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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.
Pedro Pages headshot
Los Angeles Dodgers
.500 OPS
AVG .200
OBP .200
SLG .300
HR 0
AB 10
H 2
RBI 0
George Lombard headshot
Seattle Mariners
.500 OPS
AVG .250
OBP .250
SLG .250
HR 0
AB 12
H 3
RBI 0
Jonny DeLuca headshot
Miami Marlins
.500 OPS
AVG .200
OBP .200
SLG .300
HR 0
AB 10
H 2
RBI 0
Jonny DeLuca headshot
Minnesota Twins
.500 OPS
AVG .200
OBP .200
SLG .300
HR 0
AB 10
H 2
RBI 0
Tommy White headshot
Detroit Tigers
.500 OPS
AVG .250
OBP .250
SLG .250
HR 0
AB 12
H 3
RBI 0
Derek Hill headshot
New York Mets
.500 OPS
AVG .182
OBP .182
SLG .318
HR 1
AB 22
H 4
RBI 2
Dansby Swanson headshot
Texas Rangers
.500 OPS
AVG .200
OBP .200
SLG .300
HR 0
AB 10
H 2
RBI 0
Lane Thomas headshot
San Francisco Giants
.500 OPS
AVG .250
OBP .250
SLG .250
HR 0
AB 12
H 3
RBI 2
Dansby Swanson headshot
Oakland Athletics
.500 OPS
AVG .200
OBP .200
SLG .300
HR 0
AB 10
H 2
RBI 1
Adolis Garcia headshot
Miami Marlins
.500 OPS
AVG .250
OBP .250
SLG .250
HR 0
AB 12
H 3
RBI 0
Evan Carter headshot
Cleveland Indians
.500 OPS
AVG .250
OBP .250
SLG .250
HR 0
AB 12
H 3
RBI 1
Paul Goldschmidt headshot
Cincinnati Reds
.500 OPS
AVG .100
OBP .100
SLG .400
HR 1
AB 10
H 1
RBI 1
Vaughn Grissom headshot
Baltimore Orioles
.500 OPS
AVG .222
OBP .222
SLG .278
HR 0
AB 18
H 4
RBI 3
Lars Nootbaar headshot
New York Yankees
.500 OPS
AVG .200
OBP .200
SLG .300
HR 0
AB 10
H 2
RBI 0
Randy Arozarena headshot
Arizona Diamondbacks
.500 OPS
AVG .214
OBP .214
SLG .286
HR 0
AB 14
H 3
RBI 1
Austin Hedges headshot
Los Angeles Angels
.500 OPS
AVG .100
OBP .100
SLG .400
HR 1
AB 10
H 1
RBI 2
Xavier Edwards headshot
Detroit Tigers
.500 OPS
AVG .167
OBP .167
SLG .333
HR 0
AB 12
H 2
RBI 0
Jorge Soler headshot
San Francisco Giants
.500 OPS
AVG .143
OBP .143
SLG .357
HR 1
AB 14
H 2
RBI 2
Drew Romo headshot
Kansas City Royals
.500 OPS
AVG .100
OBP .100
SLG .400
HR 1
AB 10
H 1
RBI 2
Drew Romo headshot
Houston Astros
.500 OPS
AVG .100
OBP .400
SLG .100
HR 0
AB 10
H 1
RBI 0
Chase DeLauter headshot
Washington Nationals
.500 OPS
AVG .250
OBP .250
SLG .250
HR 0
AB 12
H 3
RBI 1
Jeremiah Jackson headshot
Minnesota Twins
.500 OPS
AVG .250
OBP .250
SLG .250
HR 0
AB 12
H 3
RBI 1
Jonah Heim headshot
Cleveland Indians
.500 OPS
AVG .200
OBP .200
SLG .300
HR 0
AB 10
H 2
RBI 0
Shohei Ohtani headshot
Atlanta Braves
.500 OPS
AVG .192
OBP .192
SLG .308
HR 0
AB 26
H 5
RBI 1
Victor Scott II headshot
New York Mets
.500 OPS
AVG .200
OBP .200
SLG .300
HR 0
AB 10
H 2
RBI 0

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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