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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.
Jazz Chisholm Jr. headshot
Washington Nationals
.833 OPS
AVG .250
OBP .250
SLG .583
HR 1
AB 12
H 3
RBI 3
Shay Whitcomb headshot
Cincinnati Reds
.833 OPS
AVG .250
OBP .250
SLG .583
HR 1
AB 12
H 3
RBI 3
Riley Greene headshot
Chicago Cubs
.833 OPS
AVG .250
OBP .250
SLG .583
HR 1
AB 12
H 3
RBI 3
Dylan Crews headshot
Seattle Mariners
.833 OPS
AVG .250
OBP .250
SLG .583
HR 1
AB 12
H 3
RBI 3
Victor Mesa headshot
Baltimore Orioles
.833 OPS
AVG .286
OBP .333
SLG .500
HR 1
AB 14
H 4
RBI 3
Alika Williams headshot
Seattle Mariners
.833 OPS
AVG .273
OBP .333
SLG .500
HR 1
AB 22
H 6
RBI 1
Adley Rutschman headshot
Cleveland Indians
.833 OPS
AVG .333
OBP .333
SLG .500
HR 0
AB 12
H 4
RBI 0
Chandler Simpson headshot
New York Mets
.833 OPS
AVG .417
OBP .417
SLG .417
HR 0
AB 12
H 5
RBI 1
Jakob Marsee headshot
New York Mets
.832 OPS
AVG .326
OBP .354
SLG .478
HR 1
AB 46
H 15
RBI 7
Spencer Steer headshot
Philadelphia Phillies
.832 OPS
AVG .318
OBP .423
SLG .409
HR 0
AB 22
H 7
RBI 1
Jonathan Aranda headshot
Baltimore Orioles
.831 OPS
AVG .327
OBP .382
SLG .449
HR 1
AB 49
H 16
RBI 9
Zack Gelof headshot
Texas Rangers
.831 OPS
AVG .212
OBP .316
SLG .515
HR 3
AB 33
H 7
RBI 5
Cole Young headshot
Texas Rangers
.830 OPS
AVG .356
OBP .408
SLG .422
HR 0
AB 45
H 16
RBI 4
AJ Ewing headshot
Pittsburgh Pirates
.830 OPS
AVG .273
OBP .467
SLG .364
HR 0
AB 11
H 3
RBI 0
Oswald Peraza headshot
Oakland Athletics
.830 OPS
AVG .318
OBP .375
SLG .455
HR 0
AB 22
H 7
RBI 1
Sal Stewart headshot
Chicago Cubs
.830 OPS
AVG .269
OBP .310
SLG .519
HR 4
AB 52
H 14
RBI 8
Corey Seager headshot
Oakland Athletics
.830 OPS
AVG .263
OBP .383
SLG .447
HR 1
AB 38
H 10
RBI 5
James Wood headshot
Toronto Blue Jays
.830 OPS
AVG .273
OBP .467
SLG .364
HR 0
AB 11
H 3
RBI 0
Justin Foscue headshot
Los Angeles Angels
.830 OPS
AVG .265
OBP .359
SLG .471
HR 2
AB 34
H 9
RBI 5
Heliot Ramos headshot
Toronto Blue Jays
.830 OPS
AVG .258
OBP .281
SLG .548
HR 2
AB 31
H 8
RBI 5
Justin Foscue headshot
Boston Red Sox
.829 OPS
AVG .357
OBP .400
SLG .429
HR 0
AB 14
H 5
RBI 1
Nick Fortes headshot
Chicago White Sox
.829 OPS
AVG .357
OBP .400
SLG .429
HR 0
AB 14
H 5
RBI 2
Nick Kurtz headshot
Houston Astros
.829 OPS
AVG .200
OBP .429
SLG .400
HR 1
AB 20
H 4
RBI 2
Liam Hicks headshot
Washington Nationals
.829 OPS
AVG .200
OBP .429
SLG .400
HR 1
AB 15
H 3
RBI 2
J.T. Realmuto headshot
Atlanta Braves
.829 OPS
AVG .292
OBP .370
SLG .458
HR 1
AB 24
H 7
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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