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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.
Denzer Guzman headshot
San Francisco Giants
.432 OPS
AVG .182
OBP .250
SLG .182
HR 0
AB 11
H 2
RBI 0
Kerry Carpenter headshot
Arizona Diamondbacks
.432 OPS
AVG .182
OBP .250
SLG .182
HR 0
AB 11
H 2
RBI 1
Christian Yelich headshot
Tampa Bay Rays
.432 OPS
AVG .182
OBP .250
SLG .182
HR 0
AB 11
H 2
RBI 2
Ernie Clement headshot
Los Angeles Dodgers
.432 OPS
AVG .182
OBP .250
SLG .182
HR 0
AB 11
H 2
RBI 1
Henry Bolte headshot
Miami Marlins
.432 OPS
AVG .182
OBP .250
SLG .182
HR 0
AB 11
H 2
RBI 0
Ozzie Albies headshot
Oakland Athletics
.432 OPS
AVG .182
OBP .250
SLG .182
HR 0
AB 11
H 2
RBI 0
Orlando Arcia headshot
Chicago White Sox
.432 OPS
AVG .182
OBP .250
SLG .182
HR 0
AB 11
H 2
RBI 0
Kazuma Okamoto headshot
Milwaukee Brewers
.432 OPS
AVG .182
OBP .250
SLG .182
HR 0
AB 11
H 2
RBI 1
Jazz Chisholm Jr. headshot
San Francisco Giants
.432 OPS
AVG .182
OBP .250
SLG .182
HR 0
AB 11
H 2
RBI 0
Christian Walker headshot
Atlanta Braves
.432 OPS
AVG .182
OBP .250
SLG .182
HR 0
AB 11
H 2
RBI 0
Ryan Waldschmidt headshot
Seattle Mariners
.432 OPS
AVG .182
OBP .250
SLG .182
HR 0
AB 11
H 2
RBI 0
Pedro Ramirez headshot
Atlanta Braves
.432 OPS
AVG .182
OBP .250
SLG .182
HR 0
AB 11
H 2
RBI 1
Gavin Sheets headshot
New York Mets
.432 OPS
AVG .182
OBP .250
SLG .182
HR 0
AB 11
H 2
RBI 1
Jake Meyers headshot
Boston Red Sox
.432 OPS
AVG .182
OBP .250
SLG .182
HR 0
AB 11
H 2
RBI 0
Travis Bazzana headshot
New York Mets
.432 OPS
AVG .182
OBP .250
SLG .182
HR 0
AB 11
H 2
RBI 2
Ketel Marte headshot
New York Yankees
.432 OPS
AVG .182
OBP .250
SLG .182
HR 0
AB 11
H 2
RBI 0
Rafael Devers headshot
Texas Rangers
.432 OPS
AVG .182
OBP .250
SLG .182
HR 0
AB 11
H 2
RBI 0
Jake Cronenworth headshot
Houston Astros
.432 OPS
AVG .182
OBP .250
SLG .182
HR 0
AB 11
H 2
RBI 0
William Contreras headshot
New York Mets
.431 OPS
AVG .125
OBP .222
SLG .208
HR 0
AB 24
H 3
RBI 1
Evan Carter headshot
Oakland Athletics
.431 OPS
AVG .143
OBP .231
SLG .200
HR 0
AB 35
H 5
RBI 1
Trea Turner headshot
St. Louis Cardinals
.431 OPS
AVG .158
OBP .273
SLG .158
HR 0
AB 19
H 3
RBI 0
Otto Lopez headshot
Pittsburgh Pirates
.431 OPS
AVG .200
OBP .231
SLG .200
HR 0
AB 25
H 5
RBI 1
Xavier Edwards headshot
Pittsburgh Pirates
.430 OPS
AVG .190
OBP .240
SLG .190
HR 0
AB 21
H 4
RBI 4
Zach McKinstry headshot
Chicago White Sox
.430 OPS
AVG .100
OBP .280
SLG .150
HR 0
AB 20
H 2
RBI 1
Miguel Vargas headshot
St. Louis Cardinals
.429 OPS
AVG .214
OBP .214
SLG .214
HR 0
AB 14
H 3
RBI 0

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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