Batters



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Showing page 62 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
2017 COL Charlie Blackmon 725 288 644 387 0.397 0.601 0.998 0.331 0.426 0.757 0.364 0.514 0.878 0.746 24.1 56.8 80.8 1.14 16.3 38.5 54.7
1927 DET Bob Fothergill 593 237 528 272 0.400 0.515 0.915 0.328 0.384 0.712 0.364 0.450 0.813 0.739 21.2 34.6 55.8 1.04 20.8 33.9 54.7
1991 PIT Bobby Bonilla 680 266 577 284 0.391 0.492 0.883 0.327 0.384 0.711 0.359 0.438 0.797 0.686 21.6 31.0 52.7 0.97 22.4 32.2 54.7
2013 TEX Adrian Beltre 690 256 631 321 0.371 0.509 0.880 0.313 0.401 0.714 0.342 0.455 0.797 0.723 20.2 34.8 55.0 1.01 20.1 34.6 54.7
2009 WAS Adam Dunn 668 266 546 289 0.398 0.529 0.928 0.334 0.412 0.746 0.366 0.471 0.837 0.735 21.5 33.6 55.1 1.04 21.3 33.4 54.7
1957 BRO Gil Hodges 654 238 579 296 0.364 0.511 0.875 0.307 0.380 0.687 0.335 0.446 0.781 0.719 18.7 38.1 56.8 1.03 18.0 36.6 54.6
1930 CIN Harry Heilmann 539 218 459 265 0.404 0.577 0.982 0.336 0.423 0.760 0.370 0.500 0.871 0.799 18.5 35.3 53.8 0.96 18.8 35.8 54.6
1978 CLE Andre Thornton 617 232 508 262 0.376 0.516 0.892 0.315 0.383 0.699 0.346 0.450 0.795 0.707 18.6 34.0 52.6 0.97 19.3 35.3 54.6
1949 NY1 Bobby Thomson 689 244 641 332 0.354 0.518 0.872 0.321 0.384 0.705 0.338 0.451 0.789 0.719 11.3 43.2 54.5 1.00 11.3 43.3 54.6
1971 NYN Cleon Jones 568 216 505 239 0.380 0.473 0.854 0.301 0.352 0.653 0.341 0.412 0.753 0.679 22.3 31.5 53.7 0.99 22.7 32.0 54.6
1974 PIT Richie Zisk 604 233 536 255 0.386 0.476 0.862 0.308 0.354 0.662 0.347 0.415 0.762 0.688 23.4 32.9 56.3 1.02 22.7 31.9 54.6
1987 SFN Will Clark 588 217 529 307 0.369 0.580 0.949 0.333 0.400 0.733 0.351 0.490 0.841 0.728 10.6 48.1 58.6 1.03 9.9 44.8 54.6
1952 BSN Sid Gordon 607 231 523 252 0.381 0.482 0.862 0.308 0.367 0.675 0.344 0.424 0.769 0.693 22.0 30.5 52.6 0.98 22.8 31.6 54.5
2010 COL Carlos Gonzalez 636 239 587 351 0.376 0.598 0.974 0.323 0.395 0.717 0.349 0.496 0.846 0.720 16.9 60.0 76.9 1.14 12.0 42.5 54.5
2018 COL Nolan Arenado 673 251 590 331 0.373 0.561 0.934 0.305 0.398 0.703 0.339 0.479 0.818 0.720 23.0 48.1 71.1 1.12 17.6 36.9 54.5
1994 NYA Paul O'Neill 443 204 368 222 0.460 0.603 1.064 0.357 0.443 0.800 0.409 0.523 0.932 0.776 23.1 29.6 52.7 1.00 23.9 30.6 54.5
2010 SDN Adrian Gonzalez 693 271 591 302 0.391 0.511 0.902 0.325 0.401 0.726 0.358 0.456 0.814 0.720 22.9 32.7 55.4 0.95 22.5 32.2 54.5
1930 CHN Woody English 755 320 638 326 0.424 0.511 0.935 0.342 0.436 0.778 0.383 0.473 0.856 0.799 30.9 23.9 54.8 1.02 30.7 23.7 54.4
1968 PIT Roberto Clemente 557 198 502 242 0.355 0.482 0.838 0.289 0.338 0.627 0.322 0.410 0.732 0.637 18.5 36.4 54.9 1.01 18.3 36.1 54.4
1967 SFN Willie McCovey 539 203 456 244 0.377 0.535 0.912 0.316 0.365 0.681 0.347 0.450 0.796 0.669 16.3 38.7 55.0 1.03 16.1 38.3 54.4
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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).