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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.
Hunter Goodman headshot
St. Louis Cardinals
.583 OPS
AVG .190
OBP .250
SLG .333
HR 1
AB 21
H 4
RBI 6
Jorge Soler headshot
Seattle Mariners
.583 OPS
AVG .250
OBP .333
SLG .250
HR 0
AB 20
H 5
RBI 3
Taylor Ward headshot
Toronto Blue Jays
.583 OPS
AVG .171
OBP .326
SLG .257
HR 1
AB 35
H 6
RBI 5
Matt Vierling headshot
Texas Rangers
.583 OPS
AVG .167
OBP .167
SLG .417
HR 0
AB 12
H 2
RBI 2
Carlos Correa headshot
Los Angeles Angels
.583 OPS
AVG .250
OBP .333
SLG .250
HR 0
AB 16
H 4
RBI 2
Rafael Devers headshot
New York Yankees
.583 OPS
AVG .250
OBP .250
SLG .333
HR 0
AB 12
H 3
RBI 0
Yohendrick Pinango headshot
Miami Marlins
.583 OPS
AVG .167
OBP .167
SLG .417
HR 1
AB 12
H 2
RBI 2
Andy Pages headshot
Toronto Blue Jays
.583 OPS
AVG .250
OBP .250
SLG .333
HR 0
AB 12
H 3
RBI 2
Sal Stewart headshot
Houston Astros
.583 OPS
AVG .250
OBP .250
SLG .333
HR 0
AB 12
H 3
RBI 0
Moises Ballesteros headshot
Washington Nationals
.583 OPS
AVG .133
OBP .250
SLG .333
HR 1
AB 15
H 2
RBI 3
Rafael Devers headshot
Miami Marlins
.583 OPS
AVG .143
OBP .250
SLG .333
HR 1
AB 21
H 3
RBI 2
Matt McLain headshot
Arizona Diamondbacks
.583 OPS
AVG .143
OBP .250
SLG .333
HR 1
AB 21
H 3
RBI 2
Spencer Steer headshot
Houston Astros
.583 OPS
AVG .167
OBP .167
SLG .417
HR 1
AB 12
H 2
RBI 1
Kazuma Okamoto headshot
Los Angeles Dodgers
.583 OPS
AVG .250
OBP .250
SLG .333
HR 0
AB 12
H 3
RBI 0
Angel Martinez headshot
Washington Nationals
.583 OPS
AVG .250
OBP .250
SLG .333
HR 0
AB 12
H 3
RBI 2
Freddie Freeman headshot
Cleveland Indians
.583 OPS
AVG .167
OBP .167
SLG .417
HR 1
AB 12
H 2
RBI 2
Tim Tawa headshot
Atlanta Braves
.583 OPS
AVG .167
OBP .250
SLG .333
HR 1
AB 18
H 3
RBI 3
CJ Abrams headshot
New York Yankees
.583 OPS
AVG .250
OBP .250
SLG .333
HR 0
AB 12
H 3
RBI 0
Jorge Mateo headshot
Baltimore Orioles
.583 OPS
AVG .167
OBP .167
SLG .417
HR 1
AB 12
H 2
RBI 3
Kyle Isbel headshot
Oakland Athletics
.583 OPS
AVG .250
OBP .333
SLG .250
HR 0
AB 16
H 4
RBI 2
Xander Bogaerts headshot
Milwaukee Brewers
.583 OPS
AVG .167
OBP .250
SLG .333
HR 1
AB 18
H 3
RBI 1
Christian Koss headshot
Colorado Rockies
.583 OPS
AVG .250
OBP .250
SLG .333
HR 0
AB 12
H 3
RBI 0
AJ Ewing headshot
Boston Red Sox
.583 OPS
AVG .250
OBP .250
SLG .333
HR 0
AB 12
H 3
RBI 0
Rhys Hoskins headshot
Atlanta Braves
.583 OPS
AVG .167
OBP .167
SLG .417
HR 1
AB 12
H 2
RBI 3
Salvador Perez headshot
Atlanta Braves
.583 OPS
AVG .167
OBP .167
SLG .417
HR 1
AB 12
H 2
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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