Batters



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Showing page 395 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
2006 CIN Austin Kearns 368 129 325 160 0.351 0.492 0.843 0.328 0.429 0.758 0.339 0.461 0.800 0.757 1.9 14.2 16.1 1.04 1.9 14.0 15.9
1987 CLE Pat Tabler 618 227 553 243 0.367 0.439 0.807 0.323 0.420 0.743 0.345 0.430 0.775 0.756 13.7 4.8 18.5 1.05 11.8 4.1 15.9
1981 CLE Toby Harrah 427 163 361 140 0.382 0.388 0.770 0.314 0.380 0.694 0.348 0.384 0.732 0.690 14.5 1.2 15.7 0.98 14.7 1.2 15.9
1956 DET Earl Torgeson 400 162 318 135 0.405 0.425 0.830 0.346 0.404 0.750 0.376 0.414 0.790 0.731 11.7 3.3 15.0 0.97 12.4 3.5 15.9
2000 HOU Mitch Meluskey 400 160 337 164 0.400 0.487 0.887 0.354 0.442 0.796 0.377 0.464 0.841 0.770 9.2 7.4 16.6 1.02 8.8 7.1 15.9
1971 MIL Dave May 562 192 501 213 0.342 0.425 0.767 0.324 0.381 0.706 0.333 0.403 0.736 0.678 4.9 11.6 16.5 0.99 4.7 11.2 15.9
1969 NYA Bobby Murcer 625 199 564 256 0.318 0.454 0.772 0.327 0.389 0.716 0.323 0.421 0.744 0.687 -2.8 18.8 16.0 1.00 -2.8 18.7 15.9
1927 NYA Pat Collins 313 127 251 105 0.406 0.418 0.824 0.324 0.386 0.710 0.365 0.402 0.767 0.739 12.8 4.2 17.0 1.03 12.0 3.9 15.9
2024 NYN Jose Iglesias 291 111 270 121 0.381 0.448 0.830 0.308 0.399 0.707 0.344 0.424 0.768 0.718 10.8 6.4 17.2 1.02 10.0 5.9 15.9
1979 OAK Dave Revering 513 171 472 228 0.333 0.483 0.816 0.337 0.407 0.744 0.335 0.445 0.780 0.739 -0.9 17.4 16.5 0.94 -0.9 16.8 15.9
2002 OAK Jermaine Dye 555 185 488 224 0.333 0.459 0.792 0.318 0.409 0.727 0.326 0.434 0.760 0.753 4.1 11.9 16.0 0.98 4.1 11.8 15.9
2021 PHI Jean Segura 567 197 514 224 0.347 0.436 0.783 0.313 0.413 0.727 0.330 0.425 0.755 0.723 9.9 5.5 15.3 0.98 10.3 5.7 15.9
1993 PIT Lonnie Smith 252 105 199 88 0.417 0.442 0.859 0.317 0.400 0.717 0.367 0.421 0.788 0.722 12.7 3.0 15.7 1.00 12.9 3.0 15.9
1990 PIT Sid Bream 448 155 389 177 0.346 0.455 0.801 0.335 0.389 0.724 0.340 0.422 0.763 0.700 2.5 12.4 15.0 0.97 2.7 13.1 15.9
2003 SFN Andres Galarraga 293 103 272 133 0.352 0.489 0.841 0.317 0.407 0.724 0.334 0.448 0.782 0.745 5.0 11.2 16.2 1.04 4.9 11.0 15.9
2016 SFN Hunter Pence 442 158 395 178 0.357 0.451 0.808 0.315 0.410 0.725 0.336 0.430 0.767 0.732 9.2 8.4 17.6 1.05 8.3 7.6 15.9
1998 SFN Joe Carter 115 37 105 59 0.322 0.562 0.884 0.320 0.403 0.723 0.321 0.482 0.803 0.737 1.1 13.3 14.4 0.96 1.2 14.7 15.9
1915 SLF Ward Miller 645 249 533 204 0.386 0.383 0.769 0.337 0.369 0.706 0.361 0.376 0.737 0.651 15.8 3.7 19.6 1.06 12.8 3.0 15.9
2003 TOR Greg Myers 369 138 329 165 0.374 0.502 0.876 0.345 0.437 0.782 0.360 0.469 0.829 0.759 5.2 10.7 15.9 1.03 5.2 10.7 15.9
1998 ANA Darin Erstad 592 208 537 261 0.351 0.486 0.837 0.347 0.433 0.779 0.349 0.459 0.808 0.769 1.3 14.0 15.5 0.99 1.3 14.3 15.8
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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).