Batters



Reset All Picks
Showing page 192 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
1969 MIN Rod Carew 504 192 458 214 0.381 0.467 0.848 0.326 0.388 0.714 0.354 0.428 0.781 0.687 13.7 18.0 31.8 1.05 13.4 17.6 31.1
1974 MON Mike Jorgensen 366 161 287 140 0.440 0.488 0.928 0.338 0.381 0.720 0.389 0.434 0.824 0.688 18.6 15.6 34.3 1.04 16.9 14.1 31.1
1925 NYA Babe Ruth 426 165 359 195 0.387 0.543 0.930 0.353 0.415 0.767 0.370 0.479 0.849 0.757 7.3 23.2 30.6 0.98 7.4 23.6 31.1
2003 OAK Eric Chavez 654 229 588 302 0.350 0.514 0.864 0.338 0.425 0.763 0.344 0.469 0.813 0.759 3.9 26.0 29.9 0.97 4.1 27.0 31.1
2013 PHI Chase Utley 531 185 476 226 0.348 0.475 0.823 0.316 0.382 0.698 0.332 0.428 0.761 0.700 8.6 22.4 30.9 1.04 8.7 22.5 31.1
2014 PIT Russell Martin 460 184 379 163 0.400 0.430 0.830 0.306 0.389 0.695 0.353 0.410 0.763 0.691 21.6 8.2 29.9 0.98 22.5 8.5 31.1
2019 SLN Paul Goldschmidt 682 235 597 284 0.345 0.476 0.820 0.306 0.417 0.723 0.325 0.446 0.772 0.752 13.1 17.9 31.0 1.00 13.1 18.0 31.1
1939 SLN Terry Moore 480 168 417 203 0.350 0.487 0.837 0.318 0.376 0.694 0.334 0.432 0.765 0.713 7.8 23.0 30.8 1.00 7.9 23.2 31.1
1980 TEX Al Oliver 709 253 656 315 0.357 0.480 0.837 0.334 0.402 0.736 0.345 0.441 0.787 0.727 8.0 25.7 33.7 1.02 7.4 23.7 31.1
2022 TOR Bo Bichette 697 232 652 306 0.333 0.469 0.802 0.310 0.399 0.709 0.322 0.434 0.756 0.700 7.9 23.4 31.3 1.00 7.8 23.3 31.1
1980 BOS Carlton Fisk 530 187 478 223 0.353 0.467 0.819 0.312 0.380 0.692 0.333 0.423 0.756 0.727 10.8 21.1 31.9 1.03 10.5 20.5 31.0
1928 BRO Rube Bressler 610 233 501 215 0.382 0.429 0.811 0.327 0.387 0.714 0.354 0.408 0.762 0.730 16.9 10.8 27.7 0.97 18.9 12.1 31.0
1973 CHN Ron Santo 604 210 536 236 0.348 0.440 0.788 0.307 0.361 0.668 0.327 0.401 0.728 0.694 12.2 21.0 33.2 1.02 11.4 19.6 31.0
1943 CIN Frank McCormick 506 173 472 195 0.342 0.413 0.755 0.303 0.332 0.635 0.322 0.373 0.695 0.666 9.8 19.2 28.9 0.97 10.5 20.6 31.0
1945 CIN Frank McCormick 644 221 580 223 0.343 0.384 0.728 0.299 0.327 0.626 0.321 0.356 0.677 0.691 14.3 16.8 31.0 0.99 14.3 16.8 31.0
1966 HOU Joe Morgan 528 213 425 166 0.403 0.391 0.794 0.308 0.367 0.675 0.356 0.379 0.734 0.693 25.2 4.8 30.1 0.99 26.0 4.9 31.0
1969 MIN Rich Reese 451 163 419 215 0.361 0.513 0.875 0.331 0.395 0.726 0.346 0.454 0.800 0.687 6.8 24.8 31.6 1.04 6.7 24.3 31.0
1924 NY1 Frankie Frisch 675 256 603 282 0.379 0.468 0.847 0.344 0.409 0.753 0.361 0.438 0.800 0.721 11.9 17.3 29.3 0.95 12.6 18.3 31.0
1929 NYA Earle Combs 665 272 584 274 0.409 0.469 0.878 0.352 0.423 0.775 0.380 0.446 0.827 0.747 19.1 14.2 33.3 1.02 17.8 13.2 31.0
2000 NYA Glenallen Hill 143 54 132 97 0.378 0.735 1.112 0.347 0.450 0.796 0.362 0.592 0.954 0.790 5.2 27.8 33.0 1.05 4.9 26.1 31.0
Total 10865 3986 9599 4474 242.7 381.2 624.2 242.8 377.9 621.0

*** 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. ***










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).