Batters



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Showing page 313 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
1967 BOS Joe Foy 499 161 446 190 0.323 0.426 0.749 0.291 0.339 0.630 0.307 0.383 0.689 0.651 8.0 19.2 27.2 1.08 6.1 14.6 20.7
1994 BOS John Valentin 355 140 301 152 0.394 0.505 0.899 0.330 0.431 0.761 0.362 0.468 0.830 0.776 11.3 10.8 22.1 1.03 10.6 10.1 20.7
1912 BOS Larry Gardner 593 221 518 232 0.373 0.448 0.821 0.358 0.386 0.744 0.365 0.417 0.782 0.671 4.4 16.2 20.6 1.01 4.4 16.3 20.7
2014 BOS Mike Napoli 500 185 415 174 0.370 0.419 0.789 0.307 0.390 0.697 0.338 0.405 0.743 0.704 15.8 5.7 21.6 1.03 15.1 5.5 20.7
1999 BOS Mike Stanley 512 201 427 199 0.393 0.466 0.859 0.338 0.436 0.774 0.365 0.451 0.816 0.784 13.8 6.8 20.7 1.05 13.8 6.8 20.7
1955 BRO Pee Wee Reese 652 237 553 223 0.363 0.403 0.767 0.314 0.387 0.701 0.339 0.395 0.734 0.731 16.3 4.4 20.8 1.00 16.2 4.4 20.7
1977 CHA Lamar Johnson 401 137 374 189 0.342 0.505 0.847 0.322 0.411 0.734 0.332 0.458 0.790 0.732 3.9 17.7 21.6 1.02 3.7 17.0 20.7
1966 CHN Adolfo Phillips 473 164 416 188 0.347 0.452 0.799 0.304 0.381 0.685 0.325 0.417 0.742 0.693 10.6 14.9 25.5 1.05 8.6 12.1 20.7
1968 CHN Glenn Beckert 685 222 643 237 0.324 0.369 0.693 0.288 0.329 0.617 0.306 0.349 0.655 0.637 12.5 12.7 25.1 1.08 10.3 10.5 20.7
1993 CIN Reggie Sanders 563 192 496 220 0.341 0.444 0.785 0.313 0.394 0.707 0.327 0.419 0.746 0.722 7.9 12.7 20.7 1.00 7.9 12.7 20.7
1960 CLE John Romano 361 126 316 150 0.349 0.475 0.824 0.315 0.382 0.698 0.332 0.428 0.761 0.711 6.1 14.9 21.0 1.01 6.0 14.7 20.7
2015 HOU George Springer 451 165 388 178 0.366 0.459 0.825 0.314 0.414 0.729 0.340 0.437 0.777 0.728 11.6 9.0 20.6 1.00 11.7 9.0 20.7
1997 LAN Eric Karros 700 230 628 288 0.329 0.459 0.787 0.319 0.407 0.727 0.324 0.433 0.757 0.740 3.3 16.2 19.4 0.96 3.5 17.3 20.7
1973 MIL John Briggs 580 209 488 208 0.360 0.426 0.787 0.332 0.377 0.709 0.346 0.402 0.748 0.707 8.3 12.0 20.3 0.96 8.5 12.2 20.7
1969 MIN Cesar Tovar 591 200 535 222 0.338 0.415 0.753 0.314 0.364 0.678 0.326 0.390 0.716 0.687 7.3 13.8 21.1 1.01 7.2 13.5 20.7
1948 NY1 Walker Cooper 319 106 287 137 0.332 0.477 0.810 0.313 0.356 0.669 0.323 0.416 0.739 0.711 3.0 17.6 20.7 1.01 3.0 17.6 20.7
1943 NYA Billy Johnson 655 223 592 217 0.340 0.367 0.707 0.312 0.334 0.645 0.326 0.350 0.676 0.657 9.5 9.4 19.0 0.97 10.4 10.2 20.7
2025 NYA Jazz Chisholm 531 176 462 222 0.331 0.481 0.812 0.318 0.408 0.726 0.325 0.444 0.769 0.718 3.5 16.3 19.8 0.99 3.7 17.0 20.7
2000 NYN Benny Agbayani 415 162 350 167 0.390 0.477 0.868 0.333 0.429 0.762 0.362 0.453 0.815 0.770 11.9 8.5 20.4 0.99 12.1 8.6 20.7
2020 NYN Dominic Smith 199 75 177 109 0.377 0.616 0.993 0.343 0.428 0.770 0.360 0.522 0.882 0.746 3.4 17.0 20.5 0.98 3.4 17.2 20.7
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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).