Batters



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Showing page 172 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
1940 PIT Arky Vaughan 689 269 594 269 0.390 0.453 0.843 0.339 0.399 0.738 0.365 0.426 0.791 0.697 17.6 15.7 33.4 1.00 17.5 15.7 33.3
1969 SDN Nate Colbert 532 171 483 233 0.321 0.482 0.804 0.304 0.361 0.665 0.313 0.422 0.734 0.684 4.8 29.2 33.9 1.03 4.7 28.7 33.3
2013 WAS Bryce Harper 497 182 424 206 0.366 0.486 0.852 0.315 0.382 0.697 0.340 0.434 0.774 0.700 12.9 21.4 34.3 1.02 12.5 20.8 33.3
2016 WAS Trea Turner 324 120 307 174 0.370 0.567 0.937 0.312 0.413 0.724 0.341 0.490 0.831 0.732 9.5 23.5 33.0 1.00 9.6 23.7 33.3
2004 CHN Derrek Lee 688 244 605 305 0.355 0.504 0.859 0.317 0.426 0.744 0.336 0.465 0.801 0.752 13.0 23.5 36.5 1.06 11.8 21.4 33.2
1931 CHN Woody English 727 276 634 260 0.380 0.410 0.790 0.321 0.375 0.695 0.350 0.392 0.743 0.716 21.2 11.6 32.8 0.99 21.5 11.7 33.2
1943 CLE Roy Cullenbine 598 238 488 197 0.398 0.404 0.802 0.325 0.358 0.683 0.361 0.381 0.742 0.657 21.9 11.5 33.4 0.98 21.8 11.4 33.2
2014 COL Justin Morneau 550 200 502 249 0.364 0.496 0.860 0.319 0.392 0.711 0.341 0.444 0.785 0.691 12.3 26.3 38.6 1.13 10.6 22.6 33.2
2021 HOU Carlos Correa 640 234 555 269 0.366 0.485 0.850 0.320 0.423 0.743 0.343 0.454 0.797 0.730 14.9 17.4 32.3 0.98 15.3 17.9 33.2
1994 KCA Bob Hamelin 375 145 312 187 0.387 0.599 0.986 0.349 0.427 0.776 0.368 0.513 0.881 0.776 7.1 26.8 33.9 1.03 7.0 26.2 33.2
1990 NYN Kevin McReynolds 601 212 521 237 0.353 0.455 0.808 0.305 0.382 0.687 0.329 0.418 0.747 0.700 14.1 19.2 33.3 0.99 14.1 19.1 33.2
1977 SDN Dave Winfield 678 227 615 287 0.335 0.467 0.801 0.313 0.385 0.698 0.324 0.426 0.750 0.721 7.2 25.8 33.0 0.96 7.2 26.0 33.2
1983 SFN Jack Clark 574 207 492 217 0.361 0.441 0.802 0.306 0.370 0.677 0.334 0.406 0.739 0.694 15.5 17.6 33.0 1.00 15.6 17.7 33.2
2008 SLN Troy Glaus 637 237 544 263 0.372 0.483 0.856 0.323 0.415 0.739 0.348 0.449 0.797 0.740 15.5 17.9 33.4 1.00 15.4 17.8 33.2
1984 TOR George Bell 643 209 606 302 0.325 0.498 0.823 0.314 0.395 0.709 0.320 0.446 0.766 0.722 3.5 31.2 34.7 1.02 3.3 29.9 33.2
2020 ATL Freddie Freeman 262 121 214 137 0.462 0.640 1.102 0.345 0.447 0.792 0.403 0.543 0.947 0.746 15.3 20.3 35.6 1.06 14.2 18.9 33.1
2010 ATL Jason Heyward 623 245 520 237 0.393 0.456 0.849 0.330 0.408 0.738 0.362 0.432 0.794 0.720 19.6 13.4 33.0 0.99 19.7 13.4 33.1
1980 BAL Eddie Murray 683 242 621 322 0.354 0.519 0.873 0.346 0.423 0.768 0.350 0.471 0.820 0.727 3.1 29.9 33.0 1.00 3.1 30.0 33.1
1994 CHA Julio Franco 505 205 433 221 0.406 0.510 0.916 0.333 0.433 0.766 0.370 0.472 0.841 0.776 18.3 17.5 35.8 1.05 16.9 16.2 33.1
2012 KCA Alex Gordon 721 265 642 292 0.368 0.455 0.822 0.317 0.405 0.722 0.342 0.430 0.772 0.729 18.1 15.9 34.1 1.03 17.6 15.4 33.1
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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).