MLB Batting Splits 2025
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|---|
 |
Tampa Bay Rays | 44 | 14 | 4 | 12 | .318 | .423 | .682 | 1.105 | |
 |
Kansas City Royals | 22 | 7 | 2 | 2 | .318 | .423 | .682 | 1.105 | |
 |
Los Angeles Angels | 45 | 12 | 6 | 10 | .267 | .393 | .711 | 1.104 | |
 |
Kansas City Royals | 16 | 5 | 2 | 3 | .313 | .353 | .750 | 1.103 | |
 |
Washington Nationals | 23 | 7 | 3 | 7 | .304 | .407 | .696 | 1.103 | |
 |
Texas Rangers | 10 | 5 | 0 | 0 | .500 | .500 | .600 | 1.100 | |
  |
Philadelphia Phillies | 10 | 3 | 1 | 4 | .300 | .300 | .800 | 1.100 | |
 |
New York Yankees | 15 | 6 | 1 | 1 | .400 | .500 | .600 | 1.100 | |
|
Philadelphia Phillies | 10 | 4 | 1 | 3 | .400 | .400 | .700 | 1.100 | |
|
Texas Rangers | 10 | 4 | 0 | 2 | .400 | .500 | .600 | 1.100 | |
 |
Los Angeles Dodgers | 10 | 4 | 0 | 2 | .400 | .500 | .600 | 1.100 | |
 |
Colorado Rockies | 10 | 5 | 0 | 1 | .500 | .500 | .600 | 1.100 | |
|
Boston Red Sox | 10 | 5 | 0 | 2 | .500 | .500 | .600 | 1.100 | |
|
Cincinnati Reds | 10 | 4 | 1 | 2 | .400 | .400 | .700 | 1.100 | |
|
Washington Nationals | 16 | 6 | 1 | 1 | .375 | .474 | .625 | 1.099 | |
|
Los Angeles Dodgers | 16 | 6 | 1 | 5 | .375 | .412 | .688 | 1.099 | |
 |
Chicago Cubs | 26 | 11 | 1 | 2 | .423 | .483 | .615 | 1.098 | |
|
Chicago Cubs | 17 | 5 | 2 | 3 | .294 | .333 | .765 | 1.098 | |
  |
Seattle Mariners | 22 | 8 | 1 | 4 | .364 | .417 | .682 | 1.098 | |
 |
Oakland Athletics | 20 | 6 | 3 | 7 | .300 | .348 | .750 | 1.098 | |
 |
Philadelphia Phillies | 11 | 4 | 1 | 1 | .364 | .462 | .636 | 1.098 | |
|
Texas Rangers | 11 | 4 | 1 | 4 | .364 | .462 | .636 | 1.098 | |
|
Washington Nationals | 45 | 17 | 3 | 12 | .378 | .453 | .644 | 1.097 | |
|
Arizona Diamondbacks | 12 | 4 | 1 | 5 | .333 | .429 | .667 | 1.095 | |
|
Seattle Mariners | 18 | 6 | 2 | 2 | .333 | .429 | .667 | 1.095 | |
|
Toronto Blue Jays | 12 | 4 | 1 | 5 | .333 | .429 | .667 | 1.095 | |
|
Los Angeles Angels | 12 | 4 | 1 | 3 | .333 | .429 | .667 | 1.095 | |
|
Miami Marlins | 12 | 4 | 1 | 2 | .333 | .429 | .667 | 1.095 | |
 |
Colorado Rockies | 12 | 5 | 1 | 4 | .417 | .429 | .667 | 1.095 | |
|
Chicago White Sox | 24 | 8 | 3 | 8 | .333 | .385 | .708 | 1.093 | |
 |
Houston Astros | 16 | 8 | 0 | 7 | .500 | .529 | .563 | 1.092 | |
 |
Tampa Bay Rays | 17 | 7 | 1 | 5 | .412 | .444 | .647 | 1.092 | |
|
Toronto Blue Jays | 11 | 3 | 2 | 2 | .273 | .273 | .818 | 1.091 | |
|
San Diego Padres | 11 | 5 | 0 | 1 | .455 | .455 | .636 | 1.091 | |
|
Minnesota Twins | 11 | 4 | 0 | 0 | .364 | .364 | .727 | 1.091 | |
|
Toronto Blue Jays | 11 | 5 | 0 | 2 | .455 | .455 | .636 | 1.091 | |
|
Baltimore Orioles | 26 | 9 | 2 | 5 | .346 | .438 | .654 | 1.091 | |
 |
Pittsburgh Pirates | 11 | 3 | 2 | 2 | .273 | .273 | .818 | 1.091 | |
|
Philadelphia Phillies | 11 | 3 | 2 | 5 | .273 | .273 | .818 | 1.091 | |
|
Boston Red Sox | 21 | 6 | 3 | 7 | .286 | .375 | .714 | 1.089 | |
|
Colorado Rockies | 26 | 8 | 3 | 9 | .308 | .357 | .731 | 1.088 | |
|
Washington Nationals | 15 | 4 | 2 | 4 | .267 | .353 | .733 | 1.086 | |
|
Cincinnati Reds | 11 | 5 | 0 | 3 | .455 | .538 | .545 | 1.084 | |
|
Washington Nationals | 12 | 6 | 0 | 3 | .500 | .500 | .583 | 1.083 | |
|
Chicago White Sox | 12 | 4 | 1 | 2 | .333 | .333 | .750 | 1.083 | |
|
Pittsburgh Pirates | 12 | 5 | 1 | 3 | .417 | .417 | .667 | 1.083 | |
|
Atlanta Braves | 12 | 6 | 0 | 0 | .500 | .500 | .583 | 1.083 | |
|
Philadelphia Phillies | 24 | 9 | 0 | 1 | .375 | .500 | .583 | 1.083 | |
|
Chicago White Sox | 12 | 4 | 1 | 1 | .333 | .333 | .750 | 1.083 | |
|
Baltimore Orioles | 10 | 5 | 0 | 1 | .500 | .583 | .500 | 1.083 |
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.
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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.