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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.
Jac Caglianone headshot
Washington Nationals
.593 OPS
AVG .231
OBP .286
SLG .308
HR 0
AB 13
H 3
RBI 0
Nathan Lukes headshot
Tampa Bay Rays
.593 OPS
AVG .208
OBP .259
SLG .333
HR 1
AB 24
H 5
RBI 2
Francisco Lindor headshot
Texas Rangers
.593 OPS
AVG .231
OBP .286
SLG .308
HR 0
AB 13
H 3
RBI 0
Byron Buxton headshot
Colorado Rockies
.593 OPS
AVG .231
OBP .286
SLG .308
HR 0
AB 13
H 3
RBI 2
Brooks Lee headshot
New York Yankees
.593 OPS
AVG .227
OBP .320
SLG .273
HR 0
AB 22
H 5
RBI 1
Michael Massey headshot
Arizona Diamondbacks
.593 OPS
AVG .231
OBP .286
SLG .308
HR 0
AB 13
H 3
RBI 0
Jared Triolo headshot
Arizona Diamondbacks
.593 OPS
AVG .231
OBP .286
SLG .308
HR 0
AB 13
H 3
RBI 0
Yandy Diaz headshot
Detroit Tigers
.593 OPS
AVG .227
OBP .320
SLG .273
HR 0
AB 22
H 5
RBI 1
Jarren Duran headshot
St. Louis Cardinals
.593 OPS
AVG .231
OBP .286
SLG .308
HR 0
AB 13
H 3
RBI 4
Trevor Story headshot
New York Yankees
.593 OPS
AVG .231
OBP .286
SLG .308
HR 0
AB 13
H 3
RBI 0
Ben Williamson headshot
New York Yankees
.593 OPS
AVG .227
OBP .320
SLG .273
HR 0
AB 22
H 5
RBI 1
Ceddanne Rafaela headshot
New York Mets
.593 OPS
AVG .231
OBP .286
SLG .308
HR 0
AB 13
H 3
RBI 0
Ian Happ headshot
St. Louis Cardinals
.592 OPS
AVG .184
OBP .245
SLG .347
HR 1
AB 49
H 9
RBI 6
Yainer Diaz headshot
Baltimore Orioles
.591 OPS
AVG .273
OBP .273
SLG .318
HR 0
AB 22
H 6
RBI 2
Rafael Devers headshot
Oakland Athletics
.591 OPS
AVG .200
OBP .231
SLG .360
HR 1
AB 25
H 5
RBI 3
Royce Lewis headshot
Cleveland Indians
.591 OPS
AVG .178
OBP .302
SLG .289
HR 1
AB 45
H 8
RBI 5
Ryan Jeffers headshot
Cleveland Indians
.591 OPS
AVG .200
OBP .231
SLG .360
HR 1
AB 25
H 5
RBI 2
Kazuma Okamoto headshot
Boston Red Sox
.591 OPS
AVG .195
OBP .250
SLG .341
HR 1
AB 41
H 8
RBI 8
Chase DeLauter headshot
Cincinnati Reds
.590 OPS
AVG .174
OBP .286
SLG .304
HR 1
AB 23
H 4
RBI 3
Ryan Waldschmidt headshot
Cincinnati Reds
.590 OPS
AVG .188
OBP .278
SLG .313
HR 0
AB 16
H 3
RBI 2
Brandon Valenzuela headshot
New York Yankees
.590 OPS
AVG .238
OBP .304
SLG .286
HR 0
AB 21
H 5
RBI 0
Nathan Church headshot
Colorado Rockies
.590 OPS
AVG .286
OBP .304
SLG .286
HR 0
AB 21
H 6
RBI 3
Sal Frelick headshot
Cincinnati Reds
.590 OPS
AVG .212
OBP .257
SLG .333
HR 0
AB 33
H 7
RBI 1
Ivan Herrera headshot
Milwaukee Brewers
.590 OPS
AVG .170
OBP .250
SLG .340
HR 2
AB 47
H 8
RBI 6
Kaelen Culpepper headshot
Chicago White Sox
.590 OPS
AVG .238
OBP .304
SLG .286
HR 0
AB 21
H 5
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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