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Showing page 177 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
1982 SDN Terry Kennedy 604 197 562 273 0.326 0.486 0.812 0.325 0.371 0.697 0.326 0.429 0.754 0.688 0.3 32.2 32.5 0.98 0.3 32.4 32.7
1963 SLN Curt Flood 714 244 662 267 0.342 0.403 0.745 0.294 0.350 0.644 0.318 0.377 0.694 0.666 17.3 17.8 35.1 1.06 16.1 16.6 32.7
1995 SLN Ray Lankford 553 199 483 248 0.360 0.513 0.873 0.333 0.398 0.731 0.346 0.456 0.802 0.735 7.5 27.6 35.1 1.04 7.0 25.7 32.7
2023 TBA Isaac Paredes 571 201 492 240 0.352 0.488 0.840 0.314 0.404 0.718 0.333 0.446 0.779 0.728 10.8 21.3 32.1 0.99 11.0 21.7 32.7
1954 WS1 Eddie Yost 686 274 538 205 0.399 0.381 0.780 0.318 0.366 0.684 0.359 0.374 0.732 0.700 28.0 4.1 32.1 0.99 28.5 4.2 32.7
1953 BOS Ted Williams 110 56 91 82 0.509 0.901 1.410 0.339 0.383 0.723 0.424 0.642 1.066 0.715 9.4 23.6 32.9 1.01 9.3 23.4 32.6
1914 BRO Jake Daubert 544 193 473 206 0.355 0.436 0.790 0.313 0.341 0.654 0.334 0.388 0.722 0.641 11.4 22.3 33.7 1.05 11.0 21.6 32.6
1991 CHN Andre Dawson 596 180 563 275 0.302 0.488 0.790 0.300 0.369 0.670 0.301 0.429 0.730 0.686 0.5 33.8 34.3 1.01 0.5 32.1 32.6
1984 CHN Leon Durham 548 202 473 239 0.369 0.505 0.874 0.327 0.367 0.694 0.348 0.436 0.784 0.685 11.4 32.9 44.1 1.09 8.4 24.4 32.6
1969 CIN Bobby Tolan 691 236 637 302 0.342 0.474 0.816 0.329 0.378 0.707 0.335 0.426 0.761 0.684 4.1 30.1 34.4 1.02 3.9 28.5 32.6
1991 CIN Hal Morris 537 199 478 229 0.371 0.479 0.850 0.321 0.378 0.699 0.346 0.428 0.774 0.686 13.2 24.1 37.3 1.11 11.5 21.1 32.6
1915 CLE Braggo Roth 173 67 144 73 0.387 0.507 0.894 0.287 0.291 0.578 0.337 0.399 0.736 0.640 11.9 21.2 33.0 1.02 11.8 20.9 32.6
1948 CLE Larry Doby 499 191 438 215 0.383 0.491 0.874 0.349 0.382 0.731 0.366 0.436 0.802 0.726 8.5 23.8 32.3 0.97 8.6 24.0 32.6
1956 CLE Vic Wertz 567 206 481 245 0.363 0.509 0.873 0.342 0.392 0.733 0.352 0.451 0.803 0.731 6.0 27.4 33.5 1.05 5.8 26.7 32.6
1980 DET Lance Parrish 592 192 553 276 0.324 0.499 0.823 0.318 0.390 0.708 0.321 0.444 0.766 0.727 1.7 29.8 31.6 1.03 1.8 30.7 32.6
1951 DET Vic Wertz 582 223 501 256 0.383 0.511 0.894 0.353 0.404 0.757 0.368 0.457 0.825 0.719 8.8 26.7 35.5 1.05 8.1 24.5 32.6
1950 NY1 Monte Irvin 432 169 374 186 0.391 0.497 0.889 0.326 0.398 0.725 0.359 0.448 0.807 0.733 14.0 18.3 32.3 0.99 14.1 18.5 32.6
1983 PHI Joe Lefebvre 295 114 258 140 0.386 0.543 0.929 0.331 0.377 0.708 0.358 0.460 0.819 0.694 8.9 23.6 32.5 1.00 8.9 23.7 32.6
1920 PIT Fred Nicholson 271 107 247 131 0.395 0.530 0.925 0.309 0.354 0.663 0.352 0.442 0.794 0.670 11.7 21.7 33.2 1.00 11.5 21.3 32.6
1932 PIT Pie Traynor 556 205 513 223 0.369 0.435 0.803 0.309 0.372 0.681 0.339 0.403 0.742 0.719 16.6 16.1 32.6 1.00 16.6 16.1 32.6
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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).