Batters



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Showing page 256 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
1981 DET Kirk Gibson 313 115 290 139 0.367 0.479 0.847 0.316 0.357 0.673 0.342 0.418 0.760 0.690 8.1 17.5 25.5 1.02 7.9 17.2 25.0
1964 DET Norm Cash 559 196 479 217 0.351 0.453 0.804 0.317 0.391 0.709 0.334 0.422 0.756 0.693 9.3 15.2 24.4 0.96 9.5 15.6 25.0
1959 KC1 Bob Cerv 513 170 463 222 0.331 0.479 0.811 0.310 0.380 0.690 0.321 0.430 0.751 0.703 5.4 22.8 28.2 1.04 4.8 20.2 25.0
1957 KC1 Hector Lopez 439 154 391 175 0.351 0.448 0.798 0.305 0.370 0.675 0.328 0.409 0.736 0.704 10.2 15.0 25.2 1.01 10.1 14.9 25.0
2015 LAN Adrian Gonzalez 643 225 571 274 0.350 0.480 0.830 0.329 0.418 0.747 0.340 0.449 0.788 0.710 6.7 18.0 24.8 0.98 6.8 18.1 25.0
1919 PHA Tillie Walker 497 157 459 205 0.316 0.447 0.763 0.298 0.336 0.634 0.307 0.391 0.698 0.681 4.3 25.7 30.0 1.06 3.6 21.4 25.0
1931 PIT Pie Traynor 677 237 615 256 0.350 0.416 0.766 0.320 0.372 0.692 0.335 0.394 0.729 0.716 10.1 13.8 23.8 0.99 10.6 14.5 25.0
1991 SLN Felix Jose 625 225 568 249 0.360 0.438 0.798 0.328 0.385 0.713 0.344 0.412 0.756 0.686 10.1 15.0 25.0 0.99 10.1 15.0 25.0
1920 SLN Jack Fournier 608 216 530 232 0.355 0.438 0.793 0.325 0.376 0.701 0.340 0.407 0.747 0.670 9.1 16.5 25.6 1.03 8.9 16.1 25.0
1985 TOR George Bell 667 218 607 291 0.327 0.479 0.806 0.320 0.403 0.724 0.324 0.441 0.765 0.730 2.2 22.9 25.0 0.99 2.2 22.9 25.0
2013 WAS Ian Desmond 655 216 600 272 0.330 0.453 0.783 0.305 0.387 0.692 0.317 0.420 0.737 0.700 8.3 20.1 28.5 1.05 7.3 17.6 25.0
1933 WS1 Joe Kuhel 674 255 603 281 0.378 0.466 0.844 0.350 0.411 0.761 0.364 0.439 0.802 0.727 9.6 16.5 26.1 0.98 9.2 15.8 25.0
2009 ANA Juan Rivera 572 190 529 253 0.332 0.478 0.810 0.317 0.399 0.717 0.325 0.439 0.764 0.762 4.1 20.7 24.8 1.04 4.1 20.8 24.9
2015 ARI Welington Castillo 303 96 274 136 0.317 0.496 0.813 0.302 0.396 0.698 0.309 0.446 0.756 0.710 5.4 19.6 25.0 1.01 5.4 19.5 24.9
1980 ATL Chris Chambliss 663 223 602 265 0.336 0.440 0.777 0.332 0.376 0.707 0.334 0.408 0.742 0.691 1.6 19.7 21.3 0.94 1.9 23.0 24.9
2004 BOS Kevin Millar 588 225 508 241 0.383 0.474 0.857 0.327 0.429 0.756 0.355 0.452 0.807 0.769 16.5 11.0 27.6 1.03 14.9 9.9 24.9
1913 BOS Steve Yerkes 567 186 486 177 0.328 0.364 0.692 0.298 0.319 0.617 0.313 0.342 0.654 0.652 11.5 13.9 25.4 1.02 11.3 13.6 24.9
1989 CHN Andre Dawson 459 141 416 198 0.307 0.476 0.783 0.299 0.369 0.668 0.303 0.423 0.726 0.674 2.0 22.3 24.2 1.02 2.1 22.9 24.9
1964 CHN Ernie Banks 636 195 590 266 0.307 0.451 0.757 0.299 0.364 0.662 0.303 0.407 0.710 0.681 2.5 25.8 28.3 1.08 2.2 22.7 24.9
1940 CHN Jim Gleeson 551 212 485 228 0.385 0.470 0.855 0.345 0.413 0.758 0.365 0.442 0.806 0.697 11.0 14.0 24.9 1.01 11.0 14.0 24.9
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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).