MLB Batting Splits 2025
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|---|
 |
Los Angeles Angels | 17 | 6 | 1 | 5 | .353 | .353 | .706 | 1.059 | |
 |
Toronto Blue Jays | 20 | 7 | 2 | 3 | .350 | .409 | .650 | 1.059 | |
 |
Tampa Bay Rays | 21 | 7 | 2 | 7 | .333 | .391 | .667 | 1.058 | |
 |
Colorado Rockies | 12 | 3 | 2 | 4 | .250 | .308 | .750 | 1.058 | |
 |
Arizona Diamondbacks | 12 | 3 | 2 | 3 | .250 | .308 | .750 | 1.058 | |
 |
San Diego Padres | 12 | 3 | 2 | 3 | .250 | .308 | .750 | 1.058 | |
 |
Milwaukee Brewers | 10 | 4 | 1 | 6 | .400 | .357 | .700 | 1.057 | |
 |
New York Yankees | 36 | 12 | 3 | 8 | .333 | .419 | .639 | 1.057 | |
  |
Tampa Bay Rays | 22 | 7 | 2 | 5 | .318 | .375 | .682 | 1.057 | |
|
Cleveland Indians | 16 | 8 | 0 | 6 | .500 | .556 | .500 | 1.056 | |
|
Detroit Tigers | 18 | 9 | 0 | 0 | .500 | .500 | .556 | 1.056 | |
 |
Philadelphia Phillies | 10 | 4 | 0 | 0 | .400 | .455 | .600 | 1.055 | |
|
Cincinnati Reds | 10 | 4 | 0 | 1 | .400 | .455 | .600 | 1.055 | |
 |
New York Yankees | 13 | 3 | 2 | 3 | .231 | .286 | .769 | 1.055 | |
|
New York Mets | 16 | 4 | 2 | 4 | .250 | .429 | .625 | 1.054 | |
|
Baltimore Orioles | 27 | 8 | 3 | 6 | .296 | .424 | .630 | 1.054 | |
|
New York Yankees | 11 | 4 | 1 | 3 | .364 | .417 | .636 | 1.053 | |
|
San Diego Padres | 11 | 4 | 1 | 2 | .364 | .417 | .636 | 1.053 | |
  |
Milwaukee Brewers | 11 | 4 | 1 | 1 | .364 | .417 | .636 | 1.053 | |
|
Colorado Rockies | 11 | 4 | 1 | 1 | .364 | .417 | .636 | 1.053 | |
|
Los Angeles Dodgers | 12 | 4 | 1 | 4 | .333 | .385 | .667 | 1.051 | |
|
Cleveland Indians | 12 | 5 | 1 | 5 | .417 | .385 | .667 | 1.051 | |
|
Colorado Rockies | 12 | 4 | 1 | 3 | .333 | .385 | .667 | 1.051 | |
 |
New York Mets | 21 | 5 | 3 | 5 | .238 | .385 | .667 | 1.051 | |
 |
San Francisco Giants | 51 | 19 | 3 | 13 | .373 | .385 | .667 | 1.051 | |
|
Atlanta Braves | 12 | 4 | 1 | 1 | .333 | .467 | .583 | 1.050 | |
|
Oakland Athletics | 22 | 9 | 1 | 4 | .409 | .458 | .591 | 1.049 | |
|
Colorado Rockies | 26 | 8 | 2 | 11 | .308 | .357 | .692 | 1.049 | |
|
Detroit Tigers | 24 | 9 | 1 | 2 | .375 | .423 | .625 | 1.048 | |
|
Seattle Mariners | 21 | 8 | 2 | 3 | .381 | .381 | .667 | 1.048 | |
|
Oakland Athletics | 49 | 18 | 3 | 7 | .367 | .415 | .633 | 1.048 | |
|
Baltimore Orioles | 24 | 10 | 1 | 8 | .417 | .423 | .625 | 1.048 | |
|
Pittsburgh Pirates | 24 | 9 | 1 | 5 | .375 | .423 | .625 | 1.048 | |
|
Philadelphia Phillies | 24 | 9 | 2 | 6 | .375 | .423 | .625 | 1.048 | |
 |
Boston Red Sox | 42 | 20 | 0 | 5 | .476 | .500 | .548 | 1.048 | |
 |
Los Angeles Dodgers | 12 | 5 | 0 | 2 | .417 | .462 | .583 | 1.045 | |
|
Atlanta Braves | 11 | 4 | 0 | 1 | .364 | .500 | .545 | 1.045 | |
|
San Diego Padres | 10 | 5 | 0 | 0 | .500 | .545 | .500 | 1.045 | |
|
Texas Rangers | 11 | 5 | 0 | 3 | .455 | .500 | .545 | 1.045 | |
|
Arizona Diamondbacks | 11 | 5 | 0 | 2 | .455 | .500 | .545 | 1.045 | |
|
Pittsburgh Pirates | 11 | 5 | 0 | 0 | .455 | .500 | .545 | 1.045 | |
 |
Toronto Blue Jays | 11 | 5 | 0 | 2 | .455 | .500 | .545 | 1.045 | |
|
New York Mets | 11 | 5 | 0 | 1 | .455 | .500 | .545 | 1.045 | |
|
Tampa Bay Rays | 11 | 5 | 0 | 1 | .455 | .500 | .545 | 1.045 | |
|
San Francisco Giants | 24 | 10 | 1 | 3 | .417 | .462 | .583 | 1.045 | |
|
Milwaukee Brewers | 11 | 5 | 0 | 1 | .455 | .500 | .545 | 1.045 | |
|
Washington Nationals | 11 | 5 | 0 | 0 | .455 | .500 | .545 | 1.045 | |
|
Cincinnati Reds | 13 | 5 | 1 | 5 | .385 | .429 | .615 | 1.044 | |
|
Cleveland Indians | 14 | 5 | 1 | 2 | .357 | .400 | .643 | 1.043 | |
|
Colorado Rockies | 23 | 9 | 1 | 6 | .391 | .391 | .652 | 1.043 |
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.