Batters



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Showing page 51 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
2016 TOR Josh Donaldson 700 282 577 317 0.403 0.549 0.952 0.319 0.430 0.749 0.361 0.490 0.851 0.743 29.5 33.9 63.4 1.07 27.1 31.1 58.2
2019 ARI Ketel Marte 628 244 569 337 0.389 0.592 0.981 0.331 0.444 0.775 0.360 0.518 0.878 0.752 17.9 42.0 60.1 1.03 17.3 40.6 58.1
2003 CHA Frank Thomas 662 258 546 307 0.390 0.562 0.952 0.320 0.421 0.742 0.355 0.492 0.847 0.759 23.0 38.0 61.0 1.02 21.9 36.2 58.1
1956 DET Charlie Maxwell 592 244 500 267 0.412 0.534 0.946 0.343 0.392 0.735 0.378 0.463 0.841 0.731 20.5 35.8 56.3 0.98 21.2 36.9 58.1
1964 MLN Joe Torre 646 236 601 299 0.365 0.498 0.863 0.303 0.372 0.675 0.334 0.435 0.769 0.681 20.3 37.8 58.0 1.00 20.3 37.9 58.1
1948 PHI Del Ennis 641 220 589 309 0.343 0.525 0.868 0.312 0.360 0.672 0.328 0.442 0.770 0.711 9.8 48.3 58.2 0.96 9.8 48.2 58.1
2013 SLN Matt Holliday 602 234 520 255 0.389 0.490 0.879 0.305 0.384 0.689 0.347 0.437 0.784 0.700 25.4 28.1 53.5 0.97 27.6 30.5 58.1
2010 BOS Adrian Beltre 641 234 589 326 0.365 0.553 0.919 0.317 0.406 0.724 0.341 0.480 0.821 0.732 15.3 43.5 58.8 1.03 15.1 42.9 58.0
2019 CIN Eugenio Suarez 662 237 575 329 0.358 0.572 0.930 0.309 0.418 0.728 0.334 0.495 0.829 0.752 16.1 44.3 60.4 1.03 15.5 42.5 58.0
2002 HOU Lance Berkman 692 280 578 334 0.405 0.578 0.982 0.348 0.430 0.778 0.376 0.504 0.880 0.738 19.5 42.6 62.2 1.05 18.2 39.7 58.0
1997 LAN Raul Mondesi 670 241 616 333 0.360 0.541 0.900 0.320 0.408 0.727 0.340 0.474 0.814 0.740 13.5 40.8 54.4 0.96 14.4 43.5 58.0
2001 LAN Shawn Green 701 261 619 370 0.372 0.598 0.970 0.342 0.446 0.788 0.357 0.522 0.879 0.753 10.4 46.8 57.2 0.99 10.5 47.5 58.0
2005 SFN Randy Winn 247 95 231 157 0.385 0.680 1.064 0.339 0.437 0.777 0.362 0.559 0.921 0.741 8.3 47.3 55.7 0.97 8.6 49.3 58.0
2005 TEX Mark Teixeira 730 277 644 370 0.379 0.575 0.954 0.338 0.424 0.762 0.359 0.499 0.858 0.753 15.3 48.9 64.3 1.04 13.8 44.1 58.0
1932 NY1 Bill Terry 677 258 643 373 0.381 0.580 0.961 0.345 0.442 0.787 0.363 0.511 0.874 0.719 12.1 44.7 56.8 0.99 12.3 45.6 57.9
2000 ANA Darin Erstad 747 305 676 366 0.408 0.541 0.950 0.348 0.437 0.784 0.378 0.489 0.867 0.790 22.6 35.5 58.0 1.00 22.5 35.4 57.8
1941 BOS Joe Cronin 615 244 518 263 0.397 0.508 0.904 0.316 0.364 0.680 0.356 0.436 0.792 0.726 24.8 37.7 62.6 1.08 22.9 34.8 57.8
1986 MIN Kirby Puckett 723 264 680 365 0.365 0.537 0.902 0.312 0.400 0.712 0.339 0.468 0.807 0.735 18.9 46.2 65.0 1.06 16.8 41.1 57.8
1947 NY1 Walker Cooper 547 185 515 302 0.338 0.586 0.925 0.318 0.382 0.699 0.328 0.484 0.812 0.724 5.6 52.7 58.3 0.99 5.6 52.2 57.8
1931 NYA Ben Chapman 686 269 600 290 0.392 0.483 0.875 0.329 0.375 0.704 0.361 0.429 0.790 0.735 21.5 33.0 54.5 0.96 22.8 35.0 57.8
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Columns:
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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).