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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.
Alejandro Osuna headshot
Minnesota Twins
.517 OPS
AVG .200
OBP .250
SLG .267
HR 0
AB 15
H 3
RBI 1
Henry Davis headshot
Chicago Cubs
.517 OPS
AVG .148
OBP .258
SLG .259
HR 1
AB 27
H 4
RBI 2
Denzel Clarke headshot
Texas Rangers
.517 OPS
AVG .200
OBP .250
SLG .267
HR 0
AB 15
H 3
RBI 1
Hunter Feduccia headshot
Toronto Blue Jays
.517 OPS
AVG .200
OBP .250
SLG .267
HR 0
AB 15
H 3
RBI 0
Alex Bregman headshot
Detroit Tigers
.516 OPS
AVG .231
OBP .286
SLG .231
HR 0
AB 13
H 3
RBI 1
Zach Cole headshot
Seattle Mariners
.516 OPS
AVG .231
OBP .286
SLG .231
HR 0
AB 13
H 3
RBI 1
Casey Schmitt headshot
Seattle Mariners
.516 OPS
AVG .231
OBP .286
SLG .231
HR 0
AB 13
H 3
RBI 0
Konnor Griffin headshot
Tampa Bay Rays
.516 OPS
AVG .231
OBP .286
SLG .231
HR 0
AB 13
H 3
RBI 2
Christian Koss headshot
Pittsburgh Pirates
.516 OPS
AVG .231
OBP .286
SLG .231
HR 0
AB 13
H 3
RBI 1
Nathan Church headshot
Cincinnati Reds
.516 OPS
AVG .231
OBP .286
SLG .231
HR 0
AB 13
H 3
RBI 3
Gary Sanchez headshot
Cincinnati Reds
.516 OPS
AVG .133
OBP .316
SLG .200
HR 0
AB 15
H 2
RBI 0
Jake Cronenworth headshot
Chicago Cubs
.516 OPS
AVG .231
OBP .286
SLG .231
HR 0
AB 13
H 3
RBI 0
Tristan Peters headshot
Kansas City Royals
.516 OPS
AVG .176
OBP .222
SLG .294
HR 1
AB 34
H 6
RBI 9
Matt McLain headshot
New York Mets
.516 OPS
AVG .133
OBP .316
SLG .200
HR 0
AB 15
H 2
RBI 0
Nick Kurtz headshot
Cleveland Indians
.516 OPS
AVG .231
OBP .286
SLG .231
HR 0
AB 13
H 3
RBI 1
Luis Garcia headshot
Tampa Bay Rays
.516 OPS
AVG .158
OBP .200
SLG .316
HR 1
AB 19
H 3
RBI 1
Andruw Monasterio headshot
New York Yankees
.516 OPS
AVG .158
OBP .200
SLG .316
HR 1
AB 19
H 3
RBI 3
Geraldo Perdomo headshot
Milwaukee Brewers
.515 OPS
AVG .158
OBP .304
SLG .211
HR 0
AB 19
H 3
RBI 0
Colton Cowser headshot
New York Yankees
.515 OPS
AVG .158
OBP .304
SLG .211
HR 0
AB 19
H 3
RBI 1
Bo Bichette headshot
Philadelphia Phillies
.515 OPS
AVG .192
OBP .246
SLG .269
HR 1
AB 52
H 10
RBI 3
Jung Hoo Lee headshot
San Diego Padres
.515 OPS
AVG .180
OBP .255
SLG .260
HR 0
AB 50
H 9
RBI 4
Austin Wells headshot
Toronto Blue Jays
.515 OPS
AVG .158
OBP .304
SLG .211
HR 0
AB 19
H 3
RBI 2
Elias Diaz headshot
Oakland Athletics
.515 OPS
AVG .143
OBP .182
SLG .333
HR 1
AB 21
H 3
RBI 2
Cal Raleigh headshot
Tampa Bay Rays
.514 OPS
AVG .167
OBP .348
SLG .167
HR 0
AB 18
H 3
RBI 0
Wyatt Langford headshot
Los Angeles Angels
.514 OPS
AVG .172
OBP .273
SLG .241
HR 0
AB 29
H 5
RBI 2

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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