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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.
Jake Burger headshot
Boston Red Sox
.749 OPS
AVG .190
OBP .320
SLG .429
HR 1
AB 21
H 4
RBI 2
Steven Kwan headshot
San Diego Padres
.748 OPS
AVG .273
OBP .385
SLG .364
HR 0
AB 11
H 3
RBI 1
Travis Bazzana headshot
Arizona Diamondbacks
.748 OPS
AVG .273
OBP .385
SLG .364
HR 0
AB 11
H 3
RBI 0
Austin Riley headshot
Chicago White Sox
.748 OPS
AVG .273
OBP .385
SLG .364
HR 0
AB 11
H 3
RBI 2
Isaac Paredes headshot
Arizona Diamondbacks
.748 OPS
AVG .273
OBP .385
SLG .364
HR 0
AB 11
H 3
RBI 4
Josh Lowe headshot
Baltimore Orioles
.748 OPS
AVG .273
OBP .385
SLG .364
HR 0
AB 11
H 3
RBI 0
Brandon Nimmo headshot
Atlanta Braves
.748 OPS
AVG .273
OBP .385
SLG .364
HR 0
AB 11
H 3
RBI 3
Endy Rodriguez headshot
Colorado Rockies
.748 OPS
AVG .273
OBP .385
SLG .364
HR 0
AB 11
H 3
RBI 2
Austin Martin headshot
New York Yankees
.748 OPS
AVG .273
OBP .385
SLG .364
HR 0
AB 11
H 3
RBI 1
Mauricio Dubon headshot
Colorado Rockies
.748 OPS
AVG .273
OBP .385
SLG .364
HR 0
AB 22
H 6
RBI 4
Matt Shaw headshot
New York Mets
.748 OPS
AVG .273
OBP .385
SLG .364
HR 0
AB 11
H 3
RBI 2
Curtis Mead headshot
Minnesota Twins
.748 OPS
AVG .273
OBP .385
SLG .364
HR 0
AB 11
H 3
RBI 3
Jose Ramirez headshot
Chicago White Sox
.748 OPS
AVG .300
OBP .348
SLG .400
HR 0
AB 20
H 6
RBI 2
Ezequiel Tovar headshot
Washington Nationals
.748 OPS
AVG .235
OBP .278
SLG .471
HR 1
AB 17
H 4
RBI 3
Willson Contreras headshot
Houston Astros
.748 OPS
AVG .318
OBP .385
SLG .364
HR 0
AB 22
H 7
RBI 2
Nico Hoerner headshot
Oakland Athletics
.748 OPS
AVG .273
OBP .385
SLG .364
HR 0
AB 11
H 3
RBI 0
Nick Yorke headshot
Chicago Cubs
.748 OPS
AVG .273
OBP .385
SLG .364
HR 0
AB 11
H 3
RBI 0
Corey Seager headshot
Detroit Tigers
.748 OPS
AVG .273
OBP .385
SLG .364
HR 0
AB 11
H 3
RBI 0
Kyle Karros headshot
Los Angeles Angels
.748 OPS
AVG .273
OBP .385
SLG .364
HR 0
AB 11
H 3
RBI 1
Nick Madrigal headshot
Houston Astros
.748 OPS
AVG .364
OBP .385
SLG .364
HR 0
AB 11
H 4
RBI 1
Francisco Alvarez headshot
St. Louis Cardinals
.748 OPS
AVG .235
OBP .278
SLG .471
HR 1
AB 17
H 4
RBI 2
Bryce Harper headshot
Washington Nationals
.748 OPS
AVG .220
OBP .328
SLG .420
HR 3
AB 50
H 11
RBI 7
Kevin McGonigle headshot
Chicago Cubs
.748 OPS
AVG .273
OBP .385
SLG .364
HR 0
AB 11
H 3
RBI 0
Bo Bichette headshot
Seattle Mariners
.748 OPS
AVG .364
OBP .385
SLG .364
HR 0
AB 11
H 4
RBI 3
Jackson Chourio headshot
Texas Rangers
.747 OPS
AVG .231
OBP .286
SLG .462
HR 1
AB 13
H 3
RBI 3

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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