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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.
Adolis Garcia headshot
Atlanta Braves
.580 OPS
AVG .182
OBP .308
SLG .273
HR 0
AB 22
H 4
RBI 1
Riley Greene headshot
Pittsburgh Pirates
.580 OPS
AVG .182
OBP .308
SLG .273
HR 0
AB 11
H 2
RBI 0
Brayan Rocchio headshot
Milwaukee Brewers
.580 OPS
AVG .182
OBP .308
SLG .273
HR 0
AB 11
H 2
RBI 0
Ty France headshot
Cleveland Indians
.580 OPS
AVG .182
OBP .308
SLG .273
HR 0
AB 11
H 2
RBI 0
Dansby Swanson headshot
Tampa Bay Rays
.580 OPS
AVG .182
OBP .308
SLG .273
HR 0
AB 11
H 2
RBI 0
Ian Happ headshot
San Diego Padres
.580 OPS
AVG .182
OBP .308
SLG .273
HR 0
AB 22
H 4
RBI 0
Brett Bateman headshot
Texas Rangers
.580 OPS
AVG .182
OBP .308
SLG .273
HR 0
AB 11
H 2
RBI 0
Brett Baty headshot
Miami Marlins
.580 OPS
AVG .194
OBP .257
SLG .323
HR 1
AB 31
H 6
RBI 5
Wade Meckler headshot
Los Angeles Dodgers
.580 OPS
AVG .182
OBP .308
SLG .273
HR 0
AB 11
H 2
RBI 0
Corbin Carroll headshot
Los Angeles Dodgers
.580 OPS
AVG .173
OBP .214
SLG .365
HR 2
AB 52
H 9
RBI 4
Jeremy Pena headshot
Minnesota Twins
.580 OPS
AVG .273
OBP .308
SLG .273
HR 0
AB 11
H 3
RBI 1
Rafael Devers headshot
Cleveland Indians
.580 OPS
AVG .182
OBP .308
SLG .273
HR 0
AB 11
H 2
RBI 0
Dylan Crews headshot
Baltimore Orioles
.580 OPS
AVG .182
OBP .308
SLG .273
HR 0
AB 11
H 2
RBI 0
Alec Burleson headshot
Detroit Tigers
.580 OPS
AVG .182
OBP .308
SLG .273
HR 0
AB 11
H 2
RBI 1
Christian Vazquez headshot
Texas Rangers
.579 OPS
AVG .200
OBP .259
SLG .320
HR 1
AB 25
H 5
RBI 2
Oswald Peraza headshot
Minnesota Twins
.579 OPS
AVG .267
OBP .313
SLG .267
HR 0
AB 15
H 4
RBI 1
Brenton Doyle headshot
Detroit Tigers
.579 OPS
AVG .263
OBP .263
SLG .316
HR 0
AB 19
H 5
RBI 0
Victor Robles headshot
Baltimore Orioles
.579 OPS
AVG .267
OBP .313
SLG .267
HR 0
AB 15
H 4
RBI 0
Cal Raleigh headshot
Minnesota Twins
.579 OPS
AVG .120
OBP .179
SLG .400
HR 2
AB 25
H 3
RBI 9
Amed Rosario headshot
Los Angeles Angels
.579 OPS
AVG .263
OBP .263
SLG .316
HR 0
AB 19
H 5
RBI 1
Jeff McNeil headshot
Houston Astros
.579 OPS
AVG .209
OBP .277
SLG .302
HR 1
AB 43
H 9
RBI 4
Bryce Teodosio headshot
Seattle Mariners
.579 OPS
AVG .267
OBP .313
SLG .267
HR 0
AB 15
H 4
RBI 4
J.P. Crawford headshot
Los Angeles Angels
.579 OPS
AVG .167
OBP .245
SLG .333
HR 2
AB 48
H 8
RBI 3
Jakob Marsee headshot
San Francisco Giants
.579 OPS
AVG .227
OBP .261
SLG .318
HR 0
AB 22
H 5
RBI 2
Vaughn Grissom headshot
Boston Red Sox
.578 OPS
AVG .222
OBP .300
SLG .278
HR 0
AB 18
H 4
RBI 1

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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