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Showing page 198 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
1983 HOU Ray Knight 567 200 507 225 0.353 0.444 0.797 0.307 0.372 0.679 0.330 0.408 0.738 0.694 12.9 18.2 31.1 0.96 12.7 17.8 30.5
2023 KCA Bobby Witt 694 221 641 317 0.318 0.495 0.813 0.306 0.397 0.702 0.312 0.446 0.758 0.728 4.7 30.8 35.5 1.07 4.0 26.5 30.5
1979 NYA Oscar Gamble 126 57 113 83 0.452 0.735 1.187 0.348 0.431 0.779 0.400 0.583 0.983 0.739 6.4 23.9 30.3 1.00 6.4 24.1 30.5
1999 PHI Scott Rolen 497 183 421 221 0.368 0.525 0.893 0.328 0.424 0.751 0.348 0.474 0.822 0.768 10.0 20.9 31.1 0.98 9.8 20.5 30.5
1911 PIT Fred Clarke 461 183 391 193 0.397 0.494 0.891 0.350 0.386 0.735 0.373 0.440 0.813 0.682 10.9 21.2 32.2 1.03 10.3 20.1 30.5
1931 PIT Paul Waner 647 258 559 253 0.399 0.453 0.851 0.342 0.413 0.755 0.370 0.433 0.803 0.716 18.4 10.8 29.2 0.98 19.2 11.3 30.5
1972 SDN Leron Lee 405 143 370 184 0.353 0.497 0.850 0.322 0.372 0.694 0.338 0.435 0.772 0.676 6.3 22.9 29.2 0.96 6.6 23.9 30.5
1971 SFN Willie McCovey 402 159 329 158 0.396 0.480 0.876 0.323 0.385 0.708 0.359 0.433 0.792 0.679 14.6 15.6 30.2 0.99 14.7 15.8 30.5
1926 SLA Bing Miller 401 146 353 166 0.364 0.470 0.834 0.322 0.357 0.680 0.343 0.414 0.757 0.730 10.0 21.6 31.6 0.98 9.7 20.8 30.5
1992 TOR Joe Carter 683 211 622 310 0.309 0.498 0.807 0.322 0.391 0.713 0.315 0.445 0.760 0.711 -4.6 34.2 29.5 0.99 -4.5 35.1 30.5
2003 BAL Melvin Mora 413 170 344 173 0.412 0.503 0.915 0.327 0.434 0.760 0.369 0.468 0.837 0.759 17.4 11.9 29.3 0.97 18.1 12.3 30.4
1994 BAL Rafael Palmeiro 498 195 436 240 0.392 0.550 0.942 0.354 0.444 0.798 0.373 0.497 0.870 0.776 9.5 23.8 33.3 1.08 8.7 21.7 30.4
2004 CHA Frank Thomas 311 135 240 135 0.434 0.563 0.997 0.327 0.429 0.756 0.381 0.496 0.877 0.769 16.6 15.8 32.4 1.04 15.6 14.8 30.4
2019 CHN Javier Baez 561 177 531 282 0.316 0.531 0.847 0.310 0.423 0.733 0.313 0.477 0.790 0.752 1.4 28.9 30.3 1.00 1.4 29.0 30.4
1967 CIN Pete Rose 650 235 585 260 0.362 0.444 0.806 0.324 0.375 0.699 0.343 0.410 0.752 0.669 12.2 20.0 32.2 1.04 11.5 18.9 30.4
1985 CLE Brett Butler 666 248 591 255 0.372 0.431 0.804 0.320 0.395 0.714 0.346 0.413 0.759 0.730 17.5 11.0 28.5 0.95 18.7 11.7 30.4
2006 COL Todd Helton 649 262 546 260 0.404 0.476 0.880 0.341 0.432 0.773 0.372 0.454 0.826 0.757 20.4 12.3 32.7 1.04 19.0 11.4 30.4
2014 LAN Justin Turner 322 130 288 142 0.404 0.493 0.897 0.309 0.393 0.701 0.356 0.443 0.799 0.691 15.2 14.1 29.3 0.97 15.8 14.6 30.4
1993 MIN Kirby Puckett 682 238 622 295 0.349 0.474 0.823 0.322 0.402 0.724 0.336 0.438 0.774 0.742 9.2 22.4 31.6 1.02 8.9 21.5 30.4
1992 MON Marquis Grissom 707 227 653 273 0.321 0.418 0.739 0.293 0.354 0.647 0.307 0.386 0.693 0.679 9.8 21.9 31.7 1.06 9.4 21.0 30.4
Total 10342 3778 9142 4425 218.8 402.2 621.2 216.0 392.8 609.0

*** The information used here was obtained free of charge from and is copyrighted by Retrosheet. Interested parties may contact Retrosheet at 20 Sunset Rd., Newark, DE 19711. ***










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).