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 | 13 | 2 | 0 | 1 | .154 | .214 | .154 | .368 | |
 |
San Francisco Giants | 13 | 2 | 0 | 1 | .154 | .214 | .154 | .368 | |
 |
Boston Red Sox | 13 | 2 | 0 | 1 | .154 | .214 | .154 | .368 | |
 |
Cleveland Indians | 13 | 2 | 0 | 0 | .154 | .214 | .154 | .368 | |
  |
Texas Rangers | 15 | 2 | 0 | 1 | .133 | .235 | .133 | .369 | |
 |
Miami Marlins | 15 | 2 | 0 | 0 | .133 | .235 | .133 | .369 | |
|
Pittsburgh Pirates | 20 | 1 | 0 | 1 | .050 | .321 | .050 | .371 | |
 |
Seattle Mariners | 42 | 6 | 0 | 1 | .143 | .229 | .143 | .372 | |
 |
St. Louis Cardinals | 31 | 5 | 0 | 1 | .161 | .212 | .161 | .373 | |
 |
Philadelphia Phillies | 23 | 3 | 0 | 1 | .130 | .200 | .174 | .374 | |
  |
Boston Red Sox | 16 | 3 | 0 | 1 | .188 | .188 | .188 | .375 | |
|
Toronto Blue Jays | 16 | 3 | 0 | 0 | .188 | .188 | .188 | .375 | |
|
Kansas City Royals | 40 | 7 | 0 | 1 | .175 | .175 | .200 | .375 | |
|
Kansas City Royals | 11 | 1 | 0 | 1 | .091 | .286 | .091 | .377 | |
 |
San Diego Padres | 18 | 3 | 0 | 0 | .167 | .211 | .167 | .377 | |
|
Washington Nationals | 11 | 1 | 0 | 0 | .091 | .286 | .091 | .377 | |
 |
New York Yankees | 18 | 3 | 0 | 0 | .167 | .211 | .167 | .377 | |
|
Los Angeles Dodgers | 20 | 3 | 0 | 0 | .150 | .227 | .150 | .377 | |
|
Arizona Diamondbacks | 14 | 2 | 0 | 1 | .143 | .235 | .143 | .378 | |
 |
Seattle Mariners | 12 | 1 | 0 | 0 | .083 | .214 | .167 | .381 | |
 |
Miami Marlins | 12 | 1 | 0 | 2 | .083 | .214 | .167 | .381 | |
|
Pittsburgh Pirates | 12 | 2 | 0 | 1 | .167 | .214 | .167 | .381 | |
 |
Philadelphia Phillies | 12 | 1 | 0 | 1 | .083 | .214 | .167 | .381 | |
|
San Diego Padres | 12 | 2 | 0 | 2 | .167 | .214 | .167 | .381 | |
 |
Arizona Diamondbacks | 21 | 4 | 0 | 0 | .190 | .190 | .190 | .381 | |
|
Philadelphia Phillies | 12 | 1 | 0 | 0 | .083 | .214 | .167 | .381 | |
|
New York Yankees | 12 | 1 | 0 | 0 | .083 | .214 | .167 | .381 | |
|
Kansas City Royals | 31 | 5 | 0 | 2 | .161 | .188 | .194 | .381 | |
|
Boston Red Sox | 10 | 1 | 0 | 0 | .100 | .182 | .200 | .382 | |
|
Texas Rangers | 10 | 2 | 0 | 1 | .200 | .182 | .200 | .382 | |
|
Oakland Athletics | 10 | 1 | 0 | 1 | .100 | .182 | .200 | .382 | |
|
Chicago Cubs | 23 | 4 | 0 | 0 | .174 | .208 | .174 | .382 | |
|
Los Angeles Dodgers | 23 | 4 | 0 | 2 | .174 | .208 | .174 | .382 | |
|
Houston Astros | 10 | 1 | 0 | 0 | .100 | .182 | .200 | .382 | |
|
Milwaukee Brewers | 10 | 1 | 0 | 0 | .100 | .182 | .200 | .382 | |
|
Oakland Athletics | 10 | 1 | 0 | 0 | .100 | .182 | .200 | .382 | |
|
Boston Red Sox | 23 | 4 | 0 | 3 | .174 | .208 | .174 | .382 | |
|
Miami Marlins | 10 | 2 | 0 | 1 | .200 | .182 | .200 | .382 | |
 |
Seattle Mariners | 25 | 2 | 0 | 0 | .080 | .303 | .080 | .383 | |
|
Oakland Athletics | 21 | 2 | 0 | 1 | .095 | .240 | .143 | .383 | |
 |
Atlanta Braves | 13 | 2 | 0 | 0 | .154 | .154 | .231 | .385 | |
|
New York Yankees | 13 | 2 | 0 | 0 | .154 | .154 | .231 | .385 | |
|
San Francisco Giants | 13 | 2 | 0 | 0 | .154 | .154 | .231 | .385 | |
|
Toronto Blue Jays | 13 | 2 | 0 | 0 | .154 | .154 | .231 | .385 | |
|
New York Mets | 13 | 2 | 0 | 1 | .154 | .154 | .231 | .385 | |
|
Houston Astros | 13 | 1 | 1 | 4 | .077 | .077 | .308 | .385 | |
|
Boston Red Sox | 19 | 3 | 0 | 1 | .158 | .227 | .158 | .385 | |
|
Texas Rangers | 16 | 2 | 0 | 1 | .125 | .263 | .125 | .388 | |
|
Houston Astros | 15 | 2 | 0 | 1 | .133 | .188 | .200 | .388 | |
|
Los Angeles Angels | 18 | 3 | 0 | 3 | .167 | .167 | .222 | .389 |
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 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.