Batters



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Showing page 131 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
1922 CIN Pat Duncan 670 240 607 291 0.358 0.479 0.838 0.328 0.390 0.718 0.343 0.435 0.778 0.743 10.4 27.3 37.7 0.99 10.8 28.2 39.0
2021 KCA Salvador Perez 665 210 620 337 0.316 0.544 0.859 0.309 0.414 0.723 0.312 0.479 0.791 0.730 2.2 40.0 42.2 1.04 2.0 37.0 39.0
1996 MIL Greg Vaughn 442 167 375 214 0.378 0.571 0.948 0.338 0.450 0.788 0.358 0.510 0.868 0.793 11.7 28.0 39.8 1.01 11.5 27.4 39.0
1954 NYA Yogi Berra 651 238 584 285 0.366 0.488 0.854 0.336 0.380 0.715 0.351 0.434 0.784 0.700 9.7 31.1 40.8 1.04 9.3 29.7 39.0
2003 NYN Jeromy Burnitz 259 89 234 136 0.344 0.581 0.925 0.327 0.411 0.738 0.335 0.496 0.831 0.745 8.0 31.6 39.6 1.02 7.9 31.1 39.0
1952 PHI Del Ennis 645 219 592 281 0.340 0.475 0.814 0.316 0.369 0.685 0.328 0.422 0.750 0.693 7.6 31.3 38.8 0.99 7.6 31.5 39.0
2016 SFN Brandon Belt 655 258 542 257 0.394 0.474 0.868 0.324 0.410 0.734 0.359 0.442 0.801 0.732 22.8 16.8 39.6 1.02 22.5 16.5 39.0
1941 SLA Harlond Clift 703 262 584 251 0.373 0.430 0.802 0.316 0.364 0.680 0.345 0.397 0.741 0.726 19.7 19.1 38.9 1.00 19.8 19.1 39.0
1944 SLN Walker Cooper 426 147 397 200 0.345 0.504 0.849 0.312 0.357 0.669 0.329 0.430 0.759 0.683 6.9 29.2 36.1 0.98 7.5 31.5 39.0
2006 ATL Brian McCann 492 191 442 253 0.388 0.572 0.961 0.346 0.447 0.792 0.367 0.510 0.876 0.757 10.5 27.2 37.8 0.97 10.8 28.0 38.9
1950 BRO Gil Hodges 646 233 561 285 0.361 0.508 0.869 0.325 0.399 0.723 0.343 0.453 0.796 0.733 11.6 30.8 42.4 1.05 10.6 28.3 38.9
2021 CHN Frank Schwindel 239 93 222 136 0.389 0.613 1.002 0.306 0.392 0.698 0.347 0.502 0.850 0.723 12.3 28.0 40.2 1.03 11.9 27.1 38.9
1943 DET Dick Wakefield 697 262 633 275 0.376 0.434 0.810 0.329 0.358 0.688 0.353 0.396 0.749 0.657 16.2 23.8 40.1 1.02 15.7 23.1 38.9
1983 HOU Dickie Thon 686 233 619 283 0.340 0.457 0.797 0.307 0.371 0.678 0.323 0.414 0.737 0.694 11.2 26.9 38.0 0.96 11.5 27.5 38.9
2012 LAN Matt Kemp 449 165 403 217 0.367 0.538 0.906 0.316 0.411 0.727 0.342 0.475 0.817 0.715 11.5 26.0 37.5 0.97 11.9 27.0 38.9
1985 NYN Keith Hernandez 682 262 593 255 0.384 0.430 0.814 0.321 0.369 0.690 0.353 0.400 0.752 0.689 21.5 18.2 39.7 1.00 21.1 17.8 38.9
1914 PHA Home Run Baker 637 241 570 252 0.378 0.442 0.820 0.337 0.352 0.689 0.358 0.397 0.754 0.633 13.3 26.3 39.5 1.01 13.1 25.9 38.9
1972 PHI Greg Luzinski 611 203 563 255 0.332 0.453 0.785 0.299 0.354 0.652 0.316 0.403 0.719 0.676 10.3 28.3 38.5 0.99 10.4 28.6 38.9
2024 PHI Kyle Schwarber 692 253 573 278 0.366 0.485 0.851 0.319 0.403 0.723 0.343 0.444 0.787 0.718 16.1 23.7 39.7 1.02 15.8 23.2 38.9
2018 PHI Rhys Hoskins 660 233 558 277 0.353 0.496 0.849 0.310 0.406 0.716 0.332 0.451 0.783 0.720 14.1 25.3 39.5 1.01 13.9 24.9 38.9
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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).