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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.
Daulton Varsho headshot
New York Yankees
.954 OPS
AVG .367
OBP .387
SLG .567
HR 1
AB 30
H 11
RBI 4
Munetaka Murakami headshot
New York Yankees
.954 OPS
AVG .267
OBP .421
SLG .533
HR 1
AB 15
H 4
RBI 1
Juan Soto headshot
New York Yankees
.954 OPS
AVG .292
OBP .370
SLG .583
HR 2
AB 24
H 7
RBI 2
Josh Bell headshot
Baltimore Orioles
.953 OPS
AVG .318
OBP .407
SLG .545
HR 1
AB 22
H 7
RBI 5
Nolan Schanuel headshot
Texas Rangers
.952 OPS
AVG .370
OBP .471
SLG .481
HR 0
AB 27
H 10
RBI 5
Alex Bregman headshot
Colorado Rockies
.952 OPS
AVG .294
OBP .481
SLG .471
HR 1
AB 17
H 5
RBI 4
Brayan Rocchio headshot
Baltimore Orioles
.952 OPS
AVG .381
OBP .381
SLG .571
HR 1
AB 21
H 8
RBI 8
Ty France headshot
Atlanta Braves
.952 OPS
AVG .269
OBP .259
SLG .692
HR 3
AB 26
H 7
RBI 6
Pete Crow-Armstrong headshot
Miami Marlins
.952 OPS
AVG .286
OBP .429
SLG .524
HR 1
AB 21
H 6
RBI 3
Junior Caminero headshot
Minnesota Twins
.950 OPS
AVG .269
OBP .296
SLG .654
HR 3
AB 26
H 7
RBI 5
Travis Bazzana headshot
Minnesota Twins
.950 OPS
AVG .283
OBP .450
SLG .500
HR 3
AB 46
H 13
RBI 8
Yainer Diaz headshot
Tampa Bay Rays
.950 OPS
AVG .353
OBP .421
SLG .529
HR 1
AB 17
H 6
RBI 4
Bryan Torres headshot
Cincinnati Reds
.949 OPS
AVG .323
OBP .432
SLG .516
HR 2
AB 31
H 10
RBI 7
Alex Bregman headshot
Chicago White Sox
.948 OPS
AVG .407
OBP .467
SLG .481
HR 0
AB 27
H 11
RBI 4
Ildemaro Vargas headshot
San Diego Padres
.948 OPS
AVG .280
OBP .308
SLG .640
HR 1
AB 25
H 7
RBI 8
Konnor Griffin headshot
Washington Nationals
.948 OPS
AVG .385
OBP .448
SLG .500
HR 0
AB 26
H 10
RBI 4
Jesus Sanchez headshot
Baltimore Orioles
.947 OPS
AVG .421
OBP .421
SLG .526
HR 0
AB 19
H 8
RBI 1
Kody Clemens headshot
Texas Rangers
.946 OPS
AVG .320
OBP .346
SLG .600
HR 2
AB 25
H 8
RBI 8
Jo Adell headshot
Texas Rangers
.946 OPS
AVG .286
OBP .375
SLG .571
HR 2
AB 21
H 6
RBI 6
Zack Gelof headshot
Los Angeles Angels
.946 OPS
AVG .306
OBP .419
SLG .528
HR 2
AB 36
H 11
RBI 7
Matt Chapman headshot
Milwaukee Brewers
.946 OPS
AVG .286
OBP .375
SLG .571
HR 1
AB 14
H 4
RBI 4
Kyle Tucker headshot
Chicago Cubs
.945 OPS
AVG .318
OBP .400
SLG .545
HR 1
AB 22
H 7
RBI 1
Javier Sanoja headshot
Chicago Cubs
.945 OPS
AVG .360
OBP .385
SLG .560
HR 1
AB 25
H 9
RBI 3
Dansby Swanson headshot
Washington Nationals
.945 OPS
AVG .200
OBP .478
SLG .467
HR 1
AB 15
H 3
RBI 4
Charles McAdoo headshot
Boston Red Sox
.945 OPS
AVG .273
OBP .400
SLG .545
HR 1
AB 11
H 3
RBI 2

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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