Batters



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Showing page 133 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
1956 SLN Ken Boyer 639 221 595 294 0.346 0.494 0.840 0.314 0.400 0.715 0.330 0.447 0.777 0.718 10.0 27.5 37.5 0.99 10.3 28.5 38.8
2014 SLN Matt Holliday 667 247 574 253 0.370 0.441 0.811 0.303 0.381 0.684 0.337 0.411 0.747 0.691 22.6 17.0 39.6 1.00 22.1 16.7 38.8
2006 SLN Scott Rolen 594 219 521 270 0.369 0.518 0.887 0.323 0.426 0.749 0.346 0.472 0.818 0.757 13.8 24.3 38.0 1.00 14.1 24.8 38.8
1956 WS1 Jim Lemon 613 213 538 270 0.347 0.502 0.849 0.325 0.381 0.705 0.336 0.441 0.777 0.731 7.1 32.3 39.4 1.02 7.0 31.8 38.8
1914 BOS Duffy Lewis 598 206 512 204 0.344 0.398 0.743 0.293 0.303 0.596 0.319 0.351 0.670 0.633 15.5 24.3 39.8 0.98 15.1 23.6 38.7
1971 BOS Rico Petrocelli 661 232 553 255 0.351 0.461 0.812 0.305 0.353 0.658 0.328 0.407 0.735 0.678 15.0 30.4 45.3 1.07 12.8 26.0 38.7
1952 CHA Eddie Robinson 681 258 594 277 0.379 0.466 0.845 0.337 0.383 0.720 0.358 0.425 0.783 0.690 14.2 24.8 39.0 1.00 14.1 24.6 38.7
1961 CHA Jim Landis 618 220 534 251 0.356 0.470 0.826 0.315 0.376 0.691 0.336 0.423 0.759 0.720 12.6 25.5 38.1 0.98 12.8 25.9 38.7
1932 CIN Ernie Lombardi 458 170 413 198 0.371 0.479 0.851 0.308 0.367 0.675 0.340 0.423 0.763 0.719 14.5 23.5 38.1 0.99 14.7 23.9 38.7
1915 CLE Ray Chapman 674 229 569 211 0.340 0.371 0.711 0.288 0.297 0.585 0.314 0.334 0.648 0.640 17.5 21.8 39.4 1.02 17.2 21.4 38.7
1969 CLE Tony Horton 669 214 624 288 0.320 0.462 0.781 0.306 0.355 0.661 0.313 0.408 0.721 0.687 4.5 33.4 37.8 0.99 4.6 34.2 38.7
1930 DET Dale Alexander 660 240 602 305 0.364 0.507 0.870 0.328 0.401 0.729 0.346 0.454 0.800 0.763 12.0 31.6 43.7 1.06 10.6 28.0 38.7
1994 FLO Gary Sheffield 384 146 322 188 0.380 0.584 0.964 0.313 0.406 0.719 0.347 0.495 0.842 0.743 12.8 29.0 41.9 1.08 11.8 26.8 38.7
2009 LAN Andre Ethier 685 247 596 303 0.361 0.508 0.869 0.337 0.411 0.747 0.349 0.460 0.808 0.735 8.1 29.4 37.5 1.00 8.4 30.3 38.7
1928 NY1 Bill Terry 649 249 568 294 0.384 0.518 0.901 0.352 0.427 0.779 0.368 0.473 0.840 0.730 10.5 26.1 36.6 0.95 11.1 27.6 38.7
2015 NYA Alex Rodriguez 620 221 523 254 0.356 0.486 0.842 0.307 0.404 0.711 0.332 0.445 0.776 0.728 15.1 22.1 37.2 0.98 15.7 23.0 38.7
2000 NYA Derek Jeter 679 281 593 285 0.414 0.481 0.894 0.334 0.437 0.772 0.374 0.459 0.833 0.790 27.0 13.1 40.1 1.04 26.1 12.6 38.7
1947 PIT Hank Greenberg 510 208 402 192 0.408 0.478 0.885 0.318 0.375 0.693 0.363 0.426 0.789 0.724 22.9 21.0 43.9 1.05 20.2 18.5 38.7
1925 SLA Harry Rice 420 186 354 201 0.443 0.568 1.011 0.355 0.418 0.773 0.399 0.493 0.892 0.757 18.5 26.5 45.0 1.08 15.9 22.8 38.7
2016 SLN Matt Carpenter 566 214 473 239 0.378 0.505 0.883 0.326 0.413 0.739 0.352 0.459 0.811 0.732 14.9 22.4 37.2 0.97 15.5 23.3 38.7
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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).