MLB Batting Splits 2025
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▲ |
|---|---|---|---|---|---|---|---|---|---|---|
 |
Seattle Mariners | 47 | 6 | 1 | 2 | .128 | .226 | .213 | .439 | |
 |
Arizona Diamondbacks | 20 | 3 | 0 | 1 | .150 | .190 | .250 | .440 | |
 |
Seattle Mariners | 17 | 3 | 0 | 2 | .176 | .263 | .176 | .440 | |
|
Texas Rangers | 21 | 3 | 0 | 0 | .143 | .250 | .190 | .440 | |
 |
Baltimore Orioles | 21 | 3 | 0 | 0 | .143 | .250 | .190 | .440 | |
 |
Miami Marlins | 20 | 3 | 0 | 0 | .150 | .190 | .250 | .440 | |
|
Minnesota Twins | 29 | 6 | 0 | 0 | .207 | .233 | .207 | .440 | |
 |
Pittsburgh Pirates | 25 | 5 | 0 | 3 | .200 | .200 | .240 | .440 | |
 |
Seattle Mariners | 25 | 4 | 0 | 1 | .160 | .241 | .200 | .441 | |
|
Kansas City Royals | 20 | 3 | 0 | 1 | .150 | .292 | .150 | .442 | |
 |
Cincinnati Reds | 37 | 5 | 1 | 2 | .135 | .200 | .243 | .443 | |
 |
Tampa Bay Rays | 38 | 5 | 1 | 3 | .132 | .233 | .211 | .443 | |
 |
Texas Rangers | 18 | 4 | 0 | 2 | .222 | .222 | .222 | .444 | |
 |
New York Yankees | 31 | 4 | 2 | 5 | .129 | .121 | .323 | .444 | |
 |
Toronto Blue Jays | 22 | 4 | 0 | 2 | .182 | .217 | .227 | .445 | |
|
Arizona Diamondbacks | 13 | 2 | 0 | 2 | .154 | .214 | .231 | .445 | |
|
Los Angeles Angels | 13 | 2 | 0 | 1 | .154 | .214 | .231 | .445 | |
|
Miami Marlins | 13 | 2 | 0 | 0 | .154 | .214 | .231 | .445 | |
|
Los Angeles Angels | 13 | 2 | 0 | 1 | .154 | .214 | .231 | .445 | |
 |
New York Mets | 13 | 2 | 0 | 1 | .154 | .214 | .231 | .445 | |
|
Seattle Mariners | 13 | 2 | 0 | 1 | .154 | .214 | .231 | .445 | |
|
Los Angeles Angels | 13 | 2 | 0 | 1 | .154 | .214 | .231 | .445 | |
|
Milwaukee Brewers | 13 | 2 | 0 | 0 | .154 | .214 | .231 | .445 | |
  |
Cleveland Indians | 42 | 8 | 0 | 1 | .190 | .209 | .238 | .447 | |
 |
Boston Red Sox | 29 | 6 | 0 | 2 | .207 | .207 | .241 | .448 | |
|
Los Angeles Dodgers | 34 | 3 | 1 | 3 | .088 | .273 | .176 | .449 | |
 |
Atlanta Braves | 19 | 3 | 0 | 1 | .158 | .238 | .211 | .449 | |
 |
Colorado Rockies | 17 | 3 | 0 | 2 | .176 | .273 | .176 | .449 | |
|
St. Louis Cardinals | 49 | 9 | 0 | 4 | .184 | .245 | .204 | .449 | |
|
Cincinnati Reds | 19 | 3 | 0 | 0 | .158 | .238 | .211 | .449 | |
|
Los Angeles Angels | 20 | 3 | 1 | 5 | .150 | .150 | .300 | .450 | |
 |
Seattle Mariners | 19 | 2 | 0 | 0 | .105 | .292 | .158 | .450 | |
|
Boston Red Sox | 15 | 3 | 0 | 0 | .200 | .250 | .200 | .450 | |
|
Arizona Diamondbacks | 10 | 2 | 0 | 1 | .200 | .250 | .200 | .450 | |
|
Tampa Bay Rays | 10 | 1 | 0 | 0 | .100 | .250 | .200 | .450 | |
|
Pittsburgh Pirates | 10 | 1 | 0 | 0 | .100 | .250 | .200 | .450 | |
|
Atlanta Braves | 10 | 1 | 0 | 1 | .100 | .250 | .200 | .450 | |
|
St. Louis Cardinals | 20 | 3 | 0 | 2 | .150 | .250 | .200 | .450 | |
  |
Chicago Cubs | 21 | 3 | 0 | 1 | .143 | .308 | .143 | .451 | |
|
Texas Rangers | 21 | 4 | 0 | 0 | .190 | .261 | .190 | .451 | |
|
New York Yankees | 13 | 1 | 1 | 1 | .077 | .143 | .308 | .451 | |
|
Toronto Blue Jays | 22 | 4 | 0 | 3 | .182 | .269 | .182 | .451 | |
|
Arizona Diamondbacks | 12 | 2 | 0 | 0 | .167 | .286 | .167 | .452 | |
|
New York Yankees | 12 | 2 | 0 | 1 | .167 | .286 | .167 | .452 | |
|
San Diego Padres | 12 | 2 | 0 | 1 | .167 | .286 | .167 | .452 | |
|
Texas Rangers | 12 | 2 | 0 | 1 | .167 | .286 | .167 | .452 | |
|
San Francisco Giants | 12 | 2 | 0 | 0 | .167 | .286 | .167 | .452 | |
|
Minnesota Twins | 12 | 2 | 0 | 1 | .167 | .286 | .167 | .452 | |
|
Texas Rangers | 12 | 2 | 0 | 0 | .167 | .286 | .167 | .452 | |
|
Boston Red Sox | 12 | 2 | 0 | 1 | .167 | .286 | .167 | .452 |
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.