Batters



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Showing page 216 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
1968 CHN Ernie Banks 595 168 552 259 0.282 0.469 0.752 0.289 0.332 0.621 0.285 0.401 0.686 0.637 -1.8 37.9 36.1 1.08 -2.1 30.6 28.5
1918 CHN Fred Merkle 541 182 482 187 0.336 0.388 0.724 0.292 0.318 0.610 0.314 0.353 0.667 0.629 11.9 16.7 28.6 1.01 11.9 16.6 28.5
1914 CIN Heinie Groh 549 208 455 163 0.379 0.358 0.737 0.300 0.325 0.625 0.340 0.342 0.681 0.641 21.5 7.7 29.2 1.02 21.0 7.5 28.5
1973 CIN Johnny Bench 651 224 557 239 0.344 0.429 0.773 0.308 0.364 0.673 0.326 0.397 0.723 0.694 11.9 18.0 29.8 0.95 11.4 17.2 28.5
1979 CLE Cliff Johnson 274 94 240 129 0.343 0.538 0.881 0.315 0.388 0.702 0.329 0.463 0.791 0.739 5.9 23.8 29.7 1.04 5.7 22.8 28.5
1922 CLE Riggs Stephenson 267 112 233 119 0.419 0.511 0.930 0.320 0.382 0.702 0.370 0.446 0.816 0.735 13.4 15.3 28.6 1.00 13.4 15.2 28.5
1951 DET George Kell 674 256 598 239 0.380 0.400 0.779 0.328 0.367 0.695 0.354 0.383 0.737 0.719 17.4 10.4 27.9 0.99 17.8 10.6 28.5
1984 HOU Terry Puhl 519 195 449 195 0.376 0.434 0.810 0.325 0.368 0.693 0.350 0.401 0.752 0.685 13.2 14.8 27.8 0.97 13.5 15.2 28.5
1964 KC1 Jim Gentile 533 198 439 204 0.371 0.465 0.836 0.317 0.377 0.694 0.344 0.421 0.765 0.693 14.5 19.1 33.6 1.08 12.3 16.2 28.5
1979 KCA Amos Otis 660 241 577 256 0.365 0.444 0.809 0.320 0.397 0.717 0.342 0.420 0.763 0.739 15.0 14.1 29.1 1.01 14.7 13.8 28.5
1977 MON Andre Dawson 566 184 525 249 0.325 0.474 0.799 0.306 0.385 0.691 0.316 0.430 0.745 0.721 5.3 23.3 28.6 1.01 5.3 23.2 28.5
1939 NYA Charlie Keller 490 214 398 199 0.437 0.500 0.937 0.365 0.432 0.797 0.401 0.466 0.867 0.752 17.5 13.2 30.7 0.96 16.2 12.3 28.5
1952 NYA Joe Collins 489 176 428 206 0.360 0.481 0.841 0.331 0.377 0.708 0.345 0.429 0.775 0.690 7.1 21.9 29.0 1.02 7.0 21.5 28.5
1945 NYA Oscar Grimes 595 230 480 172 0.387 0.358 0.745 0.309 0.333 0.641 0.348 0.346 0.693 0.665 23.1 6.0 29.1 1.02 22.6 5.9 28.5
1987 NYN Kevin McReynolds 639 203 590 292 0.318 0.495 0.813 0.313 0.406 0.719 0.315 0.451 0.766 0.728 1.5 26.3 27.8 0.99 1.5 27.0 28.5
1980 NYN Steve Henderson 584 214 513 206 0.366 0.402 0.768 0.305 0.369 0.673 0.336 0.385 0.721 0.691 18.0 8.5 26.6 0.97 19.3 9.1 28.5
1944 PHI Ron Northey 644 234 570 283 0.363 0.496 0.860 0.351 0.411 0.761 0.357 0.454 0.811 0.683 3.9 24.3 28.3 1.00 3.9 24.5 28.5
1978 SDN Gene Richards 629 239 555 233 0.380 0.420 0.800 0.332 0.375 0.708 0.356 0.398 0.754 0.688 15.0 13.1 28.1 0.94 15.2 13.3 28.5
1990 SFN Will Clark 678 242 600 269 0.357 0.448 0.805 0.330 0.379 0.709 0.343 0.414 0.757 0.700 9.1 20.4 29.5 1.02 8.8 19.7 28.5
1949 SLA Bob Dillinger 605 230 544 227 0.380 0.417 0.797 0.338 0.355 0.692 0.359 0.386 0.745 0.727 12.8 16.7 29.6 1.01 12.3 16.1 28.5
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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).