Batters



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Showing page 100 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
1965 CIN Vada Pinson 728 254 669 324 0.349 0.484 0.833 0.310 0.378 0.688 0.330 0.431 0.761 0.681 14.1 35.6 49.7 1.04 12.7 32.1 44.8
1995 MIN Chuck Knoblauch 629 267 538 262 0.424 0.487 0.911 0.335 0.424 0.760 0.380 0.456 0.836 0.769 28.1 16.7 44.9 1.01 28.0 16.7 44.8
2001 NYA Derek Jeter 686 257 614 295 0.375 0.480 0.855 0.319 0.411 0.730 0.347 0.446 0.793 0.760 18.9 21.8 40.7 0.97 20.8 24.0 44.8
1963 NYA Elston Howard 531 181 487 257 0.341 0.528 0.869 0.302 0.386 0.688 0.321 0.457 0.778 0.688 10.4 33.9 44.3 0.98 10.5 34.3 44.8
1971 SDN Nate Colbert 639 216 565 261 0.338 0.462 0.800 0.298 0.354 0.651 0.318 0.408 0.726 0.679 12.7 31.0 43.7 0.97 13.0 31.8 44.8
1962 SLN Ken Boyer 691 254 611 287 0.368 0.470 0.837 0.312 0.383 0.696 0.340 0.426 0.766 0.716 19.1 26.7 45.9 1.02 18.6 26.1 44.8
1975 SLN Ted Simmons 649 257 581 285 0.396 0.491 0.887 0.341 0.396 0.737 0.369 0.443 0.812 0.691 17.9 27.4 45.3 1.03 17.7 27.1 44.8
1942 BSN Ernie Lombardi 347 140 309 149 0.403 0.482 0.886 0.291 0.319 0.610 0.347 0.401 0.748 0.656 19.6 25.2 44.7 1.00 19.6 25.2 44.7
2010 NYN David Wright 670 237 587 295 0.354 0.503 0.856 0.312 0.397 0.709 0.333 0.450 0.782 0.720 14.1 31.3 45.3 1.01 13.9 30.9 44.7
1964 NYN Joe Christopher 604 217 543 253 0.359 0.466 0.825 0.299 0.370 0.668 0.329 0.418 0.747 0.681 18.3 26.3 44.5 1.00 18.4 26.4 44.7
1982 SDN Sixto Lezcano 559 216 470 222 0.386 0.472 0.859 0.310 0.375 0.685 0.348 0.424 0.772 0.688 21.4 23.0 44.5 0.97 21.5 23.1 44.7
1965 SLN Bill White 618 224 543 261 0.362 0.481 0.843 0.306 0.372 0.677 0.334 0.426 0.760 0.681 17.6 29.6 47.2 1.05 16.7 28.0 44.7
1947 SLN Stan Musial 678 267 587 296 0.394 0.504 0.898 0.345 0.399 0.744 0.369 0.452 0.821 0.724 16.7 30.5 47.3 1.06 15.8 28.8 44.7
2025 ATL Ronald Acuna 412 172 338 175 0.417 0.518 0.935 0.308 0.388 0.696 0.363 0.453 0.816 0.718 22.4 22.0 44.6 0.99 22.4 22.0 44.6
1948 BOS Bobby Doerr 619 238 527 266 0.384 0.505 0.889 0.336 0.370 0.706 0.360 0.437 0.798 0.726 14.9 35.2 50.1 1.04 13.3 31.3 44.6
1986 CIN Eric Davis 487 184 415 217 0.378 0.523 0.901 0.313 0.383 0.695 0.345 0.453 0.798 0.698 15.7 29.1 44.8 1.02 15.6 29.0 44.6
2019 TBA Austin Meadows 591 215 530 296 0.364 0.558 0.922 0.324 0.442 0.765 0.344 0.500 0.844 0.761 11.9 31.1 43.1 0.95 12.3 32.2 44.6
2008 ANA Mark Teixeira 234 105 193 122 0.449 0.632 1.081 0.348 0.435 0.783 0.398 0.534 0.932 0.754 16.3 27.6 43.9 0.99 16.5 28.0 44.5
2016 ARI Jean Segura 694 254 637 318 0.366 0.499 0.865 0.311 0.412 0.722 0.338 0.456 0.794 0.732 19.3 28.4 47.7 1.06 18.0 26.5 44.5
1954 BOS Jackie Jensen 674 242 580 274 0.359 0.472 0.831 0.316 0.358 0.674 0.338 0.415 0.753 0.700 14.3 34.3 48.6 1.04 13.1 31.4 44.5
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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).