MLB Batting Splits 2025
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▲ |
|---|---|---|---|---|---|---|---|---|---|---|
 |
Baltimore Orioles | 10 | 3 | 1 | 2 | .300 | .462 | .800 | 1.262 | |
 |
Toronto Blue Jays | 10 | 3 | 1 | 4 | .300 | .462 | .800 | 1.262 | |
 |
New York Mets | 12 | 4 | 1 | 3 | .333 | .429 | .833 | 1.262 | |
|
Washington Nationals | 22 | 9 | 2 | 6 | .409 | .581 | .682 | 1.262 | |
 |
Colorado Rockies | 25 | 10 | 3 | 10 | .400 | .423 | .840 | 1.263 | |
 |
Kansas City Royals | 31 | 12 | 4 | 8 | .387 | .394 | .871 | 1.265 | |
 |
Colorado Rockies | 26 | 8 | 4 | 11 | .308 | .419 | .846 | 1.266 | |
 |
Seattle Mariners | 17 | 9 | 0 | 3 | .529 | .619 | .647 | 1.266 | |
 |
Atlanta Braves | 10 | 6 | 0 | 2 | .600 | .667 | .600 | 1.267 | |
 |
Baltimore Orioles | 27 | 9 | 4 | 12 | .333 | .455 | .815 | 1.269 | |
|
Tampa Bay Rays | 10 | 4 | 1 | 3 | .400 | .571 | .700 | 1.271 | |
 |
Oakland Athletics | 30 | 13 | 2 | 7 | .433 | .438 | .833 | 1.271 | |
|
Chicago Cubs | 24 | 11 | 2 | 2 | .458 | .480 | .792 | 1.272 | |
|
Chicago Cubs | 11 | 5 | 1 | 3 | .455 | .455 | .818 | 1.273 | |
|
San Diego Padres | 11 | 4 | 2 | 4 | .364 | .364 | .909 | 1.273 | |
 |
New York Mets | 11 | 5 | 1 | 2 | .455 | .455 | .818 | 1.273 | |
|
Seattle Mariners | 11 | 7 | 0 | 2 | .636 | .636 | .636 | 1.273 | |
|
Pittsburgh Pirates | 12 | 4 | 2 | 5 | .333 | .357 | .917 | 1.274 | |
|
Chicago White Sox | 15 | 5 | 2 | 6 | .333 | .412 | .867 | 1.278 | |
  |
Colorado Rockies | 12 | 7 | 0 | 0 | .583 | .615 | .667 | 1.282 | |
|
Atlanta Braves | 12 | 7 | 0 | 1 | .583 | .615 | .667 | 1.282 | |
 |
San Francisco Giants | 12 | 5 | 1 | 1 | .417 | .533 | .750 | 1.283 | |
|
Detroit Tigers | 10 | 5 | 0 | 2 | .500 | .583 | .700 | 1.283 | |
|
New York Mets | 12 | 5 | 1 | 3 | .417 | .533 | .750 | 1.283 | |
|
Colorado Rockies | 10 | 5 | 0 | 2 | .500 | .583 | .700 | 1.283 | |
|
Oakland Athletics | 13 | 4 | 2 | 5 | .308 | .438 | .846 | 1.284 | |
 |
Boston Red Sox | 14 | 7 | 1 | 4 | .500 | .500 | .786 | 1.286 | |
  |
Atlanta Braves | 23 | 9 | 2 | 5 | .391 | .462 | .826 | 1.288 | |
|
Los Angeles Dodgers | 27 | 10 | 4 | 12 | .370 | .438 | .852 | 1.289 | |
 |
Seattle Mariners | 19 | 7 | 2 | 5 | .368 | .500 | .789 | 1.289 | |
|
Baltimore Orioles | 46 | 18 | 6 | 13 | .391 | .508 | .783 | 1.291 | |
 |
St. Louis Cardinals | 34 | 13 | 4 | 11 | .382 | .500 | .794 | 1.294 | |
|
Los Angeles Angels | 12 | 5 | 1 | 4 | .417 | .462 | .833 | 1.295 | |
 |
Detroit Tigers | 12 | 5 | 1 | 4 | .417 | .462 | .833 | 1.295 | |
|
Cleveland Indians | 18 | 7 | 1 | 3 | .389 | .577 | .722 | 1.299 | |
|
Washington Nationals | 10 | 4 | 1 | 2 | .400 | .500 | .800 | 1.300 | |
|
Toronto Blue Jays | 31 | 12 | 3 | 12 | .387 | .462 | .839 | 1.300 | |
|
Philadelphia Phillies | 10 | 5 | 1 | 1 | .500 | .500 | .800 | 1.300 | |
 |
Colorado Rockies | 20 | 8 | 2 | 6 | .400 | .500 | .800 | 1.300 | |
|
Washington Nationals | 12 | 4 | 2 | 5 | .333 | .385 | .917 | 1.301 | |
|
Toronto Blue Jays | 17 | 6 | 3 | 4 | .353 | .421 | .882 | 1.303 | |
|
Philadelphia Phillies | 13 | 6 | 1 | 2 | .462 | .533 | .769 | 1.303 | |
|
Toronto Blue Jays | 17 | 6 | 2 | 6 | .353 | .421 | .882 | 1.303 | |
|
Toronto Blue Jays | 14 | 7 | 1 | 3 | .500 | .588 | .714 | 1.303 | |
|
Pittsburgh Pirates | 15 | 6 | 1 | 3 | .400 | .438 | .867 | 1.304 | |
|
Kansas City Royals | 34 | 13 | 3 | 11 | .382 | .512 | .794 | 1.306 | |
|
Colorado Rockies | 13 | 5 | 2 | 4 | .385 | .385 | .923 | 1.308 | |
|
Arizona Diamondbacks | 13 | 6 | 1 | 2 | .462 | .462 | .846 | 1.308 | |
|
Philadelphia Phillies | 13 | 4 | 3 | 8 | .308 | .308 | 1.000 | 1.308 | |
|
Pittsburgh Pirates | 12 | 3 | 3 | 5 | .250 | .308 | 1.000 | 1.308 |
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.