Batters



Reset All Picks
Showing page 102 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 CHN Aramis Ramirez 645 245 554 287 0.380 0.518 0.898 0.319 0.416 0.735 0.349 0.467 0.816 0.740 19.7 28.6 48.5 1.02 18.0 26.1 44.3
1947 CLE Lou Boudreau 624 237 538 228 0.380 0.424 0.804 0.311 0.341 0.652 0.345 0.383 0.728 0.693 21.7 22.1 43.8 0.98 21.9 22.4 44.3
1965 DET Al Kaline 474 184 399 188 0.388 0.471 0.859 0.299 0.356 0.655 0.344 0.414 0.757 0.676 21.1 23.2 44.2 1.02 21.1 23.3 44.3
1925 NY1 Irish Meusel 558 198 516 283 0.355 0.548 0.903 0.330 0.405 0.735 0.342 0.477 0.819 0.754 6.9 36.9 44.0 0.98 6.9 37.2 44.3
2006 NYA Derek Jeter 715 295 623 301 0.413 0.483 0.896 0.332 0.435 0.767 0.372 0.459 0.831 0.775 28.9 14.8 43.7 0.99 29.3 15.0 44.3
1949 NYA Tommy Henrich 502 209 411 216 0.416 0.526 0.942 0.349 0.389 0.738 0.383 0.457 0.840 0.727 16.8 28.5 45.3 1.01 16.4 27.9 44.3
1934 PIT Arky Vaughan 660 282 558 285 0.427 0.511 0.938 0.351 0.427 0.778 0.389 0.469 0.858 0.722 25.1 24.2 49.2 1.05 22.6 21.8 44.3
1994 SFN Matt Williams 483 154 445 270 0.319 0.607 0.926 0.313 0.406 0.719 0.316 0.506 0.822 0.743 1.5 45.4 46.9 1.09 1.4 42.9 44.3
1933 WS1 Joe Cronin 697 276 602 268 0.396 0.445 0.841 0.331 0.377 0.708 0.363 0.411 0.775 0.727 22.8 20.2 43.0 0.97 23.5 20.8 44.3
2009 ANA Kendrys Morales 622 221 566 322 0.355 0.569 0.924 0.345 0.432 0.777 0.350 0.501 0.850 0.762 3.4 38.9 42.3 0.99 3.6 40.6 44.2
1987 CAL Wally Joyner 653 238 564 298 0.364 0.528 0.893 0.328 0.413 0.741 0.346 0.471 0.817 0.756 11.8 33.2 44.9 1.02 11.6 32.7 44.2
1915 CHF Les Mann 516 183 471 208 0.355 0.442 0.796 0.296 0.324 0.620 0.325 0.383 0.708 0.651 15.1 28.0 43.0 0.97 15.5 28.8 44.2
2005 CHN Aramis Ramirez 506 181 463 263 0.358 0.568 0.926 0.319 0.417 0.736 0.339 0.492 0.831 0.741 9.7 35.2 45.0 0.99 9.5 34.6 44.2
1912 PHI Dode Paskert 649 268 540 223 0.413 0.413 0.826 0.321 0.358 0.679 0.367 0.385 0.752 0.700 29.8 15.3 45.0 1.02 29.3 15.0 44.2
2005 PHI Pat Burrell 669 260 562 283 0.389 0.504 0.892 0.320 0.409 0.729 0.354 0.456 0.811 0.741 23.0 26.0 49.1 1.06 20.7 23.4 44.2
1992 SLN Ray Lankford 682 252 598 287 0.370 0.480 0.849 0.325 0.374 0.698 0.347 0.427 0.774 0.679 15.3 31.8 47.1 1.04 14.4 29.8 44.2
1993 ATL Fred McGriff 291 114 255 156 0.392 0.612 1.004 0.333 0.391 0.725 0.362 0.502 0.864 0.722 10.8 35.4 46.2 1.03 10.3 33.8 44.1
1975 CHN Jose Cardenal 666 263 574 243 0.395 0.423 0.818 0.313 0.359 0.672 0.354 0.391 0.745 0.691 27.1 18.5 45.6 1.03 26.2 17.9 44.1
1952 CIN Ted Kluszewski 549 211 496 253 0.384 0.510 0.894 0.337 0.381 0.718 0.360 0.446 0.806 0.693 13.1 32.1 45.3 0.98 12.8 31.2 44.1
2018 COL Charlie Blackmon 696 249 626 314 0.358 0.502 0.859 0.312 0.389 0.701 0.335 0.445 0.780 0.720 16.0 35.7 51.7 1.08 13.6 30.5 44.1
No results found.

*** The information used here was obtained free of charge from and is copyrighted by Retrosheet. Interested parties may contact Retrosheet at 20 Sunset Rd., Newark, DE 19711. ***










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).