330 .417 747 Wade Miller HOU 27 177.1 729 .258 .326 .420 746 Darryl Kile SLN 29 196.2 827 .259 .328 .418 746 Steve Trachsel NYN 23 137.0 579 .256 .328 .417 745 Greg Maddux ATL 29 206.0 821 .257 .329 .416 745 Shawn Estes SFN 24 145.1 637 .255 .328 .416 744 Ryan Dempster FLO 29 191.1 851 .258 .329 .414 743 Javier Vazquez MON 30 210.2 849 .256 .329 .413 741 A.J. Burnett FLO 22 139.2 597 .257 .329 .412 741 Jamey Wright MIL 27 164.2 729 .256 .327 .413 740 Omar Daal PHI 27 157.2 685 .257 .326 .413 739 Julian Tavarez CHN 27 146.2 646 .255 .323 .414 737 Al Leiter NYN 24 154.0 642 .257 .325 .411 736

Remember here than a high average opponent's OPS means the pitcher has been facing tougher competition (i.e., his stats may be slightly worse than they should be). It's perhaps not a surprise that there are mostly AL pitchers at the high end of the list, and NL pitchers at the low end, given the presence of the DH vs. pitchers hitting. Can part of Woody Williams' improvement with the Cardinals be attributed to bad luck of the draw in facing stronger opponents when he was a Padre?

One caveat worth mentioning is that the handedness of the pitcher (or batter) could skew the results, particularly for lefties because of platooning. For example, a lefty-killer may get to start against a southpaw starter, and hit him harder than his season stats would indicate.

Now the batters:


BATTER               Team   PA   AVG    OBP    SLG    OPS

Juan Gonzalez CLE 515 .268 .340 .433 772 Russ Branyan CLE 320 .267 .340 .427 767 Roberto Alomar CLE 569 .266 .338 .429 767 Omar Vizquel CLE 584 .266 .337 .429 766 Jose Valentin CHA 412 .268 .336 .429 766 Marty Cordova CLE 385 .266 .337 .429 766 Einar Diaz CLE 398 .267 .336 .430 765 Julio Lugo HOU 489 .262 .334 .431 765 Kenny Lofton CLE 472 .266 .335 .429 765 Richard Hidalgo HOU 497 .262 .334 .430 765 Ellis Burks CLE 437 .266 .336 .428 764 Jim Thome CLE 540 .266 .336 .428 764 Brian Daubach BOS 378 .266 .335 .429 764 Lance Berkman HOU 575 .261 .333 .430 763 Brad Ausmus HOU 377 .262 .334 .429 763 Chris Singleton CHA 340 .266 .335 .428 763 Reggie Sanders ARI 416 .261 .332 .430 763 Jeff Bagwell HOU 606 .261 .333 .429 763 Craig Biggio HOU 600 .261 .333 .429 762 Moises Alou HOU 495 .262 .332 .430 762 Paul Konerko CHA 536 .265 .335 .427 762 Magglio Ordonez CHA 559 .265 .334 .427 761 Royce Clayton CHA 381 .265 .334 .427 761 Ray Lankford (STL) SLN 313 .260 .330 .428 758 Tony Womack ARI 413 .259 .331 .427 758 Ray Durham CHA 570 .265 .334 .424 758 Jose Offerman BOS 499 .265 .333 .425 757 Geoff Jenkins MIL 340 .261 .332 .425 757 Carlos Lee CHA 514 .264 .333 .424 757 Gabe Kapler TEX 467 .262 .332 .424 756 David Segui BAL 345 .263 .331 .425 756 Carlos Guillen SEA 468 .265 .333 .422 755 Vinny Castilla (HOU) HOU 376 .260 .331 .424 754 Henry Blanco MIL 312 .260 .331 .423 754 Cristian Guzman MIN 442 .264 .334 .420 754 Dan Wilson SEA 340 .264 .331 .423 754 Frank Catalanotto TEX 422 .262 .331 .423 754 Jay Bell ARI 454 .259 .330 .424 754 Frank Menechino OAK 505 .262 .331 .423 754 Matt Williams ARI 342 .259 .330 .424 754 Eric Young CHN 565 .258 .330 .424 754 Shea Hillenbrand BOS 411 .263 .331 .422 753 Alex Ochoa (CIN) CIN 377 .259 .329 .424 753 Ichiro Suzuki SEA 631 .264 .331 .421 753 Ron Coomer CHN 358 .259 .329 .424 752 Bret Boone SEA 586 .263 .331 .421 752 Juan Encarnacion DET 448 .261 .330 .422 752 Manny Ramirez BOS 556 .264 .331 .422 752 Trot Nixon BOS 518 .263 .331 .421 752 Jacque Jones MIN 444 .262 .333 .419 752 Randy Velarde (TEX) TEX 331 .262 .332 .420 752 David Bell SEA 470 .264 .332 .420 752 Carl Everett BOS 427 .263 .330 .422 752 Brad Fullmer TOR 508 .262 .333 .419 752 John Olerud SEA 580 .263 .331 .420 751 Ramon Hernandez OAK 427 .262 .332 .419 751 Sammy Sosa CHN 595 .257 .329 .422 751 Jason Giambi OAK 586 .262 .331 .420 751 Terrence Long OAK 586 .262 .331 .420 751 Mike Cameron SEA 524 .263 .331 .419 751 Johnny Damon OAK 627 .262 .331 .420 750 Miguel Tejada OAK 581 .261 .330 .420 750 Jose Hernandez MIL 498 .259 .329 .421 750 J.D. Drew SLN 330 .258 .328 .422 750 Rafael Furcal ATL 355 .259 .328 .423 750 Rafael Palmeiro TEX 606 .260 .329 .421 750 Ricky Gutierrez CHN 498 .257 .328 .422 750 Adam Kennedy ANA 451 .262 .330 .419 750 Brady Anderson BAL 427 .261 .329 .421 750 Luis Gonzalez ARI 611 .257 .328 .421 750 Damian Miller ARI 369 .258 .329 .421 750 Mark McLemore SEA 416 .262 .330 .419 749 Jeremy Giambi OAK 377 .261 .330 .419 749 Chris Richard BAL 441 .260 .329 .420 749 Mike Young TEX 310 .259 .328 .421 749 Greg Vaughn TBA 550 .262 .330 .419 749 Javy Lopez ATL 424 .257 .328 .421 749 Dee Brown KCA 329 .264 .331 .418 749 Jerry Hairston Jr. BAL 503 .260 .329 .420 749 Garret Anderson ANA 593 .262 .331 .418 749 Alex Rodriguez TEX 624 .260 .329 .420 749 Tony Clark DET 470 .260 .329 .420 749 Tim Salmon ANA 485 .262 .331 .418 749 Dante Bichette BOS 390 .263 .331 .417 749 Troy Glaus ANA 601 .262 .331 .418 749 Mike Matheny SLN 353 .257 .328 .421 748 Melvin Mora BAL 495 .260 .329 .419 748 Matt Stairs CHN 360 .257 .327 .421 748 Fred McGriff (TB) TBA 385 .262 .332 .416 748 Jason LaRue CIN 350 .258 .329 .420 748 Benny Agbayani NYN 338 .258 .330 .418 748 Darin Erstad ANA 611 .262 .330 .418 748 Aubrey Huff TBA 361 .260 .330 .418 748 Adrian Beltre LAN 410 .257 .327 .420 748 Ben Grieve TBA 532 .261 .330 .418 748 Todd Walker (COL) COL 318 .257 .325 .422 747 Mark Loretta MIL 354 .259 .328 .419 747 Steve Finley ARI 469 .257 .328 .419 747 Paul LoDuca LAN 417 .257 .326 .421 747 Alex Cora LAN 386 .256 .326 .421 747 Aaron Boone CIN 380 .257 .329 .418 747 Brian Jordan ATL 497 .258 .326 .421 747 Jeff Kent SFN 585 .256 .327 .420 747 Mike Lansing BOS 360 .262 .330 .417 747 David Eckstein ANA 551 .261 .331 .416 747 Ron Belliard MIL 402 .257 .329 .418 747 Mark Grudzielanek LAN 491 .257 .327 .420 746 Andruw Jones ATL 591 .257 .326 .420 746 Troy O'Leary BOS 338 .259 .329 .417 746 Fernando Vina SLN 590 .257 .327 .420 746 Jeromy Burnitz MIL 542 .258 .328 .418 746 Eric Chavez OAK 501 .260 .329 .417 746 Jose Cruz Jr. TOR 517 .260 .331 .415 746 Marquis Grissom LAN 374 .257 .325 .420 746 Shawn Green LAN 592 .256 .326 .419 746 Corey Koskie MIN 545 .260 .331 .415 746 Cal Ripken Jr. BAL 409 .260 .329 .417 746 Luis Rivas MIN 516 .260 .331 .415 746 Richie Sexson MIL 554 .257 .328 .418 746 Ivan Rodriguez TEX 470 .259 .327 .419 746 Chipper Jones ATL 576 .256 .326 .419 746 Dmitri Young CIN 499 .256 .327 .418 745 Cliff Floyd FLO 533 .258 .325 .420 745 Albert Pujols SLN 565 .257 .327 .419 745 Matt Lawton (MIN) MIN 444 .261 .331 .414 745 Marvin Benard SFN 356 .255 .326 .419 745 Edgardo Alfonzo NYN 425 .257 .328 .417 745 Mark Grace ARI 476 .256 .326 .419 745 Sean Casey CIN 524 .256 .327 .418 745 Pokey Reese CIN 440 .257 .327 .418 745 Doug Mientkiewicz MIN 555 .260 .330 .414 745 Alex Gonzalez TOR 591 .260 .330 .415 745 Armando Rios (SF) SFN 352 .254 .326 .419 745 Darrin Fletcher TOR 398 .260 .330 .415 745 Craig Counsell ARI 436 .256 .326 .418 745 Raul Mondesi TOR 578 .260 .330 .414 745 Edgar Martinez SEA 489 .262 .330 .414 744 Calvin Murray SFN 302 .256 .327 .418 744 Jeff Conine BAL 487 .259 .328 .417 744 Eric Owens FLO 395 .257 .326 .418 744 B.J. Surhoff ATL 448 .255 .324 .420 744 Scott Spiezio ANA 408 .261 .330 .414 744 Rich Aurilia SFN 571 .255 .326 .418 744 Carlos Delgado TOR 594 .260 .330 .414 744 Damion Easley DET 541 .258 .328 .416 744 Robin Ventura NYN 474 .257 .328 .416 744 Ken Griffey Jr. CIN 314 .256 .328 .416 744 Tsuyoshi Shinjo NYN 344 .258 .327 .416 744 Abraham Nunez PIT 320 .257 .325 .418 743 Rey Ordonez NYN 421 .257 .328 .416 743 Edgar Renteria SLN 450 .257 .326 .418 743 Bobby Higginson DET 522 .259 .327 .416 743 Jose Vidro MON 426 .256 .327 .416 743 Devon White MIL 352 .257 .327 .416 743 Eric Karros LAN 405 .256 .326 .417 743 Craig Paquette SLN 303 .257 .326 .417 743 Alfonso Soriano NYA 521 .260 .329 .414 743 Neifi Perez (COL) COL 399 .257 .326 .417 743 Mike Piazza NYN 484 .256 .328 .415 743 Shannon Stewart TOR 592 .259 .329 .414 743 Alex Gonzalez FLO 497 .257 .325 .418 743 Ramon Martinez SFN 364 .256 .326 .417 743 Gary Sheffield LAN 514 .255 .327 .416 742 Derrek Lee FLO 518 .257 .324 .418 742 Luis Castillo FLO 559 .256 .324 .418 742 Chuck Knoblauch NYA 526 .260 .329 .414 742 John Vander Wal (PIT) PIT 361 .256 .327 .415 742 Jose Macias DET 406 .259 .328 .413 741 Kevin Millar FLO 394 .257 .325 .417 741 Jim Edmonds SLN 506 .256 .325 .416 741 Roger Cedeno DET 537 .258 .327 .414 741 Randy Winn TBA 381 .259 .327 .414 741 Bernie Williams NYA 547 .259 .328 .413 741 Mike Darr SDN 326 .254 .326 .415 741 Benito Santiago SFN 428 .255 .326 .415 741 Scott Brosius NYA 411 .260 .328 .413 741 Barry Bonds SFN 552 .253 .325 .416 741 Chris Stynes BOS 328 .259 .328 .413 741 Deivi Cruz DET 367 .258 .327 .414 741 Todd Zeile NYN 525 .256 .326 .414 740 Paul O'Neill NYA 541 .259 .328 .412 740 Damian Jackson SDN 418 .255 .327 .413 740 A.J. Pierzynski MIN 344 .258 .329 .411 740 Placido Polanco SLN 487 .255 .326 .414 740 Joe Randa KCA 542 .260 .327 .413 740 Jack Wilson PIT 309 .256 .322 .418 740 Carlos Beltran KCA 568 .260 .327 .412 740 Travis Lee PHI 545 .256 .324 .415 739 Larry Walker COL 512 .255 .324 .415 739 Mike Lowell FLO 512 .257 .324 .415 739 Derek Jeter NYA 612 .258 .328 .411 739 Shane Halter DET 390 .257 .325 .413 738 Pat Burrell PHI 537 .256 .324 .414 738 Robert Fick DET 392 .258 .327 .411 738 Torii Hunter MIN 501 .258 .329 .409 738 Jason Tyner TBA 321 .257 .326 .412 738 Brian Giles PIT 563 .255 .324 .414 738 Luis Alicea KCA 383 .259 .327 .411 738 Charles Johnson FLO 420 .256 .323 .415 738 Bobby Abreu PHI 594 .255 .324 .414 738 Jermaine Dye (KC) KCA 409 .259 .326 .412 738 Jason Kendall PIT 571 .254 .324 .413 738 Scott Rolen PHI 560 .255 .324 .414 738 Aramis Ramirez PIT 546 .254 .324 .413 738 Mike Sweeney KCA 525 .259 .327 .411 737 Tino Martinez NYA 557 .258 .327 .410 737 Marlon Anderson PHI 464 .255 .324 .414 737 Todd Helton COL 574 .255 .324 .413 737 Michael Barrett MON 439 .255 .324 .413 737 Jimmy Rollins PHI 602 .255 .324 .413 737 Preston Wilson FLO 407 .255 .322 .416 737 Phil Nevin SDN 537 .254 .325 .412 737 Lee Stevens MON 535 .255 .325 .412 737 Bubba Trammell SDN 444 .254 .324 .413 737 Juan Pierre COL 547 .255 .324 .413 736 Ryan Klesko SDN 572 .254 .324 .412 736 Rey Sanchez (KC) KCA 407 .259 .326 .411 736 Doug Glanville PHI 568 .255 .323 .413 736 Orlando Cabrera MON 569 .254 .325 .411 735 Mark Kotsay SDN 447 .254 .324 .412 735 Vladimir Guerrero MON 566 .254 .324 .410 735 Kevin Young PIT 423 .253 .323 .411 734 Jorge Posada NYA 490 .257 .325 .408 734 Jeff Cirillo COL 478 .253 .322 .411 733 David Justice NYA 368 .256 .326 .407 733 Rickey Henderson SDN 387 .253 .322 .411 733 Denny Hocking MIN 318 .257 .326 .406 732 Geoff Blum MON 416 .253 .323 .409 732 Ben Davis SDN 456 .253 .323 .409 732 Mark Quinn KCA 377 .257 .322 .406 728 Peter Bergeron MON 332 .253 .323 .405 728

I was stunned to see all of the Cleveland Indians stacked near the top, although for a set lineup that stays healthy that's not too surprising. The Indians have had 89 games in which Juan Gonzalez, Roberto Alomar, Jim Thome, Omar Vizquel, and Kenny Lofton were all in the game. The unbalanced schedule also means that they are in a division that doesn't have a single team among the top six ERAs in the American League. Practically the whole division has a below-average pitching staff.

Of course, there is also an effect in that the pitchers who face the Indians more often (and thus are more heavily weighted in the averages above) also have their season stats hurt by facing the strong Cleveland lineup. Taking the full-season averages smoothes this out somewhat, but it's probably worth a few points of OPS by itself. Another approach would be to remove the games for that player or team from the pitcher's season totals, and compute it.

Mark Quinn and Peter Bergeron have both played below expectations this year, and the table above may give a reason for some small portion of that disappointment. They have faced tougher pitching than any other player in their respective leagues.

So, back to Brian's original question, what's the magnitude of this effect? Well, if we assume that the OPS differences listed above are comparable to what we'd find if we adjusted for park, and for the "self-batting" influence on opposing pitcher stats, the maximum effect on pitchers seems to be around 6-7% at the extremes. However, half the pitchers fall within +/- 2%, and for the most part it probably does not have a significant impact on our estimates of pitcher value. The results are comparable for batters.

Keith Woolner is an author of Baseball Prospectus. You can contact him by clicking here.

Keith Woolner is an author of Baseball Prospectus. 
Click here to see Keith's other articles. You can contact Keith by clicking here

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