Batters



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Showing page 227 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 CLE Franmil Reyes 466 151 418 218 0.324 0.522 0.846 0.311 0.409 0.720 0.318 0.465 0.783 0.730 3.1 24.3 27.3 1.01 3.1 24.5 27.5
1970 KCA Amos Otis 700 245 620 263 0.350 0.424 0.774 0.312 0.378 0.690 0.331 0.401 0.732 0.697 13.4 14.4 27.7 1.01 13.3 14.3 27.5
1998 KCA Dean Palmer 639 213 572 292 0.333 0.510 0.844 0.324 0.421 0.745 0.329 0.466 0.795 0.769 2.8 25.7 28.4 1.04 2.7 24.9 27.5
1975 KCA Hal McRae 547 198 480 212 0.362 0.442 0.804 0.318 0.371 0.689 0.340 0.406 0.746 0.703 12.0 17.1 29.1 1.04 11.3 16.2 27.5
1962 LAA Lee Thomas 652 230 583 272 0.353 0.467 0.819 0.330 0.396 0.727 0.342 0.431 0.773 0.716 7.3 20.8 28.1 1.02 7.1 20.4 27.5
2021 LAN AJ Pollock 422 150 384 206 0.355 0.536 0.892 0.322 0.433 0.755 0.339 0.485 0.823 0.723 7.1 21.0 28.0 1.02 7.0 20.6 27.5
2014 LAN Hanley Ramirez 512 189 449 201 0.369 0.448 0.817 0.310 0.395 0.705 0.340 0.421 0.761 0.691 15.1 12.2 27.3 0.97 15.2 12.3 27.5
2021 LAN Justin Turner 612 221 533 251 0.361 0.471 0.832 0.317 0.416 0.732 0.339 0.443 0.782 0.723 13.5 14.3 27.8 1.02 13.4 14.1 27.5
2017 MIL Eric Thames 551 198 469 243 0.359 0.518 0.877 0.333 0.434 0.766 0.346 0.476 0.822 0.746 7.3 20.2 27.5 1.01 7.3 20.2 27.5
1915 NEW Bill Rariden 523 188 446 164 0.359 0.368 0.727 0.294 0.322 0.617 0.327 0.345 0.672 0.651 17.1 10.2 27.3 1.01 17.2 10.3 27.5
1968 NYN Ed Charles 409 132 369 160 0.323 0.434 0.756 0.290 0.331 0.621 0.306 0.383 0.689 0.637 6.7 19.1 25.8 0.98 7.1 20.4 27.5
1999 PIT Jason Kendall 334 143 280 143 0.428 0.511 0.939 0.332 0.430 0.761 0.380 0.470 0.850 0.768 16.2 11.9 28.1 1.00 15.9 11.6 27.5
1954 PIT Sid Gordon 447 178 363 159 0.398 0.438 0.836 0.315 0.389 0.704 0.357 0.413 0.770 0.738 18.6 9.0 27.6 1.01 18.5 9.0 27.5
1923 BOS Ira Flagstead 433 159 382 173 0.367 0.453 0.820 0.317 0.362 0.678 0.342 0.407 0.749 0.728 11.2 17.6 28.7 1.05 10.7 16.8 27.4
2019 CHA Tim Anderson 518 185 498 253 0.357 0.508 0.865 0.316 0.441 0.756 0.337 0.474 0.811 0.761 10.6 17.0 27.6 1.00 10.5 16.9 27.4
1993 CHA Tim Raines 486 194 415 199 0.399 0.480 0.879 0.343 0.413 0.756 0.371 0.446 0.817 0.742 13.9 13.8 27.6 1.01 13.8 13.7 27.4
1948 CIN Danny Litwhiler 391 141 338 158 0.361 0.467 0.828 0.319 0.366 0.685 0.340 0.417 0.757 0.711 7.3 19.5 26.7 0.99 7.5 20.0 27.4
1961 CIN Gordy Coleman 578 196 520 262 0.339 0.504 0.843 0.335 0.408 0.743 0.337 0.456 0.793 0.728 1.4 26.4 27.8 1.01 1.4 26.0 27.4
1929 DET Roy Johnson 715 271 639 306 0.379 0.479 0.858 0.353 0.428 0.781 0.366 0.453 0.819 0.747 9.3 16.4 25.7 0.98 9.9 17.5 27.4
2022 HOU Alex Bregman 656 240 548 249 0.366 0.454 0.820 0.314 0.407 0.721 0.340 0.431 0.771 0.700 17.1 12.9 29.9 1.02 15.7 11.8 27.4
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Columns:
--------

Note: The batter's composite OB% and SLG% is obtained by the sum of all individual
plate appearances. For each PA, the OB% and SLG% used is versus pitchers of the same
hand as the one he's facing.

OPP_PIT_OB: the opposing pitcher OB% against, when facing batters of the same hand
OPP_PIT_SLG: the opposing pitcher SLG% against, when facing batters of the same hand
OPP_PIT_OOPS: the opposing pitcher OB% + SLG% against, when facing batters of the same hand

EXPCT_OB_AVG: the average of the opposing pitcher's OPP_PIT_OB and the batter's OB% (vs. L or R)
EXPCT_SLG_AVG: the average of the opposing pitcher's OPP_PIT_SLG and the batter's SLG% (vs. L or R)
EXPCT_OPS: the average of the opposing pitcher's OOPS and the batter's OPS (vs. L or R)

LG_OPS: the average league OPS, with the league of the home park being the league

PME_OB: the cumulative result of the plate appearance minus the EXPCT_OB_AVG
PME_SLG: the cumulative result of the plate appearance minus the EXPCT_SLG_AVG
PME: the cumulative result of the plate appearance minus the EXPCT_OPS

PF: the composite park factor the batter experienced, based on lefty-righty and park

PME_OB_PF: the cumulative result of the plate appearance minus the EXPCT_OB_AVG, with PF
PME_SLG_PF: the cumulative result of the plate appearance minus the EXPCT_SLG_AVG, with PF
PME_PF: the cumulative result of the plate appearance minus the EXPCT_OPS, with PF


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).