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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.
Ildemaro Vargas headshot
Seattle Mariners
.333 OPS
AVG .167
OBP .167
SLG .167
HR 0
AB 12
H 2
RBI 2
Cole Carrigg headshot
Detroit Tigers
.333 OPS
AVG .167
OBP .167
SLG .167
HR 0
AB 12
H 2
RBI 0
Luis Robert headshot
Miami Marlins
.333 OPS
AVG .167
OBP .167
SLG .167
HR 0
AB 12
H 2
RBI 2
Kyle Isbel headshot
Boston Red Sox
.333 OPS
AVG .167
OBP .167
SLG .167
HR 0
AB 12
H 2
RBI 0
Javier Sanoja headshot
Cleveland Indians
.333 OPS
AVG .167
OBP .167
SLG .167
HR 0
AB 12
H 2
RBI 0
Brayan Rocchio headshot
Pittsburgh Pirates
.333 OPS
AVG .167
OBP .167
SLG .167
HR 0
AB 12
H 2
RBI 0
Felix Reyes headshot
Chicago Cubs
.333 OPS
AVG .167
OBP .167
SLG .167
HR 0
AB 12
H 2
RBI 0
Daniel Schneemann headshot
New York Yankees
.333 OPS
AVG .167
OBP .167
SLG .167
HR 0
AB 12
H 2
RBI 0
Munetaka Murakami headshot
Miami Marlins
.333 OPS
AVG .167
OBP .167
SLG .167
HR 0
AB 12
H 2
RBI 1
Andruw Monasterio headshot
Los Angeles Angels
.333 OPS
AVG .167
OBP .167
SLG .167
HR 0
AB 12
H 2
RBI 0
Anthony Volpe headshot
Arizona Diamondbacks
.333 OPS
AVG .167
OBP .167
SLG .167
HR 0
AB 12
H 2
RBI 0
Sam Antonacci headshot
Pittsburgh Pirates
.333 OPS
AVG .167
OBP .167
SLG .167
HR 0
AB 12
H 2
RBI 1
Connor Norby headshot
Milwaukee Brewers
.333 OPS
AVG .167
OBP .167
SLG .167
HR 0
AB 12
H 2
RBI 1
James Wood headshot
Detroit Tigers
.333 OPS
AVG .167
OBP .167
SLG .167
HR 0
AB 12
H 2
RBI 1
Spencer Jones headshot
Minnesota Twins
.333 OPS
AVG .067
OBP .067
SLG .267
HR 1
AB 15
H 1
RBI 3
Justin Crawford headshot
Chicago Cubs
.332 OPS
AVG .100
OBP .182
SLG .150
HR 0
AB 20
H 2
RBI 2
Willi Castro headshot
Pittsburgh Pirates
.332 OPS
AVG .100
OBP .182
SLG .150
HR 0
AB 20
H 2
RBI 1
Jorge Polanco headshot
Pittsburgh Pirates
.332 OPS
AVG .059
OBP .273
SLG .059
HR 0
AB 17
H 1
RBI 1
Freddie Freeman headshot
New York Yankees
.331 OPS
AVG .100
OBP .231
SLG .100
HR 0
AB 10
H 1
RBI 2
Daylen Lile headshot
Cleveland Indians
.331 OPS
AVG .100
OBP .231
SLG .100
HR 0
AB 10
H 1
RBI 1
Trea Turner headshot
Detroit Tigers
.331 OPS
AVG .100
OBP .231
SLG .100
HR 0
AB 10
H 1
RBI 1
Jared Triolo headshot
San Francisco Giants
.330 OPS
AVG .143
OBP .188
SLG .143
HR 0
AB 14
H 2
RBI 4
Jake Burger headshot
New York Yankees
.330 OPS
AVG .130
OBP .200
SLG .130
HR 0
AB 23
H 3
RBI 1
Joc Pederson headshot
Detroit Tigers
.330 OPS
AVG .143
OBP .188
SLG .143
HR 0
AB 14
H 2
RBI 1
Jackson Merrill headshot
Chicago Cubs
.330 OPS
AVG .130
OBP .200
SLG .130
HR 0
AB 23
H 3
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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