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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.
Nick Gonzales headshot
Atlanta Braves
.646 OPS
AVG .238
OBP .360
SLG .286
HR 0
AB 21
H 5
RBI 3
JJ Wetherholt headshot
Washington Nationals
.646 OPS
AVG .238
OBP .360
SLG .286
HR 0
AB 21
H 5
RBI 3
Ty France headshot
Philadelphia Phillies
.646 OPS
AVG .250
OBP .333
SLG .313
HR 0
AB 16
H 4
RBI 0
Anthony Seigler headshot
Oakland Athletics
.646 OPS
AVG .250
OBP .333
SLG .313
HR 0
AB 16
H 4
RBI 0
Patrick Bailey headshot
Baltimore Orioles
.646 OPS
AVG .267
OBP .313
SLG .333
HR 0
AB 15
H 4
RBI 2
Richie Palacios headshot
Boston Red Sox
.646 OPS
AVG .250
OBP .333
SLG .313
HR 0
AB 16
H 4
RBI 2
Willy Adames headshot
Chicago Cubs
.646 OPS
AVG .143
OBP .217
SLG .429
HR 2
AB 21
H 3
RBI 4
Jake Cronenworth headshot
Colorado Rockies
.646 OPS
AVG .255
OBP .327
SLG .319
HR 0
AB 47
H 12
RBI 3
Luis Arraez headshot
San Diego Padres
.646 OPS
AVG .259
OBP .276
SLG .370
HR 0
AB 27
H 7
RBI 1
Paul Goldschmidt headshot
Boston Red Sox
.645 OPS
AVG .211
OBP .250
SLG .395
HR 2
AB 38
H 8
RBI 7
Munetaka Murakami headshot
Kansas City Royals
.644 OPS
AVG .129
OBP .386
SLG .258
HR 1
AB 31
H 4
RBI 4
Matt Olson headshot
Pittsburgh Pirates
.644 OPS
AVG .208
OBP .269
SLG .375
HR 1
AB 24
H 5
RBI 1
Henry Bolte headshot
Boston Red Sox
.644 OPS
AVG .208
OBP .269
SLG .375
HR 1
AB 24
H 5
RBI 2
Gabriel Moreno headshot
Texas Rangers
.644 OPS
AVG .269
OBP .259
SLG .385
HR 1
AB 26
H 7
RBI 4
Jorbit Vivas headshot
Los Angeles Dodgers
.643 OPS
AVG .231
OBP .412
SLG .231
HR 0
AB 13
H 3
RBI 1
Jac Caglianone headshot
New York Mets
.643 OPS
AVG .214
OBP .214
SLG .429
HR 0
AB 14
H 3
RBI 1
Leody Taveras headshot
St. Louis Cardinals
.643 OPS
AVG .214
OBP .214
SLG .429
HR 1
AB 14
H 3
RBI 5
Elias Diaz headshot
Cleveland Indians
.643 OPS
AVG .214
OBP .214
SLG .429
HR 1
AB 14
H 3
RBI 2
Mauricio Dubon headshot
Texas Rangers
.643 OPS
AVG .286
OBP .286
SLG .357
HR 0
AB 14
H 4
RBI 2
Michael Harris II headshot
Chicago White Sox
.643 OPS
AVG .286
OBP .286
SLG .357
HR 0
AB 14
H 4
RBI 0
Shea Langeliers headshot
Los Angeles Dodgers
.643 OPS
AVG .214
OBP .214
SLG .429
HR 1
AB 14
H 3
RBI 1
Dominic Canzone headshot
Miami Marlins
.643 OPS
AVG .214
OBP .214
SLG .429
HR 1
AB 14
H 3
RBI 2
Nolan Gorman headshot
Houston Astros
.643 OPS
AVG .214
OBP .214
SLG .429
HR 1
AB 14
H 3
RBI 5
Dustin Harris headshot
Miami Marlins
.643 OPS
AVG .286
OBP .286
SLG .357
HR 0
AB 14
H 4
RBI 2
Esteury Ruiz headshot
Los Angeles Dodgers
.643 OPS
AVG .214
OBP .214
SLG .429
HR 1
AB 14
H 3
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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