Batters



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Showing page 329 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
2008 CLE Jhonny Peralta 664 219 605 286 0.330 0.473 0.803 0.323 0.408 0.730 0.326 0.440 0.766 0.754 2.2 19.4 21.6 0.97 2.0 17.7 19.7
2022 CLE Josh Naylor 498 159 449 203 0.319 0.452 0.771 0.305 0.381 0.687 0.312 0.417 0.729 0.700 3.5 16.2 19.7 1.02 3.5 16.2 19.7
1955 CLE Ralph Kiner 390 143 321 145 0.367 0.452 0.818 0.326 0.382 0.708 0.346 0.417 0.763 0.713 7.9 11.1 19.0 1.00 8.2 11.5 19.7
2017 COL Jonathan Lucroy 175 75 142 62 0.429 0.437 0.865 0.319 0.427 0.746 0.374 0.432 0.806 0.746 17.0 5.6 22.6 1.05 14.8 4.9 19.7
1931 DET John Stone 648 249 584 270 0.384 0.462 0.847 0.353 0.420 0.772 0.368 0.441 0.810 0.735 10.2 12.2 22.4 1.04 9.0 10.7 19.7
1972 DET Norm Cash 501 168 440 196 0.335 0.445 0.781 0.319 0.363 0.682 0.327 0.404 0.731 0.645 4.1 18.5 22.6 1.16 3.6 16.1 19.7
1965 KC1 Ed Charles 535 177 480 186 0.331 0.388 0.718 0.294 0.352 0.646 0.312 0.370 0.682 0.676 9.8 8.6 18.5 0.96 10.4 9.2 19.7
1956 KC1 Vic Power 559 189 530 237 0.338 0.447 0.785 0.327 0.383 0.710 0.332 0.415 0.747 0.731 3.3 16.9 20.2 1.02 3.2 16.5 19.7
1972 LAN Willie Davis 654 206 615 271 0.315 0.441 0.756 0.321 0.367 0.689 0.318 0.404 0.722 0.676 -2.1 22.3 20.1 0.95 -2.1 21.9 19.7
1991 MIL Willie Randolph 512 216 431 161 0.422 0.374 0.795 0.324 0.397 0.721 0.373 0.385 0.758 0.721 25.2 -4.7 20.5 1.03 24.5 -4.8 19.7
2023 MIN Edouard Julien 408 155 338 155 0.380 0.459 0.838 0.319 0.412 0.731 0.349 0.435 0.785 0.728 12.5 7.9 20.5 1.03 12.0 7.6 19.7
1988 MON Tim Raines 488 171 429 185 0.350 0.431 0.782 0.321 0.365 0.686 0.336 0.398 0.734 0.669 7.1 13.9 21.1 1.08 6.6 13.0 19.7
1937 NY1 Jo-Jo Moore 633 229 580 255 0.362 0.440 0.801 0.339 0.400 0.740 0.351 0.420 0.771 0.709 7.0 11.5 18.4 0.97 7.5 12.3 19.7
1910 NYA Bert Daniels 424 149 356 121 0.351 0.340 0.691 0.287 0.307 0.594 0.319 0.323 0.643 0.613 14.7 6.5 21.2 1.03 13.7 6.0 19.7
1920 NYA Roger Peckinpaugh 623 219 534 207 0.352 0.388 0.739 0.314 0.354 0.669 0.333 0.371 0.704 0.723 11.5 8.5 20.0 1.01 11.3 8.4 19.7
1916 NYA Roger Peckinpaugh 631 203 551 191 0.322 0.347 0.668 0.293 0.306 0.600 0.308 0.327 0.634 0.635 8.8 11.4 20.2 1.02 8.6 11.1 19.7
1972 NYA Thurman Munson 568 193 511 186 0.340 0.364 0.704 0.297 0.340 0.637 0.318 0.352 0.671 0.645 12.2 6.0 18.2 0.97 13.2 6.5 19.7
2003 NYN Jason Phillips 453 169 403 178 0.373 0.442 0.815 0.317 0.410 0.727 0.345 0.426 0.771 0.745 12.6 6.5 19.1 0.99 13.0 6.7 19.7
1978 NYN Lee Mazzilli 619 218 542 234 0.352 0.432 0.784 0.331 0.385 0.717 0.342 0.408 0.750 0.688 6.5 13.3 19.8 1.01 6.5 13.2 19.7
2015 OAK Danny Valencia 205 73 183 97 0.356 0.530 0.886 0.304 0.400 0.704 0.330 0.465 0.795 0.728 6.9 12.4 19.4 0.98 7.0 12.6 19.7
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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).