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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.
Keibert Ruiz headshot
Chicago Cubs
.621 OPS
AVG .182
OBP .167
SLG .455
HR 1
AB 11
H 2
RBI 3
Denzer Guzman headshot
Texas Rangers
.621 OPS
AVG .276
OBP .276
SLG .345
HR 0
AB 29
H 8
RBI 3
Jac Caglianone headshot
Tampa Bay Rays
.621 OPS
AVG .207
OBP .207
SLG .414
HR 2
AB 29
H 6
RBI 3
Jonny DeLuca headshot
Boston Red Sox
.621 OPS
AVG .212
OBP .257
SLG .364
HR 1
AB 33
H 7
RBI 5
Andrew Benintendi headshot
Toronto Blue Jays
.620 OPS
AVG .231
OBP .313
SLG .308
HR 0
AB 13
H 3
RBI 1
Kyle Tucker headshot
Colorado Rockies
.620 OPS
AVG .260
OBP .260
SLG .360
HR 1
AB 50
H 13
RBI 5
Zach Neto headshot
Oakland Athletics
.620 OPS
AVG .154
OBP .254
SLG .365
HR 3
AB 52
H 8
RBI 7
Luis Lara headshot
New York Mets
.620 OPS
AVG .267
OBP .353
SLG .267
HR 0
AB 15
H 4
RBI 1
Willson Contreras headshot
Detroit Tigers
.620 OPS
AVG .148
OBP .250
SLG .370
HR 2
AB 27
H 4
RBI 3
Nico Hoerner headshot
Pittsburgh Pirates
.619 OPS
AVG .273
OBP .310
SLG .309
HR 0
AB 55
H 15
RBI 6
Jakob Marsee headshot
Philadelphia Phillies
.619 OPS
AVG .200
OBP .319
SLG .300
HR 1
AB 40
H 8
RBI 2
Nick Fortes headshot
Kansas City Royals
.619 OPS
AVG .286
OBP .333
SLG .286
HR 0
AB 14
H 4
RBI 3
Will Smith headshot
San Diego Padres
.619 OPS
AVG .167
OBP .286
SLG .333
HR 1
AB 18
H 3
RBI 1
Miles Mastrobuoni headshot
Baltimore Orioles
.619 OPS
AVG .286
OBP .333
SLG .286
HR 0
AB 14
H 4
RBI 0
Salvador Perez headshot
Los Angeles Angels
.619 OPS
AVG .238
OBP .238
SLG .381
HR 1
AB 21
H 5
RBI 3
Ozzie Albies headshot
Boston Red Sox
.619 OPS
AVG .200
OBP .259
SLG .360
HR 1
AB 25
H 5
RBI 2
Brandon Nimmo headshot
Detroit Tigers
.619 OPS
AVG .286
OBP .333
SLG .286
HR 0
AB 14
H 4
RBI 1
Alejandro Kirk headshot
Texas Rangers
.619 OPS
AVG .238
OBP .238
SLG .381
HR 1
AB 21
H 5
RBI 2
Alex Bregman headshot
Kansas City Royals
.619 OPS
AVG .286
OBP .333
SLG .286
HR 0
AB 14
H 4
RBI 3
Jake Burger headshot
Baltimore Orioles
.619 OPS
AVG .238
OBP .333
SLG .286
HR 0
AB 21
H 5
RBI 2
Andrew Vaughn headshot
Minnesota Twins
.619 OPS
AVG .286
OBP .333
SLG .286
HR 0
AB 14
H 4
RBI 1
Mike Trout headshot
Kansas City Royals
.619 OPS
AVG .167
OBP .286
SLG .333
HR 1
AB 24
H 4
RBI 3
Ben Malgeri headshot
Cleveland Indians
.619 OPS
AVG .238
OBP .333
SLG .286
HR 0
AB 21
H 5
RBI 3
Dylan Beavers headshot
Toronto Blue Jays
.619 OPS
AVG .200
OBP .259
SLG .360
HR 1
AB 25
H 5
RBI 3
Nick Loftin headshot
Los Angeles Angels
.619 OPS
AVG .227
OBP .346
SLG .273
HR 0
AB 22
H 5
RBI 4

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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