MLB Batting Splits 2025
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▲ |
|---|---|---|---|---|---|---|---|---|---|---|
 |
Chicago Cubs | 14 | 3 | 0 | 2 | .214 | .250 | .214 | .464 | |
 |
Miami Marlins | 26 | 3 | 1 | 1 | .115 | .233 | .231 | .464 | |
 |
Houston Astros | 25 | 3 | 1 | 1 | .120 | .185 | .280 | .465 | |
 |
Baltimore Orioles | 16 | 3 | 0 | 0 | .188 | .278 | .188 | .465 | |
 |
Boston Red Sox | 43 | 8 | 0 | 1 | .186 | .255 | .209 | .465 | |
|
Atlanta Braves | 25 | 3 | 1 | 2 | .120 | .185 | .280 | .465 | |
 |
San Francisco Giants | 11 | 1 | 0 | 0 | .091 | .375 | .091 | .466 | |
 |
Atlanta Braves | 13 | 2 | 0 | 0 | .154 | .313 | .154 | .466 | |
 |
Los Angeles Angels | 13 | 2 | 0 | 0 | .154 | .313 | .154 | .466 | |
 |
Detroit Tigers | 11 | 1 | 0 | 0 | .091 | .375 | .091 | .466 | |
|
Minnesota Twins | 13 | 2 | 0 | 2 | .154 | .313 | .154 | .466 | |
|
Tampa Bay Rays | 15 | 3 | 0 | 2 | .200 | .200 | .267 | .467 | |
|
Atlanta Braves | 20 | 2 | 0 | 1 | .100 | .217 | .250 | .467 | |
|
Pittsburgh Pirates | 15 | 3 | 0 | 1 | .200 | .200 | .267 | .467 | |
|
Los Angeles Dodgers | 15 | 3 | 0 | 1 | .200 | .200 | .267 | .467 | |
|
Detroit Tigers | 22 | 3 | 0 | 4 | .136 | .240 | .227 | .467 | |
 |
Colorado Rockies | 15 | 2 | 1 | 1 | .133 | .133 | .333 | .467 | |
 |
New York Yankees | 15 | 3 | 0 | 1 | .200 | .200 | .267 | .467 | |
|
Boston Red Sox | 24 | 4 | 0 | 1 | .167 | .259 | .208 | .468 | |
|
Texas Rangers | 26 | 5 | 0 | 0 | .192 | .276 | .192 | .468 | |
|
Kansas City Royals | 21 | 3 | 0 | 2 | .143 | .182 | .286 | .468 | |
|
Chicago White Sox | 21 | 3 | 1 | 3 | .143 | .182 | .286 | .468 | |
 |
St. Louis Cardinals | 11 | 2 | 0 | 1 | .182 | .286 | .182 | .468 | |
|
Washington Nationals | 23 | 4 | 0 | 2 | .174 | .296 | .174 | .470 | |
|
San Diego Padres | 34 | 7 | 0 | 2 | .206 | .206 | .265 | .471 | |
  |
Baltimore Orioles | 33 | 6 | 0 | 1 | .182 | .229 | .242 | .471 | |
|
Tampa Bay Rays | 33 | 6 | 0 | 2 | .182 | .229 | .242 | .471 | |
 |
Seattle Mariners | 26 | 5 | 0 | 2 | .192 | .241 | .231 | .472 | |
|
Chicago White Sox | 10 | 2 | 0 | 1 | .200 | .273 | .200 | .473 | |
 |
Los Angeles Dodgers | 10 | 2 | 0 | 0 | .200 | .273 | .200 | .473 | |
 |
Toronto Blue Jays | 14 | 1 | 1 | 1 | .071 | .188 | .286 | .473 | |
|
Oakland Athletics | 10 | 2 | 0 | 1 | .200 | .273 | .200 | .473 | |
|
Detroit Tigers | 10 | 2 | 0 | 0 | .200 | .273 | .200 | .473 | |
|
Tampa Bay Rays | 20 | 4 | 0 | 1 | .200 | .273 | .200 | .473 | |
|
San Francisco Giants | 10 | 2 | 0 | 0 | .200 | .273 | .200 | .473 | |
 |
Cincinnati Reds | 10 | 2 | 0 | 2 | .200 | .273 | .200 | .473 | |
|
Boston Red Sox | 10 | 2 | 0 | 1 | .200 | .273 | .200 | .473 | |
|
Washington Nationals | 10 | 2 | 0 | 0 | .200 | .273 | .200 | .473 | |
|
San Francisco Giants | 10 | 2 | 0 | 0 | .200 | .273 | .200 | .473 | |
  |
Texas Rangers | 10 | 2 | 0 | 0 | .200 | .273 | .200 | .473 | |
|
Chicago White Sox | 10 | 2 | 0 | 2 | .200 | .273 | .200 | .473 | |
|
New York Mets | 10 | 2 | 0 | 0 | .200 | .273 | .200 | .473 | |
|
Minnesota Twins | 10 | 2 | 0 | 0 | .200 | .273 | .200 | .473 | |
|
Seattle Mariners | 10 | 2 | 0 | 1 | .200 | .273 | .200 | .473 | |
|
New York Yankees | 10 | 2 | 0 | 0 | .200 | .273 | .200 | .473 | |
|
San Diego Padres | 10 | 2 | 0 | 0 | .200 | .273 | .200 | .473 | |
|
Los Angeles Angels | 10 | 2 | 0 | 0 | .200 | .273 | .200 | .473 | |
 |
Seattle Mariners | 10 | 2 | 0 | 0 | .200 | .273 | .200 | .473 | |
|
Chicago Cubs | 10 | 2 | 0 | 0 | .200 | .273 | .200 | .473 | |
|
Arizona Diamondbacks | 10 | 2 | 0 | 0 | .200 | .273 | .200 | .473 |
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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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.