Batters



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Showing page 164 of 4181 (83616 total matches)
YEAR TEAM
ID 		NAME PLATE
APP 		ON
BASE 		AT
BATS 		TOTAL
BASES 		OB
AVG 		SLG
AVG 		OPS OPP
PIT
OB 		OPP
PIT
SLG 		OPP
PIT
OOPS 		EXPCT
OB
AVG 		EXPCT
SLG
AVG 		EXPCT
OPS 		LG
OPS 		PME
OB 		PME
SLG 		PME PF PME
OB
PF 		PME
SLG
PF 		PME
PF
2021 SFN Buster Posey 454 177 395 197 0.390 0.499 0.889 0.309 0.411 0.721 0.350 0.455 0.805 0.723 18.3 17.4 35.7 1.05 17.6 16.7 34.3
1966 WS2 Frank Howard 548 190 493 218 0.347 0.442 0.789 0.296 0.359 0.656 0.322 0.401 0.722 0.671 13.8 20.2 34.0 1.00 13.9 20.4 34.3
1988 CIN Barry Larkin 652 223 588 252 0.342 0.429 0.771 0.292 0.359 0.652 0.317 0.394 0.711 0.669 16.2 20.8 37.0 1.05 15.0 19.2 34.2
1970 CIN Bobby Tolan 675 256 589 280 0.379 0.475 0.855 0.338 0.397 0.736 0.359 0.436 0.795 0.718 13.8 22.3 36.1 1.00 13.1 21.1 34.2
1951 CLE Al Rosen 661 239 573 256 0.362 0.447 0.808 0.332 0.370 0.702 0.347 0.408 0.755 0.719 9.7 21.6 31.3 0.96 10.6 23.6 34.2
1968 HOU Rusty Staub 682 252 591 229 0.370 0.387 0.757 0.299 0.348 0.647 0.334 0.368 0.702 0.637 23.8 11.5 35.3 1.02 23.1 11.1 34.2
1958 MLN Wes Covington 324 122 294 183 0.377 0.622 0.999 0.346 0.421 0.767 0.361 0.522 0.883 0.729 4.9 29.8 34.7 0.96 4.8 29.4 34.2
2018 OAK Matt Chapman 616 219 547 278 0.356 0.508 0.864 0.315 0.420 0.735 0.335 0.464 0.799 0.733 12.5 23.9 36.4 1.00 11.7 22.5 34.2
1949 PHA Sam Chapman 674 245 590 268 0.364 0.454 0.818 0.341 0.368 0.709 0.352 0.411 0.763 0.727 7.4 26.1 33.5 0.99 7.6 26.6 34.2
1962 SLN Bill White 682 263 614 296 0.386 0.482 0.868 0.336 0.397 0.733 0.361 0.440 0.800 0.716 16.8 26.3 43.1 1.12 13.3 20.9 34.2
1931 SLN Jim Bottomley 419 168 382 204 0.401 0.534 0.935 0.343 0.421 0.764 0.372 0.477 0.849 0.716 12.1 21.9 34.2 1.00 12.1 21.9 34.2
2009 BOS J. D. Drew 539 211 452 236 0.391 0.522 0.914 0.338 0.434 0.772 0.365 0.478 0.843 0.762 14.4 20.3 34.6 1.01 14.2 20.0 34.1
1948 BOS Vern Stephens 715 249 635 299 0.348 0.471 0.819 0.337 0.372 0.709 0.343 0.421 0.764 0.726 4.1 31.7 35.8 1.04 3.9 30.2 34.1
1996 CAL Tim Salmon 681 263 581 291 0.386 0.501 0.887 0.340 0.444 0.783 0.363 0.472 0.835 0.793 15.9 18.0 33.9 0.99 16.0 18.1 34.1
1987 CHA Ivan Calderon 607 220 542 285 0.362 0.526 0.888 0.326 0.422 0.749 0.344 0.474 0.819 0.756 10.9 28.1 39.1 1.06 9.5 24.5 34.1
1945 CHA Johnny Dickshot 542 196 486 198 0.362 0.407 0.769 0.309 0.325 0.634 0.335 0.366 0.701 0.665 14.3 20.1 34.4 0.95 14.2 19.9 34.1
1912 CHN Johnny Evers 567 235 481 211 0.414 0.439 0.853 0.338 0.381 0.719 0.376 0.410 0.786 0.700 21.5 14.0 35.5 1.02 20.7 13.4 34.1
2008 COL Brad Hawpe 569 217 488 243 0.381 0.498 0.879 0.336 0.413 0.749 0.359 0.455 0.814 0.740 13.0 21.3 34.2 1.00 13.0 21.2 34.1
1999 COL Dante Bichette 659 233 593 321 0.354 0.541 0.895 0.328 0.425 0.754 0.341 0.483 0.824 0.768 8.3 35.0 43.4 1.15 6.5 27.5 34.1
1947 DET Hoot Evers 525 187 460 200 0.356 0.435 0.791 0.311 0.343 0.654 0.334 0.389 0.723 0.693 11.8 21.5 33.3 0.99 12.1 22.0 34.1
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On every pitcher versus batter matchup, we have a contest of the batter's ability and
the pitcher's ability. Although OPS and OOPS are not perfect statistics, they are
widely embraced and are relatively straightforward for most fans. They're approximations.
At some point, this process can be made smarter. Until then, this is where we are.

What is the batter's average ability on any plate appearance in a season? It's his OPS for the
season. Likewise, the pitcher's OOPS on the play is his seasonal OOPS. What is the expected
outcome? It's the average of the two, of course.

However, we have two issues to deal with -- the handedness (L or R) of the batter and pitcher
and the park where each event occurred.

1) Hand: For each and every PA, the expected outcome is affected by the hand of the batter and
pitcher. But, we only care about the batter's and pitcher's seasonal OPS/OOPS when it matches
the same scenario as the specific PA.

For example: If a left-handed batter is facing a right-handed pitcher, we only care about how
the batter did versus right-handed pitchers that year, and how the pitcher did versus left-handed
batters. Those are the specific OPS/OOPS values used from which to build the expected outcome.

Ex.: A LHB faces a RHP. The batter's OPS versus righties that year was 0.800. The pitcher's OOPS
versus lefties was 0.700. The expected outcome is the average of the two, 0.750.

Suppose the batter makes an out. His on-base average on the play was 0.000 and his slugging average
is also 0.000. On the play, the batter attained a negative PME, 0.000 minus 0.750 = -0.750. Meanwhile,
the pitcher attained a positive PME of 0.750 minus 0.000 = 0.750. All plays balance in this way.

What if the batter singles? His OB% was 1.000 and his SLG% is 1.000. That's an OPS of 2.000. His PME
is 2.000 minus 0.750 = 1.250, and the pitcher's PME is 0.750 minus 2.000 = -1.250.

All ~16 million plays in MLB from 1910-2025 were assessed in this manner.



2) Park: The parks where events occurred are important as well. Using the enhanced Park Factors at
this site -- those which break down PFs by L-L, L-R, R-L, R-R by using a base counting method -- a
composite PF is derived based on all of the PAs a batter had that season. After the seasonal PME is
compiled by adding all of the plays that year, the PME is divided by the PF* to obtain the final PME.

* The PME is compiled at the home and road level and divided by the corresponding PF. The PFs may
not seem correct but are indicative of the season. For example, the Rockies of 2001 had a composite
PF of 1.22. Todd Helton's (as a lefty) was more like 1.18. On the road, he was 0.97 -- for a
composite of 1.08 (1.18 + 0.97) / 2, the value shown. Before applying the PF, his home PME was about
96 and road was 9. Thus, most of the PME reduction was caused at home. It drops by ~16% (twice 1.08)
while his road PME stays relatively constant. His park-adjusted PME drops from ~105 to 91.


NOTE: This analysis concerns only what the batter does at the plate. Things like base running and
the quality of the opposing defense is not factored in (aside from taking extra bases on a hit).