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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.
Brett Baty headshot
Pittsburgh Pirates
.480 OPS
AVG .200
OBP .200
SLG .280
HR 0
AB 25
H 5
RBI 3
Randal Grichuk headshot
Boston Red Sox
.480 OPS
AVG .200
OBP .200
SLG .280
HR 0
AB 25
H 5
RBI 1
Taylor Ward headshot
New York Yankees
.480 OPS
AVG .172
OBP .273
SLG .207
HR 0
AB 29
H 5
RBI 1
Dylan Crews headshot
New York Mets
.479 OPS
AVG .133
OBP .212
SLG .267
HR 1
AB 30
H 4
RBI 1
Jonathan Aranda headshot
Miami Marlins
.478 OPS
AVG .136
OBP .296
SLG .182
HR 0
AB 22
H 3
RBI 2
Jackson Chourio headshot
San Diego Padres
.478 OPS
AVG .208
OBP .269
SLG .208
HR 0
AB 24
H 5
RBI 1
Will Smith headshot
St. Louis Cardinals
.478 OPS
AVG .133
OBP .278
SLG .200
HR 0
AB 15
H 2
RBI 2
Kyle Tucker headshot
Atlanta Braves
.478 OPS
AVG .133
OBP .278
SLG .200
HR 0
AB 15
H 2
RBI 1
Ildemaro Vargas headshot
Colorado Rockies
.478 OPS
AVG .179
OBP .273
SLG .205
HR 0
AB 39
H 7
RBI 4
Kyle Schwarber headshot
Miami Marlins
.477 OPS
AVG .163
OBP .245
SLG .233
HR 1
AB 43
H 7
RBI 3
Ezequiel Tovar headshot
Houston Astros
.477 OPS
AVG .150
OBP .227
SLG .250
HR 0
AB 20
H 3
RBI 1
Heliot Ramos headshot
New York Mets
.476 OPS
AVG .238
OBP .238
SLG .238
HR 0
AB 21
H 5
RBI 0
Nolan Gorman headshot
San Francisco Giants
.476 OPS
AVG .176
OBP .300
SLG .176
HR 0
AB 17
H 3
RBI 2
Lars Nootbaar headshot
Colorado Rockies
.476 OPS
AVG .176
OBP .300
SLG .176
HR 0
AB 17
H 3
RBI 0
Angel Martinez headshot
Baltimore Orioles
.476 OPS
AVG .190
OBP .190
SLG .286
HR 0
AB 21
H 4
RBI 0
Brett Baty headshot
Chicago Cubs
.476 OPS
AVG .176
OBP .300
SLG .176
HR 0
AB 17
H 3
RBI 0
Liam Hicks headshot
San Diego Padres
.476 OPS
AVG .176
OBP .300
SLG .176
HR 0
AB 17
H 3
RBI 1
Denzer Guzman headshot
Houston Astros
.475 OPS
AVG .148
OBP .179
SLG .296
HR 1
AB 27
H 4
RBI 5
Alejandro Osuna headshot
Detroit Tigers
.474 OPS
AVG .211
OBP .211
SLG .263
HR 0
AB 19
H 4
RBI 2
Jose Trevino headshot
Chicago Cubs
.474 OPS
AVG .158
OBP .158
SLG .316
HR 1
AB 19
H 3
RBI 3
Javier Sanoja headshot
Washington Nationals
.474 OPS
AVG .189
OBP .231
SLG .243
HR 0
AB 37
H 7
RBI 2
Austin Riley headshot
Milwaukee Brewers
.473 OPS
AVG .200
OBP .273
SLG .200
HR 0
AB 20
H 4
RBI 1
Dansby Swanson headshot
Arizona Diamondbacks
.473 OPS
AVG .200
OBP .273
SLG .200
HR 0
AB 10
H 2
RBI 1
Caleb Durbin headshot
San Diego Padres
.473 OPS
AVG .200
OBP .273
SLG .200
HR 0
AB 10
H 2
RBI 1
Brayan Rocchio headshot
Los Angeles Dodgers
.473 OPS
AVG .200
OBP .273
SLG .200
HR 0
AB 10
H 2
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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