Batters



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Showing page 362 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
2008 FLO Cody Ross 506 160 461 225 0.316 0.488 0.804 0.322 0.405 0.727 0.319 0.447 0.766 0.740 -1.6 19.5 17.8 1.00 -1.6 19.4 17.7
1968 HOU Doug Rader 371 121 333 131 0.326 0.393 0.720 0.286 0.331 0.616 0.306 0.362 0.668 0.637 7.5 10.3 17.8 1.00 7.5 10.2 17.7
2016 HOU Evan Gattis 499 159 447 227 0.319 0.508 0.826 0.323 0.426 0.749 0.321 0.467 0.788 0.743 -1.1 18.0 16.9 0.93 -1.1 18.8 17.7
1995 KCA Gary Gaetti 578 189 514 266 0.327 0.518 0.844 0.339 0.437 0.776 0.333 0.477 0.810 0.769 -3.4 21.0 17.5 0.99 -3.4 21.2 17.7
1980 KCA John Wathan 510 191 453 184 0.375 0.406 0.781 0.319 0.391 0.710 0.347 0.399 0.746 0.727 14.1 3.6 17.7 1.00 14.1 3.6 17.7
1915 KCF Duke Kenworthy 449 155 396 171 0.345 0.432 0.777 0.329 0.365 0.694 0.337 0.399 0.736 0.651 3.6 13.3 16.9 0.96 3.8 13.9 17.7
2000 LAN Adrian Beltre 575 206 510 242 0.358 0.475 0.833 0.332 0.435 0.767 0.345 0.455 0.800 0.770 7.5 10.6 18.2 0.98 7.3 10.3 17.7
1969 LAN Manny Mota 336 122 294 118 0.363 0.401 0.764 0.311 0.368 0.679 0.337 0.385 0.722 0.684 9.5 7.0 16.6 0.97 10.1 7.5 17.7
2012 MIA Jose Reyes 716 247 642 278 0.345 0.433 0.778 0.322 0.408 0.730 0.334 0.421 0.754 0.715 8.2 8.4 16.5 0.99 8.8 9.0 17.7
2017 MIN Eddie Rosario 589 192 542 275 0.326 0.507 0.833 0.330 0.426 0.756 0.328 0.467 0.795 0.752 -1.2 22.2 21.0 1.03 -1.4 19.1 17.7
1989 MON Hubie Brooks 593 188 542 219 0.317 0.404 0.721 0.294 0.358 0.652 0.305 0.381 0.687 0.674 7.0 12.5 19.5 1.03 6.4 11.3 17.7
1970 MON Mack Jones 345 137 271 124 0.397 0.458 0.855 0.339 0.396 0.736 0.368 0.427 0.795 0.718 10.0 7.8 17.8 1.02 9.9 7.8 17.7
1978 MON Warren Cromartie 655 220 607 254 0.336 0.418 0.754 0.326 0.375 0.700 0.331 0.397 0.727 0.688 3.3 13.6 16.9 0.99 3.5 14.2 17.7
2020 NYA Luke Voit 234 79 213 130 0.338 0.610 0.948 0.332 0.442 0.775 0.335 0.526 0.861 0.732 0.6 17.9 18.6 1.02 0.6 17.0 17.7
1992 NYN Chico Walker 257 94 227 96 0.366 0.423 0.789 0.324 0.373 0.697 0.345 0.398 0.743 0.679 7.6 9.4 17.0 0.97 7.9 9.8 17.7
1999 NYN Darryl Hamilton 189 77 168 82 0.407 0.488 0.896 0.351 0.427 0.777 0.379 0.457 0.836 0.768 7.3 10.3 17.6 1.00 7.3 10.4 17.7
2005 OAK Eric Byrnes 215 72 192 91 0.335 0.474 0.809 0.334 0.433 0.766 0.334 0.453 0.788 0.753 4.5 13.7 18.3 1.01 4.4 13.2 17.7
1970 OAK Gene Tenace 128 55 105 59 0.430 0.562 0.992 0.310 0.367 0.677 0.370 0.464 0.834 0.697 7.6 10.4 18.0 1.02 7.5 10.2 17.7
1977 PHI Bob Boone 495 169 440 192 0.341 0.436 0.778 0.313 0.386 0.700 0.327 0.411 0.739 0.721 6.9 11.1 18.1 1.00 6.7 10.9 17.7
2012 PHI Chase Utley 362 132 301 129 0.365 0.429 0.793 0.311 0.385 0.696 0.338 0.407 0.745 0.715 9.6 6.7 16.3 0.97 10.4 7.3 17.7
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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).