Batters



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Showing page 17 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
2002 BOS Manny Ramirez 518 233 436 282 0.450 0.647 1.097 0.328 0.422 0.749 0.389 0.534 0.923 0.753 31.6 48.3 79.9 1.02 31.1 47.6 78.7
1993 SEA Ken Griffey 691 282 582 359 0.408 0.617 1.025 0.345 0.407 0.752 0.376 0.512 0.888 0.742 21.8 61.2 83.0 1.04 20.6 58.0 78.6
2004 COL Todd Helton 683 320 547 339 0.469 0.620 1.088 0.342 0.433 0.775 0.405 0.526 0.932 0.752 43.1 51.2 94.4 1.13 35.8 42.6 78.5
2013 ARI Paul Goldschmidt 710 284 602 332 0.400 0.551 0.951 0.311 0.395 0.707 0.356 0.473 0.829 0.700 31.5 47.6 79.0 1.01 31.3 47.2 78.4
2013 BAL Chris Davis 673 249 584 370 0.370 0.634 1.004 0.318 0.403 0.721 0.344 0.518 0.862 0.723 17.5 67.4 84.9 1.07 16.2 62.2 78.4
2019 LAN Cody Bellinger 661 268 558 351 0.405 0.629 1.034 0.327 0.438 0.765 0.366 0.534 0.900 0.752 25.8 52.9 78.7 1.01 25.7 52.7 78.4
2014 ANA Mike Trout 705 266 602 338 0.377 0.561 0.939 0.307 0.396 0.704 0.342 0.479 0.821 0.704 24.7 49.6 74.4 0.96 26.0 52.1 78.2
2016 ATL Freddie Freeman 693 277 589 335 0.400 0.569 0.968 0.320 0.399 0.719 0.360 0.484 0.844 0.732 27.7 49.9 77.6 1.04 27.9 50.3 78.2
1965 CIN Frank Robinson 674 260 582 314 0.386 0.540 0.925 0.302 0.368 0.670 0.344 0.454 0.797 0.681 28.4 49.8 78.2 1.00 28.4 49.8 78.2
2014 PIT Andrew McCutchen 648 266 548 297 0.410 0.542 0.952 0.304 0.390 0.694 0.357 0.466 0.823 0.691 34.4 41.5 75.9 0.97 35.4 42.7 78.1
2019 WAS Anthony Rendon 646 266 545 326 0.412 0.598 1.010 0.315 0.426 0.741 0.363 0.512 0.875 0.752 31.4 47.4 78.7 1.01 31.2 47.0 78.1
1993 OAK Rickey Henderson 407 191 318 176 0.469 0.553 1.023 0.324 0.404 0.728 0.397 0.478 0.875 0.742 37.5 37.7 75.2 0.97 38.9 39.1 78.0
2002 CHN Sammy Sosa 666 266 556 330 0.399 0.594 0.993 0.320 0.408 0.729 0.360 0.501 0.861 0.738 26.5 51.9 78.4 1.01 26.3 51.6 77.9
1929 NYA Tony Lazzeri 639 268 546 306 0.419 0.560 0.980 0.325 0.391 0.716 0.372 0.476 0.848 0.747 29.9 46.1 76.0 0.96 30.6 47.3 77.9
1997 SEA Ken Griffey 704 269 608 393 0.382 0.646 1.028 0.348 0.442 0.789 0.365 0.544 0.909 0.766 11.9 62.4 74.4 0.97 12.5 65.3 77.9
1969 HOU Jim Wynn 653 284 495 251 0.435 0.507 0.942 0.305 0.368 0.672 0.370 0.437 0.807 0.684 42.6 34.6 77.3 1.00 42.9 34.8 77.8
1994 CLE Albert Belle 480 210 412 294 0.438 0.714 1.151 0.337 0.439 0.776 0.387 0.576 0.963 0.776 24.2 56.5 80.7 1.02 23.3 54.3 77.6
1915 DET Ty Cobb 701 337 563 274 0.481 0.487 0.967 0.346 0.356 0.703 0.414 0.421 0.835 0.640 47.0 36.5 83.6 1.06 43.6 33.9 77.6
1984 ATL Dale Murphy 691 257 607 332 0.372 0.547 0.919 0.303 0.360 0.664 0.338 0.454 0.791 0.685 23.8 56.4 80.2 1.03 23.0 54.5 77.5
2006 CLE Travis Hafner 564 247 454 299 0.438 0.659 1.097 0.332 0.432 0.764 0.385 0.545 0.930 0.775 29.9 52.0 81.9 1.06 28.3 49.2 77.5
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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).