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 | 23 | 8 | 2 | 6 | .348 | .433 | .696 | 1.129 | |
 |
St. Louis Cardinals | 12 | 5 | 0 | 0 | .417 | .462 | .667 | 1.128 | |
 |
Houston Astros | 12 | 5 | 0 | 1 | .417 | .462 | .667 | 1.128 | |
 |
Chicago Cubs | 12 | 5 | 1 | 1 | .417 | .462 | .667 | 1.128 | |
 |
Colorado Rockies | 22 | 10 | 0 | 2 | .455 | .536 | .591 | 1.127 | |
 |
New York Mets | 11 | 2 | 2 | 4 | .182 | .400 | .727 | 1.127 | |
 |
Boston Red Sox | 22 | 7 | 3 | 5 | .318 | .400 | .727 | 1.127 | |
|
Atlanta Braves | 11 | 3 | 2 | 4 | .273 | .308 | .818 | 1.126 | |
 |
Washington Nationals | 13 | 4 | 2 | 3 | .308 | .357 | .769 | 1.126 | |
 |
Colorado Rockies | 22 | 7 | 2 | 5 | .318 | .444 | .682 | 1.126 | |
 |
Seattle Mariners | 19 | 5 | 3 | 4 | .263 | .333 | .789 | 1.123 | |
  |
Seattle Mariners | 12 | 6 | 0 | 4 | .500 | .538 | .583 | 1.122 | |
|
Oakland Athletics | 22 | 8 | 1 | 3 | .364 | .440 | .682 | 1.122 | |
|
Seattle Mariners | 12 | 6 | 0 | 3 | .500 | .538 | .583 | 1.122 | |
  |
Oakland Athletics | 13 | 6 | 0 | 1 | .462 | .429 | .692 | 1.121 | |
|
Atlanta Braves | 13 | 5 | 1 | 1 | .385 | .429 | .692 | 1.121 | |
 |
Washington Nationals | 23 | 8 | 2 | 5 | .348 | .423 | .696 | 1.119 | |
 |
Los Angeles Angels | 23 | 8 | 1 | 4 | .348 | .423 | .696 | 1.119 | |
|
Milwaukee Brewers | 44 | 17 | 2 | 8 | .386 | .460 | .659 | 1.119 | |
|
Toronto Blue Jays | 40 | 13 | 3 | 6 | .325 | .518 | .600 | 1.118 | |
 |
Miami Marlins | 10 | 3 | 1 | 1 | .300 | .417 | .700 | 1.117 | |
|
Detroit Tigers | 12 | 5 | 0 | 0 | .417 | .533 | .583 | 1.117 | |
|
San Diego Padres | 10 | 3 | 1 | 3 | .300 | .417 | .700 | 1.117 | |
|
Los Angeles Angels | 10 | 3 | 1 | 3 | .300 | .417 | .700 | 1.117 | |
|
New York Yankees | 46 | 16 | 4 | 12 | .348 | .464 | .652 | 1.116 | |
|
Toronto Blue Jays | 45 | 16 | 5 | 15 | .356 | .383 | .733 | 1.116 | |
 |
Boston Red Sox | 13 | 6 | 0 | 2 | .462 | .500 | .615 | 1.115 | |
|
Colorado Rockies | 13 | 6 | 0 | 2 | .462 | .500 | .615 | 1.115 | |
|
St. Louis Cardinals | 13 | 5 | 1 | 3 | .385 | .500 | .615 | 1.115 | |
|
Cleveland Indians | 24 | 8 | 2 | 4 | .333 | .448 | .667 | 1.115 | |
|
Boston Red Sox | 23 | 8 | 2 | 5 | .348 | .375 | .739 | 1.114 | |
|
Pittsburgh Pirates | 21 | 7 | 2 | 3 | .333 | .400 | .714 | 1.114 | |
|
Baltimore Orioles | 43 | 18 | 2 | 8 | .419 | .510 | .605 | 1.114 | |
|
Los Angeles Angels | 23 | 9 | 2 | 9 | .391 | .375 | .739 | 1.114 | |
|
Los Angeles Dodgers | 11 | 3 | 1 | 5 | .273 | .385 | .727 | 1.112 | |
|
Arizona Diamondbacks | 14 | 6 | 0 | 3 | .429 | .467 | .643 | 1.110 | |
|
Los Angeles Angels | 53 | 19 | 4 | 10 | .358 | .393 | .717 | 1.110 | |
|
Detroit Tigers | 20 | 7 | 2 | 5 | .350 | .409 | .700 | 1.109 | |
|
Seattle Mariners | 20 | 7 | 1 | 5 | .350 | .409 | .700 | 1.109 | |
 |
Minnesota Twins | 20 | 7 | 2 | 4 | .350 | .409 | .700 | 1.109 | |
 |
Baltimore Orioles | 16 | 6 | 0 | 1 | .375 | .421 | .688 | 1.109 | |
|
Los Angeles Angels | 24 | 9 | 2 | 5 | .375 | .400 | .708 | 1.108 | |
|
Oakland Athletics | 17 | 9 | 0 | 1 | .529 | .579 | .529 | 1.108 | |
|
Boston Red Sox | 10 | 2 | 2 | 5 | .200 | .308 | .800 | 1.108 | |
|
St. Louis Cardinals | 12 | 3 | 2 | 6 | .250 | .357 | .750 | 1.107 | |
|
Houston Astros | 21 | 7 | 2 | 3 | .333 | .440 | .667 | 1.107 | |
|
New York Yankees | 24 | 10 | 1 | 3 | .417 | .481 | .625 | 1.106 | |
|
Los Angeles Angels | 37 | 15 | 1 | 6 | .405 | .511 | .595 | 1.106 | |
|
Tampa Bay Rays | 44 | 14 | 4 | 12 | .318 | .423 | .682 | 1.105 | |
|
Minnesota Twins | 26 | 9 | 1 | 6 | .346 | .452 | .654 | 1.105 |
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.