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MLB Batting Splits 2025

Performance splits by handedness, home/away, and situational categories.

Batting splits break down a hitter's performance across different game situations. Platoon splits (vs LHP/RHP) are the most predictive for DFS and prop betting. Minimum 10 at-bats displayed.
Luis Garcia headshot
Colorado Rockies
1.153 OPS
AVG .421
OBP .522
SLG .632
HR 1
AB 19
H 8
RBI 2
Spencer Torkelson headshot
Atlanta Braves
1.152 OPS
AVG .273
OBP .333
SLG .818
HR 2
AB 11
H 3
RBI 4
Yoan Moncada headshot
Toronto Blue Jays
1.152 OPS
AVG .273
OBP .333
SLG .818
HR 2
AB 11
H 3
RBI 4
Brandon Lowe headshot
Washington Nationals
1.152 OPS
AVG .273
OBP .333
SLG .818
HR 2
AB 11
H 3
RBI 6
Junior Caminero headshot
Atlanta Braves
1.152 OPS
AVG .273
OBP .333
SLG .818
HR 2
AB 11
H 3
RBI 4
Jake Cronenworth headshot
Washington Nationals
1.151 OPS
AVG .389
OBP .429
SLG .722
HR 1
AB 18
H 7
RBI 4
Austin Hays headshot
New York Mets
1.150 OPS
AVG .300
OBP .400
SLG .750
HR 3
AB 20
H 6
RBI 6
Luis Garcia headshot
Philadelphia Phillies
1.148 OPS
AVG .371
OBP .405
SLG .743
HR 3
AB 35
H 13
RBI 6
Mike Trout headshot
Boston Red Sox
1.148 OPS
AVG .389
OBP .593
SLG .556
HR 1
AB 18
H 7
RBI 4
Gunnar Henderson headshot
Oakland Athletics
1.147 OPS
AVG .412
OBP .500
SLG .647
HR 1
AB 17
H 7
RBI 4
Junior Caminero headshot
Houston Astros
1.146 OPS
AVG .320
OBP .346
SLG .800
HR 3
AB 25
H 8
RBI 11
TJ Friedl headshot
Atlanta Braves
1.145 OPS
AVG .333
OBP .478
SLG .667
HR 2
AB 18
H 6
RBI 3
Henry Davis headshot
New York Mets
1.145 OPS
AVG .500
OBP .545
SLG .600
HR 0
AB 10
H 5
RBI 1
Andrew Vaughn headshot
Los Angeles Dodgers
1.145 OPS
AVG .400
OBP .545
SLG .600
HR 1
AB 15
H 6
RBI 7
Jeremy Pena headshot
Tampa Bay Rays
1.144 OPS
AVG .400
OBP .464
SLG .680
HR 2
AB 25
H 10
RBI 3
Joey Wiemer headshot
Washington Nationals
1.144 OPS
AVG .308
OBP .375
SLG .769
HR 2
AB 13
H 4
RBI 4
Daylen Lile headshot
Minnesota Twins
1.144 OPS
AVG .455
OBP .417
SLG .727
HR 0
AB 11
H 5
RBI 1
Austin Hays headshot
Cleveland Indians
1.144 OPS
AVG .364
OBP .417
SLG .727
HR 1
AB 11
H 4
RBI 2
Aaron Judge headshot
Minnesota Twins
1.144 OPS
AVG .353
OBP .556
SLG .588
HR 1
AB 17
H 6
RBI 3
Danny Jansen headshot
New York Mets
1.144 OPS
AVG .364
OBP .417
SLG .727
HR 1
AB 11
H 4
RBI 3
Rafael Devers headshot
Colorado Rockies
1.143 OPS
AVG .292
OBP .393
SLG .750
HR 3
AB 24
H 7
RBI 6
Jazz Chisholm headshot
Cleveland Indians
1.143 OPS
AVG .368
OBP .458
SLG .684
HR 2
AB 19
H 7
RBI 5
Julio Rodriguez headshot
Arizona Diamondbacks
1.143 OPS
AVG .500
OBP .500
SLG .643
HR 0
AB 14
H 7
RBI 1
Will Benson headshot
San Diego Padres
1.143 OPS
AVG .429
OBP .429
SLG .714
HR 1
AB 14
H 6
RBI 2
Cal Raleigh headshot
Los Angeles Angels
1.142 OPS
AVG .326
OBP .446
SLG .696
HR 5
AB 46
H 15
RBI 9
Jazz Chisholm headshot
Oakland Athletics
1.141 OPS
AVG .250
OBP .308
SLG .833
HR 2
AB 12
H 3
RBI 4
Ramon Laureano headshot
Seattle Mariners
1.141 OPS
AVG .250
OBP .308
SLG .833
HR 2
AB 12
H 3
RBI 5
Nathaniel Lowe headshot
Philadelphia Phillies
1.140 OPS
AVG .346
OBP .370
SLG .769
HR 3
AB 26
H 9
RBI 10
Harrison Bader headshot
Baltimore Orioles
1.139 OPS
AVG .313
OBP .389
SLG .750
HR 2
AB 16
H 5
RBI 6
JP Crawford headshot
Cleveland Indians
1.139 OPS
AVG .429
OBP .520
SLG .619
HR 1
AB 21
H 9
RBI 5
Ryan McMahon headshot
Detroit Tigers
1.138 OPS
AVG .313
OBP .450
SLG .688
HR 1
AB 16
H 5
RBI 2
Nick Gonzales headshot
Chicago White Sox
1.138 OPS
AVG .400
OBP .538
SLG .600
HR 0
AB 10
H 4
RBI 2
Jazz Chisholm headshot
Los Angeles Angels
1.137 OPS
AVG .400
OBP .471
SLG .667
HR 1
AB 15
H 6
RBI 1
Maikel Garcia headshot
Detroit Tigers
1.137 OPS
AVG .357
OBP .471
SLG .667
HR 3
AB 42
H 15
RBI 5
Spencer Steer headshot
New York Yankees
1.136 OPS
AVG .545
OBP .500
SLG .636
HR 0
AB 11
H 6
RBI 2
Fernando Tatis headshot
Tampa Bay Rays
1.136 OPS
AVG .455
OBP .500
SLG .636
HR 0
AB 11
H 5
RBI 1
Matt McLain headshot
Toronto Blue Jays
1.136 OPS
AVG .455
OBP .500
SLG .636
HR 0
AB 11
H 5
RBI 3
Isaac Paredes headshot
Cincinnati Reds
1.136 OPS
AVG .364
OBP .500
SLG .636
HR 0
AB 11
H 4
RBI 2
Jackson Merrill headshot
Chicago White Sox
1.135 OPS
AVG .333
OBP .385
SLG .750
HR 1
AB 12
H 4
RBI 1
Andrew McCutchen headshot
San Diego Padres
1.135 OPS
AVG .350
OBP .435
SLG .700
HR 2
AB 20
H 7
RBI 3
JP Crawford headshot
Boston Red Sox
1.134 OPS
AVG .412
OBP .545
SLG .588
HR 1
AB 17
H 7
RBI 6
Alejandro Kirk headshot
Seattle Mariners
1.134 OPS
AVG .500
OBP .563
SLG .571
HR 0
AB 14
H 7
RBI 2
Xander Bogaerts headshot
Philadelphia Phillies
1.133 OPS
AVG .500
OBP .583
SLG .550
HR 0
AB 20
H 10
RBI 0
Austin Wells headshot
Milwaukee Brewers
1.133 OPS
AVG .200
OBP .333
SLG .800
HR 2
AB 10
H 2
RBI 3
Mike Trout headshot
Toronto Blue Jays
1.133 OPS
AVG .300
OBP .533
SLG .600
HR 1
AB 10
H 3
RBI 1
Henry Davis headshot
Arizona Diamondbacks
1.133 OPS
AVG .333
OBP .467
SLG .667
HR 1
AB 12
H 4
RBI 3
Tyler Stephenson headshot
Detroit Tigers
1.133 OPS
AVG .400
OBP .400
SLG .733
HR 1
AB 15
H 6
RBI 7
Jonathan Aranda headshot
Minnesota Twins
1.132 OPS
AVG .435
OBP .480
SLG .652
HR 1
AB 23
H 10
RBI 7
Andrew McCutchen headshot
Colorado Rockies
1.131 OPS
AVG .333
OBP .417
SLG .714
HR 2
AB 21
H 7
RBI 11
Yainer Diaz headshot
Toronto Blue Jays
1.130 OPS
AVG .391
OBP .391
SLG .739
HR 1
AB 23
H 9
RBI 4

Understanding Opponent Splits

Opponent splits reveal how a hitter performs against each MLB team. These splits capture the combined effect of a team's pitching staff, defensive alignment, and park factors. Some hitters consistently dominate certain teams due to favorable pitching matchups.

Team-Specific Matchups

Some hitters own certain teams. This often reflects favorable matchups against that team's pitching staff — handedness advantages, pitch-type weaknesses, or familiarity from division play. Division rivals face each other 13+ times per season, creating larger sample sizes.

Stacking by Opponent

For DFS, opponent splits help identify entire lineups to stack. If multiple hitters on a team have strong splits against today's opponent, that's a high-correlation stack. Combine with the opposing starter's recent form for maximum edge.

Sample Size Caution

Opponent splits against non-division teams can be small (3-4 games per season). Weight division matchups more heavily since they have 13+ games of data. A .400 AVG in 10 at-bats against a team is interesting but not predictive on its own.

Data Source & Methodology

Batting splits sourced from MLB Stats API. Stats reflect current season data and update daily as games are played.

Frequently Asked Questions

How reliable are opponent batting splits?
Division opponent splits are the most reliable since hitters face those teams 13+ times per season. Interleague and non-division splits have smaller sample sizes (3-7 games) and should be weighted less heavily. Always check the at-bat count before drawing conclusions.
How do I use opponent splits for DFS stacks?
Find teams where multiple hitters have strong splits against today's opponent. Stack 3-4 hitters from that team in your DFS lineup for high correlation. This works especially well when the opposing starter is also weak against that lineup's handedness profile.
Why do some hitters crush certain teams?
It usually comes down to pitching staff matchups. A hitter might face favorable pitch types, have platoon advantages against most of a team's rotation, or thrive at that team's home park. Division familiarity also plays a role — hitters see the same pitchers repeatedly.
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