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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.
Royce Lewis headshot
Colorado Rockies
.769 OPS
AVG .308
OBP .308
SLG .462
HR 0
AB 13
H 4
RBI 1
Rafael Devers headshot
Chicago White Sox
.769 OPS
AVG .231
OBP .231
SLG .538
HR 1
AB 13
H 3
RBI 5
Vladimir Guerrero Jr. headshot
Los Angeles Angels
.769 OPS
AVG .273
OBP .360
SLG .409
HR 1
AB 22
H 6
RBI 3
Daniel Schneemann headshot
Seattle Mariners
.769 OPS
AVG .308
OBP .308
SLG .462
HR 0
AB 13
H 4
RBI 1
Jake Cronenworth headshot
Atlanta Braves
.769 OPS
AVG .286
OBP .412
SLG .357
HR 0
AB 14
H 4
RBI 0
Justin Foscue headshot
Tampa Bay Rays
.769 OPS
AVG .308
OBP .308
SLG .462
HR 0
AB 13
H 4
RBI 4
Cole Carrigg headshot
Seattle Mariners
.769 OPS
AVG .385
OBP .385
SLG .385
HR 0
AB 13
H 5
RBI 3
Nico Hoerner headshot
Philadelphia Phillies
.769 OPS
AVG .273
OBP .314
SLG .455
HR 2
AB 33
H 9
RBI 9
Mauricio Dubon headshot
Houston Astros
.769 OPS
AVG .308
OBP .308
SLG .462
HR 0
AB 13
H 4
RBI 0
Jake McCarthy headshot
New York Yankees
.769 OPS
AVG .308
OBP .308
SLG .462
HR 0
AB 13
H 4
RBI 1
Graham Pauley headshot
St. Louis Cardinals
.769 OPS
AVG .308
OBP .308
SLG .462
HR 0
AB 13
H 4
RBI 2
Jeff McNeil headshot
Detroit Tigers
.769 OPS
AVG .385
OBP .385
SLG .385
HR 0
AB 13
H 5
RBI 1
Riley Greene headshot
Arizona Diamondbacks
.769 OPS
AVG .308
OBP .308
SLG .462
HR 0
AB 13
H 4
RBI 3
Kyle Stowers headshot
Texas Rangers
.769 OPS
AVG .231
OBP .231
SLG .538
HR 0
AB 13
H 3
RBI 1
Bobby Witt Jr. headshot
Pittsburgh Pirates
.769 OPS
AVG .385
OBP .385
SLG .385
HR 0
AB 13
H 5
RBI 0
Yainer Diaz headshot
Toronto Blue Jays
.768 OPS
AVG .304
OBP .333
SLG .435
HR 1
AB 23
H 7
RBI 2
Jakob Marsee headshot
Cincinnati Reds
.768 OPS
AVG .286
OBP .375
SLG .393
HR 1
AB 28
H 8
RBI 2
Esmerlyn Valdez headshot
Chicago Cubs
.768 OPS
AVG .190
OBP .292
SLG .476
HR 2
AB 21
H 4
RBI 5
Ryan McMahon headshot
Texas Rangers
.768 OPS
AVG .250
OBP .318
SLG .450
HR 1
AB 20
H 5
RBI 3
Cam Smith headshot
Colorado Rockies
.768 OPS
AVG .238
OBP .292
SLG .476
HR 1
AB 21
H 5
RBI 3
Jorge Soler headshot
Cincinnati Reds
.767 OPS
AVG .167
OBP .267
SLG .500
HR 1
AB 12
H 2
RBI 5
Maikel Garcia headshot
Cleveland Indians
.767 OPS
AVG .294
OBP .385
SLG .382
HR 0
AB 34
H 10
RBI 1
Sean Murphy headshot
Los Angeles Dodgers
.767 OPS
AVG .214
OBP .267
SLG .500
HR 1
AB 14
H 3
RBI 1
Willy Adames headshot
Chicago White Sox
.767 OPS
AVG .214
OBP .267
SLG .500
HR 1
AB 14
H 3
RBI 2
Bobby Witt Jr. headshot
Cincinnati Reds
.767 OPS
AVG .200
OBP .467
SLG .300
HR 0
AB 10
H 2
RBI 0

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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