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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.
Ben Rice headshot
Minnesota Twins
.857 OPS
AVG .273
OBP .448
SLG .409
HR 1
AB 22
H 6
RBI 4
Victor Caratini headshot
Kansas City Royals
.857 OPS
AVG .290
OBP .405
SLG .452
HR 1
AB 31
H 9
RBI 4
Wyatt Langford headshot
Miami Marlins
.857 OPS
AVG .250
OBP .357
SLG .500
HR 1
AB 12
H 3
RBI 1
Bryan Reynolds headshot
Cincinnati Reds
.857 OPS
AVG .255
OBP .367
SLG .490
HR 3
AB 51
H 13
RBI 8
Dane Myers headshot
San Diego Padres
.857 OPS
AVG .429
OBP .429
SLG .429
HR 0
AB 14
H 6
RBI 0
Wilyer Abreu headshot
Los Angeles Dodgers
.857 OPS
AVG .250
OBP .357
SLG .500
HR 1
AB 12
H 3
RBI 1
Jordan Walker headshot
Cleveland Indians
.857 OPS
AVG .286
OBP .286
SLG .571
HR 1
AB 14
H 4
RBI 1
Brandon Nimmo headshot
San Diego Padres
.857 OPS
AVG .357
OBP .357
SLG .500
HR 0
AB 14
H 5
RBI 1
Sal Stewart headshot
Detroit Tigers
.857 OPS
AVG .250
OBP .357
SLG .500
HR 1
AB 12
H 3
RBI 5
Yordan Alvarez headshot
Arizona Diamondbacks
.857 OPS
AVG .250
OBP .357
SLG .500
HR 1
AB 12
H 3
RBI 1
Miguel Andujar headshot
Kansas City Royals
.857 OPS
AVG .250
OBP .357
SLG .500
HR 0
AB 12
H 3
RBI 1
Drake Baldwin headshot
Minnesota Twins
.857 OPS
AVG .286
OBP .286
SLG .571
HR 1
AB 14
H 4
RBI 1
Austin Wells headshot
Texas Rangers
.857 OPS
AVG .250
OBP .357
SLG .500
HR 1
AB 12
H 3
RBI 1
Will Benson headshot
Pittsburgh Pirates
.857 OPS
AVG .214
OBP .214
SLG .643
HR 1
AB 14
H 3
RBI 2
Jose Ramirez headshot
Atlanta Braves
.857 OPS
AVG .250
OBP .357
SLG .500
HR 1
AB 12
H 3
RBI 1
Jackson Chourio headshot
Baltimore Orioles
.857 OPS
AVG .250
OBP .357
SLG .500
HR 1
AB 12
H 3
RBI 3
Hector Rodriguez headshot
San Diego Padres
.857 OPS
AVG .286
OBP .286
SLG .571
HR 1
AB 14
H 4
RBI 2
Cal Raleigh headshot
St. Louis Cardinals
.857 OPS
AVG .250
OBP .357
SLG .500
HR 1
AB 12
H 3
RBI 1
Vaughn Grissom headshot
San Francisco Giants
.857 OPS
AVG .250
OBP .357
SLG .500
HR 1
AB 12
H 3
RBI 3
Victor Mesa headshot
Los Angeles Angels
.857 OPS
AVG .250
OBP .357
SLG .500
HR 1
AB 12
H 3
RBI 3
Kevin McGonigle headshot
Pittsburgh Pirates
.856 OPS
AVG .280
OBP .296
SLG .560
HR 2
AB 25
H 7
RBI 6
Dustin Harris headshot
Baltimore Orioles
.856 OPS
AVG .333
OBP .389
SLG .467
HR 0
AB 15
H 5
RBI 5
Austin Riley headshot
Philadelphia Phillies
.856 OPS
AVG .229
OBP .315
SLG .542
HR 4
AB 48
H 11
RBI 11
Tyler Stephenson headshot
Miami Marlins
.856 OPS
AVG .222
OBP .300
SLG .556
HR 2
AB 18
H 4
RBI 2
Jose Caballero headshot
Boston Red Sox
.856 OPS
AVG .318
OBP .333
SLG .523
HR 2
AB 44
H 14
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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