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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.
Josh Naylor headshot
Atlanta Braves
.962 OPS
AVG .417
OBP .462
SLG .500
HR 0
AB 12
H 5
RBI 0
Munetaka Murakami headshot
Minnesota Twins
.961 OPS
AVG .237
OBP .356
SLG .605
HR 4
AB 38
H 9
RBI 8
Cody Bellinger headshot
Los Angeles Angels
.961 OPS
AVG .440
OBP .481
SLG .480
HR 0
AB 25
H 11
RBI 1
Nick Gonzales headshot
Colorado Rockies
.961 OPS
AVG .278
OBP .350
SLG .611
HR 1
AB 18
H 5
RBI 4
Nathan Lukes headshot
Texas Rangers
.961 OPS
AVG .368
OBP .435
SLG .526
HR 1
AB 19
H 7
RBI 4
JJ Wetherholt headshot
Pittsburgh Pirates
.961 OPS
AVG .313
OBP .377
SLG .583
HR 3
AB 48
H 15
RBI 6
Austin Hedges headshot
Chicago White Sox
.961 OPS
AVG .316
OBP .435
SLG .526
HR 1
AB 19
H 6
RBI 3
Bryan Reynolds headshot
Chicago Cubs
.960 OPS
AVG .327
OBP .364
SLG .596
HR 3
AB 52
H 17
RBI 8
Steven Kwan headshot
Chicago White Sox
.960 OPS
AVG .357
OBP .460
SLG .500
HR 1
AB 42
H 15
RBI 2
JJ Wetherholt headshot
Chicago Cubs
.960 OPS
AVG .353
OBP .431
SLG .529
HR 2
AB 51
H 18
RBI 3
Luis Garcia headshot
Miami Marlins
.960 OPS
AVG .316
OBP .381
SLG .579
HR 0
AB 19
H 6
RBI 4
Dylan Crews headshot
San Diego Padres
.960 OPS
AVG .316
OBP .381
SLG .579
HR 1
AB 19
H 6
RBI 5
Tristan Peters headshot
Minnesota Twins
.959 OPS
AVG .381
OBP .435
SLG .524
HR 0
AB 42
H 16
RBI 3
Liam Hicks headshot
Oakland Athletics
.959 OPS
AVG .367
OBP .459
SLG .500
HR 1
AB 30
H 11
RBI 7
Michael Conforto headshot
Miami Marlins
.958 OPS
AVG .294
OBP .429
SLG .529
HR 1
AB 17
H 5
RBI 1
Lawrence Butler headshot
Tampa Bay Rays
.958 OPS
AVG .292
OBP .292
SLG .667
HR 3
AB 24
H 7
RBI 4
Randy Arozarena headshot
Cleveland Indians
.958 OPS
AVG .280
OBP .438
SLG .520
HR 1
AB 25
H 7
RBI 5
Colson Montgomery headshot
Oakland Athletics
.958 OPS
AVG .261
OBP .393
SLG .565
HR 2
AB 23
H 6
RBI 4
Jo Adell headshot
Kansas City Royals
.957 OPS
AVG .314
OBP .415
SLG .543
HR 2
AB 35
H 11
RBI 7
Yordan Alvarez headshot
Boston Red Sox
.957 OPS
AVG .280
OBP .357
SLG .600
HR 2
AB 25
H 7
RBI 4
Evan Carter headshot
Tampa Bay Rays
.957 OPS
AVG .294
OBP .368
SLG .588
HR 1
AB 17
H 5
RBI 3
Chase DeLauter headshot
Detroit Tigers
.957 OPS
AVG .359
OBP .419
SLG .538
HR 1
AB 39
H 14
RBI 3
Kyle Schwarber headshot
Atlanta Braves
.956 OPS
AVG .240
OBP .356
SLG .600
HR 5
AB 50
H 12
RBI 10
Nick Gonzales headshot
San Francisco Giants
.956 OPS
AVG .400
OBP .516
SLG .440
HR 0
AB 25
H 10
RBI 3
Luke Keaschall headshot
Detroit Tigers
.956 OPS
AVG .325
OBP .481
SLG .475
HR 1
AB 40
H 13
RBI 7

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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