Batters



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Showing page 116 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
1931 DET Dale Alexander 583 234 517 230 0.401 0.445 0.846 0.320 0.371 0.691 0.361 0.408 0.768 0.735 23.9 19.0 42.8 1.04 23.3 18.5 41.7
1991 LAN Darryl Strawberry 588 212 505 248 0.361 0.491 0.852 0.321 0.363 0.684 0.341 0.427 0.768 0.686 11.6 32.6 44.3 1.05 10.9 30.7 41.7
1980 MIL Robin Yount 647 206 611 317 0.318 0.519 0.837 0.316 0.389 0.705 0.317 0.454 0.771 0.727 0.8 39.5 40.3 0.98 0.8 40.9 41.7
1967 MIN Tony Oliva 615 213 557 258 0.346 0.463 0.810 0.302 0.358 0.661 0.324 0.411 0.735 0.651 13.5 29.3 42.8 1.05 13.2 28.5 41.7
1939 NY1 Harry Danning 563 200 520 249 0.355 0.479 0.834 0.312 0.371 0.684 0.334 0.425 0.759 0.713 12.1 27.9 40.1 0.99 12.6 29.0 41.7
1970 OAK Sal Bando 636 256 502 216 0.403 0.430 0.833 0.312 0.375 0.688 0.357 0.403 0.760 0.697 28.7 14.2 42.8 1.02 28.0 13.8 41.7
1929 PHI Pinky Whitney 697 263 612 295 0.377 0.482 0.859 0.331 0.393 0.724 0.354 0.437 0.792 0.773 16.0 27.7 43.7 1.04 15.3 26.4 41.7
1912 SLA Del Pratt 620 209 569 243 0.337 0.427 0.764 0.300 0.322 0.621 0.318 0.374 0.693 0.671 11.6 30.3 41.9 1.01 11.5 30.2 41.7
2012 SLN Yadier Molina 563 209 505 253 0.371 0.501 0.872 0.312 0.402 0.715 0.342 0.452 0.794 0.715 16.5 24.6 41.1 0.99 16.7 25.0 41.7
1997 TEX Rusty Greer 690 279 601 319 0.404 0.531 0.935 0.346 0.438 0.784 0.375 0.484 0.860 0.766 19.9 27.8 47.7 1.05 17.4 24.3 41.7
1921 BRO Jimmy Johnston 688 249 624 288 0.362 0.462 0.823 0.314 0.379 0.694 0.338 0.420 0.759 0.726 16.4 25.5 41.9 1.02 16.3 25.3 41.6
1987 CAL Brian Downing 695 277 567 276 0.399 0.487 0.885 0.330 0.430 0.759 0.364 0.458 0.822 0.756 24.0 16.8 40.9 0.98 24.4 17.1 41.6
1920 CLE Steve O'Neill 578 231 489 215 0.400 0.440 0.839 0.323 0.368 0.691 0.361 0.404 0.765 0.723 22.1 17.6 39.7 0.98 23.2 18.4 41.6
2008 FLO Dan Uggla 619 223 531 273 0.360 0.514 0.874 0.320 0.408 0.728 0.340 0.461 0.801 0.740 12.6 28.8 41.4 1.01 12.7 28.9 41.6
1973 LAN Joe Ferguson 585 216 487 229 0.369 0.470 0.839 0.310 0.368 0.677 0.340 0.419 0.758 0.694 17.4 24.5 41.9 1.01 17.3 24.3 41.6
1950 PHI Andy Seminick 468 187 393 206 0.400 0.524 0.924 0.328 0.399 0.727 0.364 0.462 0.825 0.733 16.8 24.5 41.4 0.98 16.9 24.6 41.6
1999 PHI Mike Lieberthal 574 208 510 281 0.362 0.551 0.913 0.328 0.424 0.752 0.345 0.488 0.833 0.768 10.0 32.9 42.8 0.99 9.7 32.0 41.6
1989 SDN Tony Gwynn 679 260 604 256 0.383 0.424 0.807 0.315 0.361 0.676 0.349 0.392 0.741 0.674 23.1 19.2 42.2 1.02 22.8 18.9 41.6
1969 BAL Paul Blair 685 220 625 298 0.321 0.477 0.798 0.310 0.357 0.667 0.316 0.417 0.732 0.687 3.9 37.4 41.2 1.00 3.9 37.7 41.5
1946 BRO Eddie Stanky 642 271 483 170 0.422 0.352 0.774 0.306 0.335 0.641 0.364 0.344 0.708 0.678 37.3 4.7 41.9 1.02 36.9 4.7 41.5
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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).