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MLB Batting Splits 2026

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.
Trea Turner headshot
Texas Rangers
.368 OPS
AVG .154
OBP .214
SLG .154
HR 0
AB 13
H 2
RBI 0
Sal Stewart headshot
Minnesota Twins
.368 OPS
AVG .154
OBP .214
SLG .154
HR 0
AB 13
H 2
RBI 1
Marcelo Mayer headshot
Houston Astros
.368 OPS
AVG .118
OBP .250
SLG .118
HR 0
AB 17
H 2
RBI 0
Kyle Tucker headshot
Texas Rangers
.368 OPS
AVG .154
OBP .214
SLG .154
HR 0
AB 13
H 2
RBI 1
Christian Vazquez headshot
Detroit Tigers
.368 OPS
AVG .154
OBP .214
SLG .154
HR 0
AB 13
H 2
RBI 0
Ivan Herrera headshot
Texas Rangers
.368 OPS
AVG .154
OBP .214
SLG .154
HR 0
AB 13
H 2
RBI 0
David Hamilton headshot
Washington Nationals
.368 OPS
AVG .154
OBP .214
SLG .154
HR 0
AB 13
H 2
RBI 0
Jackson Chourio headshot
New York Yankees
.368 OPS
AVG .154
OBP .214
SLG .154
HR 0
AB 13
H 2
RBI 2
Daniel Schneemann headshot
Houston Astros
.368 OPS
AVG .118
OBP .250
SLG .118
HR 0
AB 17
H 2
RBI 0
James Wood headshot
Philadelphia Phillies
.368 OPS
AVG .119
OBP .178
SLG .190
HR 0
AB 42
H 5
RBI 2
Elias Diaz headshot
Seattle Mariners
.368 OPS
AVG .154
OBP .214
SLG .154
HR 0
AB 13
H 2
RBI 0
Ryan O'Hearn headshot
Arizona Diamondbacks
.368 OPS
AVG .125
OBP .160
SLG .208
HR 0
AB 24
H 3
RBI 2
Vladimir Guerrero Jr. headshot
Houston Astros
.367 OPS
AVG .150
OBP .217
SLG .150
HR 0
AB 20
H 3
RBI 1
George Lombard headshot
San Diego Padres
.367 OPS
AVG .100
OBP .167
SLG .200
HR 0
AB 10
H 1
RBI 1
Luis Rengifo headshot
Colorado Rockies
.367 OPS
AVG .083
OBP .200
SLG .167
HR 0
AB 12
H 1
RBI 4
Richie Palacios headshot
Detroit Tigers
.367 OPS
AVG .111
OBP .200
SLG .167
HR 0
AB 18
H 2
RBI 0
Mike Yastrzemski headshot
Arizona Diamondbacks
.367 OPS
AVG .100
OBP .217
SLG .150
HR 0
AB 20
H 2
RBI 2
Francisco Alvarez headshot
Minnesota Twins
.367 OPS
AVG .100
OBP .167
SLG .200
HR 0
AB 10
H 1
RBI 2
Jose Tena headshot
Miami Marlins
.367 OPS
AVG .091
OBP .231
SLG .136
HR 0
AB 22
H 2
RBI 0
Jim Jarvis headshot
New York Mets
.367 OPS
AVG .111
OBP .200
SLG .167
HR 0
AB 18
H 2
RBI 1
Josh Bell headshot
Boston Red Sox
.366 OPS
AVG .130
OBP .192
SLG .174
HR 0
AB 23
H 3
RBI 3
Gunnar Henderson headshot
New York Yankees
.365 OPS
AVG .150
OBP .190
SLG .175
HR 0
AB 40
H 6
RBI 1
Ryan Kreidler headshot
Los Angeles Dodgers
.364 OPS
AVG .182
OBP .182
SLG .182
HR 0
AB 11
H 2
RBI 2
Brayan Rocchio headshot
San Francisco Giants
.364 OPS
AVG .182
OBP .182
SLG .182
HR 0
AB 11
H 2
RBI 1
Brice Matthews headshot
Chicago Cubs
.364 OPS
AVG .182
OBP .182
SLG .182
HR 0
AB 11
H 2
RBI 1

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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