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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.
Trevor Story headshot
Milwaukee Brewers
.594 OPS
AVG .273
OBP .231
SLG .364
HR 0
AB 11
H 3
RBI 6
Trent Grisham headshot
Los Angeles Dodgers
.594 OPS
AVG .091
OBP .231
SLG .364
HR 1
AB 11
H 1
RBI 1
Munetaka Murakami headshot
San Diego Padres
.594 OPS
AVG .091
OBP .231
SLG .364
HR 1
AB 11
H 1
RBI 3
Salvador Perez headshot
Minnesota Twins
.594 OPS
AVG .238
OBP .261
SLG .333
HR 0
AB 42
H 10
RBI 4
James Wood headshot
Cincinnati Reds
.594 OPS
AVG .091
OBP .231
SLG .364
HR 1
AB 11
H 1
RBI 1
Jac Caglianone headshot
Seattle Mariners
.594 OPS
AVG .190
OBP .261
SLG .333
HR 1
AB 21
H 4
RBI 4
Ezequiel Tovar headshot
Philadelphia Phillies
.594 OPS
AVG .278
OBP .316
SLG .278
HR 0
AB 18
H 5
RBI 1
Royce Lewis headshot
New York Yankees
.594 OPS
AVG .238
OBP .261
SLG .333
HR 0
AB 21
H 5
RBI 3
Hao-Yu Lee headshot
Baltimore Orioles
.594 OPS
AVG .273
OBP .231
SLG .364
HR 0
AB 11
H 3
RBI 5
Jeremy Pena headshot
Colorado Rockies
.593 OPS
AVG .231
OBP .286
SLG .308
HR 0
AB 13
H 3
RBI 0
Wade Meckler headshot
Miami Marlins
.593 OPS
AVG .231
OBP .286
SLG .308
HR 0
AB 13
H 3
RBI 0
Luis Arraez headshot
Los Angeles Dodgers
.593 OPS
AVG .259
OBP .333
SLG .259
HR 0
AB 27
H 7
RBI 0
Drake Baldwin headshot
Cleveland Indians
.593 OPS
AVG .231
OBP .286
SLG .308
HR 0
AB 13
H 3
RBI 2
Mookie Betts headshot
Detroit Tigers
.593 OPS
AVG .231
OBP .286
SLG .308
HR 0
AB 13
H 3
RBI 0
Isaac Paredes headshot
Washington Nationals
.593 OPS
AVG .231
OBP .286
SLG .308
HR 0
AB 13
H 3
RBI 0
Nathaniel Lowe headshot
Milwaukee Brewers
.593 OPS
AVG .231
OBP .286
SLG .308
HR 0
AB 13
H 3
RBI 0
Nathan Church headshot
San Francisco Giants
.593 OPS
AVG .227
OBP .320
SLG .273
HR 0
AB 22
H 5
RBI 1
Wilyer Abreu headshot
Kansas City Royals
.593 OPS
AVG .259
OBP .259
SLG .333
HR 0
AB 27
H 7
RBI 3
Kyle Stowers headshot
Houston Astros
.593 OPS
AVG .231
OBP .286
SLG .308
HR 0
AB 13
H 3
RBI 1
Salvador Perez headshot
New York Mets
.593 OPS
AVG .231
OBP .286
SLG .308
HR 0
AB 13
H 3
RBI 3
Brett Callahan headshot
Minnesota Twins
.593 OPS
AVG .231
OBP .286
SLG .308
HR 0
AB 13
H 3
RBI 1
Jasson Dominguez headshot
Chicago White Sox
.593 OPS
AVG .231
OBP .286
SLG .308
HR 0
AB 26
H 6
RBI 0
Kyle Karros headshot
San Diego Padres
.593 OPS
AVG .189
OBP .268
SLG .324
HR 1
AB 37
H 7
RBI 3
Andres Gimenez headshot
Seattle Mariners
.593 OPS
AVG .231
OBP .286
SLG .308
HR 0
AB 13
H 3
RBI 4
Christian Moore headshot
Seattle Mariners
.593 OPS
AVG .167
OBP .259
SLG .333
HR 1
AB 24
H 4
RBI 6

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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