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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.
Jose Altuve headshot
Cleveland Indians
.462 OPS
AVG .154
OBP .154
SLG .308
HR 1
AB 26
H 4
RBI 4
Josh Lowe headshot
Texas Rangers
.462 OPS
AVG .200
OBP .222
SLG .240
HR 0
AB 25
H 5
RBI 4
Josh Lowe headshot
Toronto Blue Jays
.462 OPS
AVG .231
OBP .231
SLG .231
HR 0
AB 13
H 3
RBI 0
Jeremy Pena headshot
Atlanta Braves
.462 OPS
AVG .154
OBP .154
SLG .308
HR 0
AB 13
H 2
RBI 0
Josh Naylor headshot
Kansas City Royals
.461 OPS
AVG .211
OBP .250
SLG .211
HR 0
AB 19
H 4
RBI 3
Kyle Schwarber headshot
Los Angeles Dodgers
.461 OPS
AVG .130
OBP .200
SLG .261
HR 1
AB 23
H 3
RBI 1
J.T. Realmuto headshot
Cincinnati Reds
.461 OPS
AVG .063
OBP .211
SLG .250
HR 1
AB 16
H 1
RBI 1
Randy Arozarena headshot
Tampa Bay Rays
.461 OPS
AVG .130
OBP .200
SLG .261
HR 1
AB 23
H 3
RBI 3
Luis Robert headshot
Los Angeles Dodgers
.461 OPS
AVG .063
OBP .211
SLG .250
HR 1
AB 16
H 1
RBI 1
Nico Hoerner headshot
Arizona Diamondbacks
.461 OPS
AVG .176
OBP .167
SLG .294
HR 0
AB 17
H 3
RBI 1
Salvador Perez headshot
New York Yankees
.461 OPS
AVG .118
OBP .167
SLG .294
HR 1
AB 17
H 2
RBI 1
Kody Clemens headshot
Boston Red Sox
.461 OPS
AVG .211
OBP .250
SLG .211
HR 0
AB 19
H 4
RBI 1
Teoscar Hernandez headshot
Colorado Rockies
.460 OPS
AVG .167
OBP .222
SLG .238
HR 0
AB 42
H 7
RBI 2
Luke Keaschall headshot
Kansas City Royals
.459 OPS
AVG .190
OBP .244
SLG .214
HR 0
AB 42
H 8
RBI 2
Alec Bohm headshot
Chicago Cubs
.458 OPS
AVG .182
OBP .231
SLG .227
HR 0
AB 22
H 4
RBI 3
Jose Altuve headshot
Detroit Tigers
.458 OPS
AVG .167
OBP .167
SLG .292
HR 1
AB 24
H 4
RBI 1
Daylen Lile headshot
Los Angeles Dodgers
.458 OPS
AVG .167
OBP .167
SLG .292
HR 0
AB 24
H 4
RBI 1
Joey Ortiz headshot
Atlanta Braves
.458 OPS
AVG .176
OBP .222
SLG .235
HR 0
AB 17
H 3
RBI 0
Hunter Feduccia headshot
Cincinnati Reds
.458 OPS
AVG .125
OBP .333
SLG .125
HR 0
AB 16
H 2
RBI 1
Jonah Heim headshot
Seattle Mariners
.457 OPS
AVG .174
OBP .240
SLG .217
HR 0
AB 23
H 4
RBI 0
William Contreras headshot
San Diego Padres
.457 OPS
AVG .056
OBP .346
SLG .111
HR 0
AB 18
H 1
RBI 0
Dalton Rushing headshot
San Francisco Giants
.457 OPS
AVG .100
OBP .357
SLG .100
HR 0
AB 10
H 1
RBI 1
Nick Sogard headshot
Los Angeles Dodgers
.457 OPS
AVG .100
OBP .357
SLG .100
HR 0
AB 10
H 1
RBI 0
Jose Ramirez headshot
Toronto Blue Jays
.457 OPS
AVG .174
OBP .240
SLG .217
HR 0
AB 23
H 4
RBI 0
Isaac Paredes headshot
Toronto Blue Jays
.457 OPS
AVG .174
OBP .240
SLG .217
HR 0
AB 23
H 4
RBI 3

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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