MLB Batting Splits 2025
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|---|
 |
New York Mets | 11 | 1 | 0 | 1 | .091 | .167 | .091 | .258 | |
 |
Cleveland Indians | 11 | 1 | 0 | 0 | .091 | .167 | .091 | .258 | |
|
Atlanta Braves | 11 | 1 | 0 | 0 | .091 | .167 | .091 | .258 | |
 |
Oakland Athletics | 11 | 1 | 0 | 0 | .091 | .167 | .091 | .258 | |
 |
Miami Marlins | 11 | 1 | 0 | 1 | .091 | .167 | .091 | .258 | |
 |
Tampa Bay Rays | 11 | 1 | 0 | 0 | .091 | .167 | .091 | .258 | |
 |
Detroit Tigers | 11 | 1 | 0 | 1 | .091 | .167 | .091 | .258 | |
 |
San Francisco Giants | 11 | 1 | 0 | 0 | .091 | .167 | .091 | .258 | |
|
New York Mets | 11 | 1 | 0 | 1 | .091 | .167 | .091 | .258 | |
|
Oakland Athletics | 11 | 1 | 0 | 0 | .091 | .167 | .091 | .258 | |
  |
Seattle Mariners | 11 | 1 | 0 | 0 | .091 | .167 | .091 | .258 | |
 |
Detroit Tigers | 11 | 1 | 0 | 0 | .091 | .167 | .091 | .258 | |
 |
San Diego Padres | 11 | 1 | 0 | 0 | .091 | .167 | .091 | .258 | |
|
Arizona Diamondbacks | 11 | 1 | 0 | 1 | .091 | .167 | .091 | .258 | |
 |
Texas Rangers | 11 | 1 | 0 | 0 | .091 | .167 | .091 | .258 | |
|
New York Mets | 11 | 1 | 0 | 2 | .091 | .167 | .091 | .258 | |
|
Kansas City Royals | 19 | 2 | 0 | 0 | .105 | .150 | .105 | .255 | |
|
Boston Red Sox | 19 | 2 | 0 | 0 | .105 | .150 | .105 | .255 | |
|
Toronto Blue Jays | 19 | 2 | 0 | 0 | .105 | .150 | .105 | .255 | |
|
New York Mets | 12 | 1 | 0 | 0 | .083 | .083 | .167 | .250 | |
 |
Kansas City Royals | 12 | 1 | 0 | 0 | .083 | .083 | .167 | .250 | |
|
Houston Astros | 20 | 2 | 0 | 0 | .100 | .100 | .150 | .250 | |
|
San Francisco Giants | 12 | 1 | 0 | 0 | .083 | .083 | .167 | .250 | |
  |
Tampa Bay Rays | 12 | 1 | 0 | 0 | .083 | .083 | .167 | .250 | |
|
Oakland Athletics | 16 | 2 | 0 | 0 | .125 | .125 | .125 | .250 | |
 |
Miami Marlins | 19 | 2 | 0 | 1 | .105 | .143 | .105 | .248 | |
 |
Miami Marlins | 36 | 4 | 0 | 0 | .111 | .135 | .111 | .246 | |
|
San Francisco Giants | 18 | 1 | 0 | 0 | .056 | .190 | .056 | .246 | |
|
Chicago White Sox | 18 | 1 | 0 | 0 | .056 | .190 | .056 | .246 | |
|
Cleveland Indians | 11 | 1 | 0 | 1 | .091 | .154 | .091 | .245 | |
|
Arizona Diamondbacks | 11 | 1 | 0 | 1 | .091 | .154 | .091 | .245 | |
|
Milwaukee Brewers | 11 | 1 | 0 | 2 | .091 | .154 | .091 | .245 | |
 |
Cleveland Indians | 21 | 1 | 1 | 1 | .048 | .048 | .190 | .238 | |
 |
New York Mets | 12 | 1 | 0 | 0 | .083 | .154 | .083 | .237 | |
|
Toronto Blue Jays | 12 | 1 | 0 | 0 | .083 | .154 | .083 | .237 | |
 |
Texas Rangers | 12 | 1 | 0 | 0 | .083 | .154 | .083 | .237 | |
 |
Chicago White Sox | 12 | 1 | 0 | 0 | .083 | .154 | .083 | .237 | |
|
Detroit Tigers | 12 | 1 | 0 | 0 | .083 | .154 | .083 | .237 | |
|
Atlanta Braves | 12 | 1 | 0 | 0 | .083 | .154 | .083 | .237 | |
|
Minnesota Twins | 12 | 1 | 0 | 0 | .083 | .154 | .083 | .237 | |
|
Pittsburgh Pirates | 20 | 1 | 0 | 0 | .050 | .136 | .100 | .236 | |
|
Milwaukee Brewers | 19 | 1 | 0 | 0 | .053 | .182 | .053 | .234 | |
|
Toronto Blue Jays | 21 | 2 | 0 | 1 | .095 | .136 | .095 | .232 | |
|
Cleveland Indians | 10 | 0 | 0 | 0 | .000 | .231 | .000 | .231 | |
|
Tampa Bay Rays | 10 | 0 | 0 | 0 | .000 | .231 | .000 | .231 | |
|
Kansas City Royals | 10 | 0 | 0 | 0 | .000 | .231 | .000 | .231 | |
|
Cleveland Indians | 10 | 0 | 0 | 0 | .000 | .231 | .000 | .231 | |
|
St. Louis Cardinals | 13 | 1 | 0 | 1 | .077 | .077 | .154 | .231 | |
|
Cleveland Indians | 10 | 0 | 0 | 0 | .000 | .231 | .000 | .231 | |
 |
New York Yankees | 10 | 0 | 0 | 0 | .000 | .231 | .000 | .231 |
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.
Related MLB Tools
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MLB Player Props Today
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DraftKings MLB Optimizer
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MLB DFS Stacks
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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.