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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.
Wyatt Langford headshot
Philadelphia Phillies
.333 OPS
AVG .167
OBP .167
SLG .167
HR 0
AB 12
H 2
RBI 1
Josh Naylor headshot
Cleveland Indians
.333 OPS
AVG .167
OBP .167
SLG .167
HR 0
AB 12
H 2
RBI 0
Michael Massey headshot
Colorado Rockies
.336 OPS
AVG .182
OBP .154
SLG .182
HR 0
AB 11
H 2
RBI 3
Jackson Holliday headshot
Minnesota Twins
.339 OPS
AVG .154
OBP .185
SLG .154
HR 0
AB 26
H 4
RBI 0
Kebryan Hayes headshot
Chicago Cubs
.340 OPS
AVG .150
OBP .190
SLG .150
HR 0
AB 40
H 6
RBI 1
Luis Rengifo headshot
Seattle Mariners
.340 OPS
AVG .150
OBP .190
SLG .150
HR 0
AB 40
H 6
RBI 1
Cam Smith headshot
Detroit Tigers
.343 OPS
AVG .118
OBP .167
SLG .176
HR 0
AB 17
H 2
RBI 0
Willi Castro headshot
San Francisco Giants
.343 OPS
AVG .143
OBP .200
SLG .143
HR 0
AB 14
H 2
RBI 0
Jac Caglianone headshot
Oakland Athletics
.343 OPS
AVG .143
OBP .200
SLG .143
HR 0
AB 14
H 2
RBI 0
Everson Pereira headshot
Cleveland Indians
.343 OPS
AVG .143
OBP .200
SLG .143
HR 0
AB 14
H 2
RBI 1
Ramon Laureano headshot
Boston Red Sox
.347 OPS
AVG .125
OBP .222
SLG .125
HR 0
AB 16
H 2
RBI 3
Christian Vazquez headshot
Cleveland Indians
.347 OPS
AVG .125
OBP .222
SLG .125
HR 0
AB 16
H 2
RBI 1
Luke Raley headshot
Houston Astros
.347 OPS
AVG .125
OBP .222
SLG .125
HR 0
AB 16
H 2
RBI 2
Josh Lowe headshot
Texas Rangers
.348 OPS
AVG .091
OBP .167
SLG .182
HR 0
AB 11
H 1
RBI 0
Oswald Peraza headshot
Colorado Rockies
.348 OPS
AVG .091
OBP .167
SLG .182
HR 0
AB 11
H 1
RBI 1
Ryan Mountcastle headshot
Los Angeles Dodgers
.348 OPS
AVG .091
OBP .167
SLG .182
HR 0
AB 11
H 1
RBI 0
Dylan Crews headshot
Cleveland Indians
.348 OPS
AVG .091
OBP .167
SLG .182
HR 0
AB 11
H 1
RBI 1
Max Muncy headshot
Chicago White Sox
.348 OPS
AVG .091
OBP .167
SLG .182
HR 0
AB 11
H 1
RBI 0
Julio Rodriguez headshot
Pittsburgh Pirates
.348 OPS
AVG .091
OBP .167
SLG .182
HR 0
AB 11
H 1
RBI 0
Josh Jung headshot
Milwaukee Brewers
.348 OPS
AVG .091
OBP .167
SLG .182
HR 0
AB 11
H 1
RBI 0
Blake Perkins headshot
Philadelphia Phillies
.348 OPS
AVG .091
OBP .167
SLG .182
HR 0
AB 11
H 1
RBI 2
Jazz Chisholm headshot
Texas Rangers
.348 OPS
AVG .091
OBP .167
SLG .182
HR 0
AB 11
H 1
RBI 0
Anthony Volpe headshot
San Diego Padres
.348 OPS
AVG .182
OBP .167
SLG .182
HR 0
AB 11
H 2
RBI 2
Gunnar Henderson headshot
Los Angeles Dodgers
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 0
Gleyber Torres headshot
New York Mets
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 0
Gavin Lux headshot
Houston Astros
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 2
Jonathan Aranda headshot
Cincinnati Reds
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 1
Bryan Reynolds headshot
Houston Astros
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 0
Chase Meidroth headshot
Oakland Athletics
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 0
James Wood headshot
Boston Red Sox
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 0
JP Crawford headshot
New York Mets
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 0
Oswald Peraza headshot
Boston Red Sox
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 0
Jordan Beck headshot
Texas Rangers
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 0
Miguel Vargas headshot
San Francisco Giants
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 0
Willi Castro headshot
Chicago White Sox
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 0
Jung Hoo Lee headshot
Cleveland Indians
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 0
Matt Chapman headshot
Texas Rangers
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 0
Alejandro Osuna headshot
Los Angeles Angels
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 0
Brady House headshot
Philadelphia Phillies
.350 OPS
AVG .150
OBP .150
SLG .200
HR 0
AB 20
H 3
RBI 1
Henry Davis headshot
Los Angeles Dodgers
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 1
JP Crawford headshot
Washington Nationals
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 1
Gabriel Arias headshot
New York Yankees
.350 OPS
AVG .150
OBP .150
SLG .200
HR 0
AB 20
H 3
RBI 0
David Hamilton headshot
Toronto Blue Jays
.350 OPS
AVG .083
OBP .267
SLG .083
HR 0
AB 12
H 1
RBI 0
Anthony Volpe headshot
Los Angeles Dodgers
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 0
Christian Yelich headshot
New York Yankees
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 1
Xander Bogaerts headshot
Tampa Bay Rays
.350 OPS
AVG .100
OBP .250
SLG .100
HR 0
AB 10
H 1
RBI 0
Giancarlo Stanton headshot
Chicago White Sox
.351 OPS
AVG .095
OBP .208
SLG .143
HR 0
AB 21
H 2
RBI 3
Heliot Ramos headshot
Washington Nationals
.352 OPS
AVG .160
OBP .192
SLG .160
HR 0
AB 25
H 4
RBI 1
Ezequiel Tovar headshot
Miami Marlins
.353 OPS
AVG .176
OBP .176
SLG .176
HR 0
AB 17
H 3
RBI 0
Randy Arozarena headshot
San Francisco Giants
.354 OPS
AVG .077
OBP .200
SLG .154
HR 0
AB 13
H 1
RBI 2

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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