Batters



Reset All Picks
Showing page 689 of 4181 (83612 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
2023 SLN Richie Palacios 102 31 93 48 0.304 0.516 0.820 0.321 0.394 0.715 0.313 0.455 0.767 0.740 -0.9 5.9 5.0 1.04 -0.7 6.2 5.5
2001 TBA Ben Grieve 639 238 542 210 0.372 0.388 0.760 0.331 0.420 0.751 0.352 0.404 0.755 0.760 13.2 -7.8 5.4 0.98 13.5 -8.0 5.5
2024 TBA Junior Caminero 177 53 165 70 0.300 0.424 0.724 0.289 0.371 0.661 0.294 0.398 0.692 0.705 0.8 4.4 5.2 0.97 1.0 4.5 5.5
2019 TEX Nomar Mazara 469 149 429 201 0.318 0.468 0.786 0.322 0.434 0.756 0.320 0.451 0.771 0.763 -0.9 7.2 6.3 1.05 -1.0 6.5 5.5
1974 TEX Tom Grieve 288 88 259 111 0.305 0.429 0.734 0.316 0.372 0.688 0.311 0.400 0.711 0.691 -1.4 7.4 6.0 0.98 -1.5 6.9 5.5
2013 TOR Moises Sierra 122 45 107 49 0.369 0.458 0.827 0.305 0.394 0.699 0.337 0.426 0.763 0.722 3.9 3.4 7.3 1.07 3.1 2.4 5.5
1927 WS1 Topper Rigney 157 59 132 49 0.376 0.371 0.747 0.333 0.386 0.718 0.354 0.378 0.732 0.739 5.2 0.5 5.7 1.00 5.1 0.5 5.5
1963 WS2 Jim King 511 152 459 204 0.297 0.445 0.742 0.325 0.391 0.716 0.311 0.418 0.729 0.688 -7.2 12.5 5.3 0.98 -7.1 12.6 5.5
2014 ANA C. J. Cron 253 73 242 109 0.289 0.451 0.739 0.306 0.386 0.692 0.297 0.418 0.716 0.704 -2.3 7.7 5.4 0.95 -2.4 7.8 5.4
2004 ANA Garret Anderson 475 163 442 197 0.343 0.446 0.789 0.342 0.423 0.765 0.343 0.434 0.777 0.766 0.4 5.3 5.7 1.01 0.3 5.1 5.4
2023 ANA Luis Rengifo 445 151 394 175 0.339 0.444 0.784 0.331 0.428 0.759 0.335 0.436 0.771 0.729 1.9 3.9 5.8 0.99 1.6 3.8 5.4
2022 ANA Luis Rengifo 511 150 489 210 0.294 0.430 0.723 0.305 0.384 0.689 0.300 0.407 0.706 0.700 -2.9 11.2 8.3 1.00 -3.8 9.2 5.4
2016 ARI Chris Herrmann 166 58 148 73 0.349 0.494 0.843 0.330 0.432 0.762 0.340 0.463 0.803 0.731 1.6 4.0 5.6 1.07 1.5 3.9 5.4
1993 BAL Cal Ripken 718 236 641 269 0.329 0.419 0.748 0.325 0.406 0.731 0.327 0.413 0.740 0.742 1.5 4.3 5.8 1.02 1.3 4.1 5.4
1972 BAL Terry Crowley 283 90 247 100 0.318 0.405 0.723 0.318 0.358 0.676 0.318 0.381 0.699 0.645 0.0 5.6 5.6 0.99 0.0 5.4 5.4
1974 BOS Bernie Carbo 402 146 338 140 0.363 0.414 0.778 0.334 0.384 0.718 0.349 0.399 0.748 0.691 5.9 5.3 11.2 1.10 3.8 1.6 5.4
1911 BOS Bill Carrigan 266 97 233 78 0.365 0.335 0.699 0.312 0.343 0.655 0.338 0.339 0.677 0.688 7.1 -1.1 6.0 0.98 7.1 -1.7 5.4
1912 BOS Forrest Cady 152 48 132 53 0.316 0.402 0.718 0.307 0.325 0.633 0.312 0.364 0.675 0.671 0.6 5.0 5.6 1.05 0.6 4.9 5.4
1933 BOS Joe Judge 127 46 108 42 0.362 0.389 0.751 0.365 0.419 0.784 0.364 0.404 0.767 0.727 2.8 2.3 5.1 0.99 2.9 2.5 5.4
2004 BOS Mark Bellhorn 620 231 523 232 0.372 0.443 0.816 0.348 0.444 0.792 0.360 0.444 0.804 0.766 7.5 0.9 8.4 1.09 6.5 -1.1 5.4
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).