Batters



Reset All Picks
Showing page 129 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
2005 BAL Brian Roberts 640 246 561 289 0.384 0.515 0.900 0.337 0.430 0.767 0.361 0.472 0.833 0.753 15.0 24.2 39.2 0.98 15.0 24.3 39.3
1937 BOS Joe Cronin 671 265 570 277 0.395 0.486 0.881 0.340 0.404 0.744 0.368 0.445 0.813 0.765 18.4 23.6 41.8 1.05 17.3 22.2 39.3
1995 BOS John Valentin 621 246 520 277 0.396 0.533 0.929 0.343 0.438 0.780 0.369 0.485 0.855 0.769 16.7 25.0 41.7 1.03 15.7 23.6 39.3
1987 BOS Mike Greenwell 456 176 412 235 0.386 0.570 0.956 0.338 0.430 0.768 0.362 0.500 0.862 0.756 10.8 28.6 39.4 1.01 10.8 28.5 39.3
1982 CAL Brian Downing 725 266 623 300 0.367 0.482 0.848 0.321 0.408 0.729 0.344 0.445 0.789 0.727 16.7 22.5 39.2 1.00 16.7 22.6 39.3
1974 CHN Jose Cardenal 604 216 542 239 0.358 0.441 0.799 0.307 0.356 0.663 0.333 0.398 0.731 0.688 15.1 23.8 38.8 0.99 15.3 24.1 39.3
1985 CHN Keith Moreland 667 249 587 258 0.373 0.440 0.813 0.301 0.367 0.669 0.337 0.403 0.741 0.689 23.9 21.4 45.3 1.05 20.7 18.6 39.3
1984 DET Alan Trammell 626 237 555 260 0.379 0.468 0.847 0.318 0.401 0.719 0.348 0.435 0.783 0.722 19.0 18.9 37.8 0.96 19.8 19.6 39.3
2006 DET Carlos Guillen 622 249 543 282 0.400 0.519 0.920 0.344 0.444 0.789 0.372 0.482 0.854 0.775 17.4 20.9 38.2 0.99 17.9 21.5 39.3
1915 DET Marty Kavanagh 386 143 332 151 0.370 0.455 0.825 0.286 0.306 0.592 0.328 0.380 0.709 0.640 16.2 24.8 41.0 1.03 15.5 23.8 39.3
2004 HOU Jeff Kent 606 211 540 287 0.348 0.531 0.880 0.315 0.413 0.728 0.332 0.472 0.804 0.752 9.9 32.0 41.9 1.04 9.3 30.0 39.3
2003 SEA Edgar Martinez 603 245 497 243 0.406 0.489 0.895 0.322 0.425 0.747 0.364 0.457 0.821 0.759 25.4 15.6 40.9 0.96 24.4 15.0 39.3
2016 TEX Adrian Beltre 640 229 583 304 0.358 0.521 0.879 0.318 0.426 0.743 0.338 0.474 0.811 0.743 12.9 28.3 41.2 1.04 12.3 27.0 39.3
1942 WS1 Bobby Estalella 517 207 429 177 0.400 0.413 0.813 0.312 0.331 0.643 0.356 0.372 0.728 0.681 22.9 17.4 40.3 1.02 22.3 17.0 39.3
1913 WS1 Chick Gandil 603 213 550 219 0.353 0.398 0.751 0.299 0.318 0.617 0.326 0.358 0.684 0.652 17.1 22.8 39.8 1.00 16.9 22.5 39.3
1950 WS1 Eddie Yost 730 317 573 232 0.434 0.405 0.839 0.340 0.390 0.730 0.387 0.397 0.784 0.754 34.4 4.1 38.5 0.97 35.1 4.2 39.3
1954 WS1 Mickey Vernon 674 239 598 294 0.355 0.492 0.846 0.333 0.381 0.714 0.344 0.436 0.780 0.700 7.4 33.1 40.4 1.03 7.2 32.2 39.3
1973 BOS Reggie Smith 495 197 423 218 0.398 0.515 0.913 0.340 0.401 0.741 0.369 0.458 0.827 0.707 14.3 24.0 38.3 0.99 14.6 24.6 39.2
1968 CAL Rick Reichardt 601 196 534 225 0.326 0.421 0.747 0.284 0.330 0.614 0.305 0.376 0.681 0.633 12.7 24.6 37.3 0.99 13.3 25.9 39.2
2025 CHN Michael Busch 592 203 524 274 0.343 0.523 0.866 0.320 0.403 0.723 0.332 0.463 0.794 0.718 6.7 31.3 38.0 0.98 6.9 32.3 39.2
No results found.

*** The information used here was obtained free of charge from and is copyrighted by Retrosheet. Interested parties may contact Retrosheet at 20 Sunset Rd., Newark, DE 19711. ***










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).