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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.
Derek Hill headshot
Los Angeles Angels
.429 OPS
AVG .214
OBP .214
SLG .214
HR 0
AB 14
H 3
RBI 1
Nico Hoerner headshot
Detroit Tigers
.429 OPS
AVG .214
OBP .214
SLG .214
HR 0
AB 14
H 3
RBI 0
Colt Keith headshot
New York Yankees
.429 OPS
AVG .214
OBP .214
SLG .214
HR 0
AB 14
H 3
RBI 1
Christian Walker headshot
Pittsburgh Pirates
.429 OPS
AVG .214
OBP .214
SLG .214
HR 0
AB 14
H 3
RBI 2
Scott Bandura headshot
Los Angeles Dodgers
.429 OPS
AVG .214
OBP .214
SLG .214
HR 0
AB 14
H 3
RBI 1
Jake Burger headshot
Atlanta Braves
.429 OPS
AVG .214
OBP .214
SLG .214
HR 0
AB 14
H 3
RBI 1
Nolan Arenado headshot
Chicago Cubs
.429 OPS
AVG .190
OBP .190
SLG .238
HR 0
AB 21
H 4
RBI 0
Brandon Marsh headshot
Arizona Diamondbacks
.429 OPS
AVG .143
OBP .143
SLG .286
HR 1
AB 21
H 3
RBI 3
Kyle Higashioka headshot
New York Yankees
.429 OPS
AVG .214
OBP .214
SLG .214
HR 0
AB 14
H 3
RBI 0
Brooks Lee headshot
Milwaukee Brewers
.429 OPS
AVG .143
OBP .143
SLG .286
HR 1
AB 21
H 3
RBI 1
Jake Cronenworth headshot
Los Angeles Dodgers
.428 OPS
AVG .130
OBP .167
SLG .261
HR 1
AB 23
H 3
RBI 3
Byron Buxton headshot
Kansas City Royals
.428 OPS
AVG .111
OBP .150
SLG .278
HR 1
AB 18
H 2
RBI 2
Jonathan Aranda headshot
New York Yankees
.427 OPS
AVG .167
OBP .213
SLG .214
HR 0
AB 42
H 7
RBI 7
Byron Buxton headshot
Oakland Athletics
.427 OPS
AVG .150
OBP .227
SLG .200
HR 0
AB 20
H 3
RBI 0
Max Muncy headshot
Chicago White Sox
.427 OPS
AVG .091
OBP .154
SLG .273
HR 0
AB 11
H 1
RBI 1
Elly De La Cruz headshot
Miami Marlins
.427 OPS
AVG .120
OBP .267
SLG .160
HR 0
AB 25
H 3
RBI 1
JJ Bleday headshot
St. Louis Cardinals
.426 OPS
AVG .167
OBP .259
SLG .167
HR 0
AB 48
H 8
RBI 2
Jared Triolo headshot
Milwaukee Brewers
.426 OPS
AVG .174
OBP .208
SLG .217
HR 0
AB 23
H 4
RBI 2
Alec Bohm headshot
Milwaukee Brewers
.426 OPS
AVG .174
OBP .208
SLG .217
HR 0
AB 23
H 4
RBI 1
Yainer Diaz headshot
Boston Red Sox
.426 OPS
AVG .188
OBP .176
SLG .250
HR 0
AB 16
H 3
RBI 1
Anthony Volpe headshot
Boston Red Sox
.426 OPS
AVG .118
OBP .250
SLG .176
HR 0
AB 17
H 2
RBI 0
Jose Ramirez headshot
Seattle Mariners
.426 OPS
AVG .125
OBP .176
SLG .250
HR 0
AB 16
H 2
RBI 3
Spencer Horwitz headshot
Detroit Tigers
.426 OPS
AVG .118
OBP .250
SLG .176
HR 0
AB 17
H 2
RBI 2
Cole Young headshot
San Diego Padres
.426 OPS
AVG .174
OBP .208
SLG .217
HR 0
AB 23
H 4
RBI 2
Jeremiah Jackson headshot
New York Yankees
.425 OPS
AVG .120
OBP .185
SLG .240
HR 1
AB 25
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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