Batters



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Showing page 259 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
1923 PHA Bing Miller 506 169 458 206 0.334 0.450 0.784 0.318 0.360 0.678 0.326 0.405 0.731 0.728 4.0 20.8 24.8 1.04 4.0 20.8 24.8
1951 PHA Elmer Valo 530 217 444 198 0.409 0.446 0.855 0.351 0.406 0.758 0.380 0.426 0.806 0.719 15.6 8.0 23.4 0.98 16.5 8.5 24.8
1930 PHA Jimmy Dykes 535 215 435 185 0.402 0.425 0.827 0.331 0.402 0.733 0.366 0.413 0.780 0.763 18.9 5.4 24.3 0.98 19.3 5.5 24.8
1929 PIT George Grantham 458 201 348 186 0.439 0.534 0.973 0.375 0.479 0.854 0.407 0.507 0.914 0.773 14.7 9.9 24.6 1.00 14.8 10.0 24.8
1990 SDN Bip Roberts 629 233 556 241 0.370 0.433 0.804 0.330 0.391 0.721 0.350 0.412 0.762 0.700 12.8 12.2 25.0 1.00 12.7 12.1 24.8
2024 SDN Fernando Tatis 438 149 398 196 0.340 0.492 0.833 0.310 0.403 0.713 0.325 0.448 0.773 0.718 6.6 18.3 24.8 0.99 6.6 18.3 24.8
2015 SFN Brandon Belt 556 198 492 235 0.356 0.478 0.834 0.328 0.419 0.747 0.342 0.448 0.791 0.710 7.8 15.0 22.7 0.97 8.5 16.4 24.8
2006 SLN Chris Duncan 314 114 280 165 0.363 0.589 0.952 0.338 0.441 0.778 0.350 0.515 0.865 0.757 4.0 20.8 24.9 0.99 4.0 20.7 24.8
1982 TEX Buddy Bell 614 231 537 229 0.376 0.426 0.803 0.319 0.401 0.719 0.347 0.414 0.761 0.727 17.6 6.9 24.5 0.97 17.8 7.0 24.8
2019 ARI Christian Walker 603 210 529 252 0.348 0.476 0.825 0.313 0.430 0.743 0.331 0.453 0.784 0.752 10.7 12.6 23.4 0.96 11.3 13.3 24.7
1988 ATL Dale Murphy 671 210 592 249 0.313 0.421 0.734 0.287 0.351 0.638 0.300 0.386 0.686 0.669 8.6 20.6 29.3 1.04 7.2 17.4 24.7
2001 BOS Trot Nixon 633 236 535 270 0.373 0.505 0.878 0.345 0.446 0.791 0.359 0.475 0.834 0.760 8.9 15.7 24.6 1.00 8.9 15.8 24.7
1938 BRO Cookie Lavagetto 562 204 487 198 0.363 0.407 0.770 0.313 0.361 0.675 0.338 0.384 0.722 0.701 14.1 11.0 25.0 1.01 13.9 10.9 24.7
1947 BRO Dixie Walker 637 260 529 226 0.408 0.427 0.835 0.350 0.408 0.758 0.379 0.418 0.797 0.724 18.4 6.1 24.6 1.00 18.5 6.1 24.7
1944 BSN Connie Ryan 381 134 332 138 0.352 0.416 0.767 0.303 0.340 0.643 0.328 0.378 0.705 0.683 9.2 12.6 21.7 0.97 10.5 14.3 24.7
1939 CHA Luke Appling 633 270 516 190 0.427 0.368 0.795 0.332 0.387 0.719 0.379 0.378 0.757 0.752 30.0 -4.4 25.6 1.04 29.2 -4.5 24.7
1911 CIN Johnny Bates 646 259 519 204 0.401 0.393 0.794 0.343 0.379 0.722 0.372 0.386 0.758 0.682 18.3 5.0 23.3 0.99 19.4 5.3 24.7
1995 CLE Eddie Murray 480 180 436 225 0.375 0.516 0.891 0.352 0.433 0.785 0.363 0.475 0.838 0.769 5.5 18.0 23.5 0.99 5.8 18.9 24.7
2003 CLE Milton Bradley 451 190 377 189 0.421 0.501 0.923 0.349 0.455 0.804 0.385 0.478 0.864 0.759 16.2 9.2 25.4 0.98 15.8 8.9 24.7
2000 KCA Johnny Damon 741 280 655 324 0.378 0.495 0.873 0.352 0.446 0.798 0.365 0.470 0.835 0.790 9.6 15.5 25.1 1.01 9.4 15.3 24.7
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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).