Batters



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Showing page 526 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
1951 CIN Connie Ryan 560 194 473 185 0.346 0.391 0.738 0.319 0.386 0.705 0.333 0.389 0.721 0.717 7.5 1.3 8.8 0.98 8.6 1.5 10.1
1986 CIN Eddie Milner 462 146 424 189 0.316 0.446 0.762 0.329 0.377 0.706 0.322 0.411 0.734 0.698 -2.9 14.5 11.6 1.03 -3.2 13.3 10.1
1991 CIN Glenn Braggs 279 90 250 108 0.323 0.432 0.755 0.301 0.367 0.667 0.312 0.399 0.711 0.686 3.0 8.0 11.1 1.02 2.7 7.3 10.1
1989 CIN Ken Griffey 266 92 236 100 0.346 0.424 0.770 0.323 0.366 0.689 0.334 0.395 0.729 0.674 3.1 6.8 9.9 1.09 3.2 6.9 10.1
1966 CIN Leo Cardenas 624 191 568 238 0.306 0.419 0.725 0.303 0.377 0.680 0.305 0.398 0.703 0.693 0.8 11.9 12.7 1.06 0.6 9.5 10.1
1997 CIN Mike Kelly 151 51 140 76 0.338 0.543 0.881 0.324 0.413 0.738 0.331 0.478 0.809 0.740 1.0 9.1 10.1 1.00 1.0 9.1 10.1
1988 CIN Paul O'Neill 533 162 485 201 0.304 0.414 0.718 0.315 0.359 0.674 0.310 0.387 0.696 0.669 -3.0 13.5 10.5 1.03 -3.1 13.2 10.1
2008 COL Garrett Atkins 664 218 611 276 0.328 0.452 0.780 0.320 0.412 0.732 0.324 0.432 0.756 0.740 2.7 12.2 15.0 1.06 1.8 8.2 10.1
2021 DET Akil Baddoo 461 152 413 180 0.330 0.436 0.766 0.316 0.404 0.721 0.323 0.420 0.743 0.730 3.0 6.4 9.4 0.97 3.2 6.9 10.1
1945 DET Don Ross 34 16 29 15 0.471 0.517 0.988 0.291 0.302 0.593 0.381 0.410 0.791 0.665 5.4 6.0 11.4 1.13 4.8 5.3 10.1
1934 DET Goose Goslin 686 254 614 278 0.370 0.453 0.823 0.366 0.422 0.788 0.368 0.437 0.805 0.744 1.6 9.7 11.2 0.97 1.4 8.8 10.1
2013 DET Victor Martinez 668 237 605 260 0.355 0.430 0.785 0.331 0.415 0.746 0.343 0.422 0.765 0.723 7.9 4.6 12.4 1.07 6.4 3.8 10.1
1978 HOU Cesar Cedeno 209 69 192 87 0.330 0.453 0.783 0.307 0.377 0.684 0.319 0.415 0.734 0.688 2.4 7.5 9.8 0.97 2.5 7.7 10.1
1971 HOU Joe Morgan 689 238 583 237 0.345 0.407 0.752 0.325 0.386 0.710 0.335 0.396 0.731 0.679 7.1 5.2 12.3 0.92 5.8 4.3 10.1
1963 KC1 Charley Lau 207 69 187 75 0.333 0.401 0.734 0.316 0.383 0.699 0.325 0.392 0.717 0.688 4.7 5.4 10.1 1.04 4.7 5.4 10.1
2007 LAN Andre Ethier 507 177 447 202 0.349 0.452 0.801 0.337 0.421 0.758 0.343 0.437 0.780 0.753 3.1 7.0 10.1 1.02 3.1 7.0 10.1
1966 LAN Lou Johnson 572 178 526 218 0.311 0.414 0.726 0.303 0.386 0.689 0.307 0.400 0.707 0.693 2.3 7.4 9.8 0.98 2.4 7.6 10.1
1999 MIN Marty Cordova 488 178 425 197 0.365 0.464 0.828 0.342 0.441 0.783 0.353 0.452 0.806 0.784 5.7 4.8 10.5 1.01 5.5 4.6 10.1
1994 MIN Pedro Munoz 268 93 244 124 0.347 0.508 0.855 0.339 0.437 0.776 0.343 0.472 0.816 0.776 1.0 8.6 9.7 0.99 1.0 9.0 10.1
1927 NY1 Jack Cummings 89 35 80 43 0.393 0.538 0.931 0.312 0.375 0.687 0.353 0.456 0.809 0.714 3.6 6.3 10.0 1.01 3.6 6.4 10.1
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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).