MLB Batting Splits 2025
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|---|
 |
New York Mets | 22 | 9 | 1 | 3 | .409 | .462 | .545 | 1.007 | |
 |
Washington Nationals | 11 | 5 | 0 | 2 | .455 | .462 | .545 | 1.007 | |
 |
Miami Marlins | 49 | 15 | 3 | 9 | .306 | .414 | .592 | 1.006 | |
|
Cincinnati Reds | 24 | 9 | 0 | 1 | .375 | .464 | .542 | 1.006 | |
 |
Tampa Bay Rays | 40 | 11 | 5 | 6 | .275 | .356 | .650 | 1.006 | |
|
Philadelphia Phillies | 28 | 11 | 1 | 4 | .393 | .433 | .571 | 1.005 | |
 |
Chicago White Sox | 42 | 10 | 5 | 9 | .238 | .385 | .619 | 1.004 | |
 |
San Diego Padres | 20 | 5 | 3 | 4 | .250 | .304 | .700 | 1.004 | |
|
Seattle Mariners | 20 | 6 | 2 | 9 | .300 | .304 | .700 | 1.004 | |
 |
Chicago White Sox | 54 | 21 | 2 | 10 | .389 | .411 | .593 | 1.003 | |
 |
Oakland Athletics | 23 | 10 | 0 | 1 | .435 | .480 | .522 | 1.002 | |
 |
Detroit Tigers | 15 | 3 | 2 | 4 | .200 | .400 | .600 | 1.000 | |
|
Baltimore Orioles | 13 | 5 | 1 | 3 | .385 | .385 | .615 | 1.000 | |
|
Los Angeles Dodgers | 12 | 5 | 0 | 0 | .417 | .500 | .500 | 1.000 | |
 |
Cincinnati Reds | 12 | 3 | 2 | 2 | .250 | .250 | .750 | 1.000 | |
 |
Colorado Rockies | 10 | 5 | 0 | 2 | .500 | .500 | .500 | 1.000 | |
|
Los Angeles Angels | 10 | 3 | 1 | 3 | .300 | .300 | .700 | 1.000 | |
  |
Houston Astros | 12 | 5 | 0 | 1 | .417 | .417 | .583 | 1.000 | |
 |
Chicago Cubs | 11 | 4 | 1 | 1 | .364 | .364 | .636 | 1.000 | |
  |
Arizona Diamondbacks | 12 | 4 | 0 | 1 | .333 | .333 | .667 | 1.000 | |
 |
Detroit Tigers | 14 | 6 | 0 | 4 | .429 | .429 | .571 | 1.000 | |
|
Los Angeles Dodgers | 12 | 3 | 2 | 2 | .250 | .250 | .750 | 1.000 | |
 |
Philadelphia Phillies | 12 | 4 | 1 | 3 | .333 | .333 | .667 | 1.000 | |
|
Colorado Rockies | 16 | 7 | 0 | 1 | .438 | .438 | .563 | 1.000 | |
|
Arizona Diamondbacks | 12 | 4 | 1 | 1 | .333 | .333 | .667 | 1.000 | |
|
Toronto Blue Jays | 24 | 10 | 0 | 1 | .417 | .500 | .500 | 1.000 | |
|
St. Louis Cardinals | 14 | 6 | 0 | 2 | .429 | .429 | .571 | 1.000 | |
 |
Cleveland Indians | 17 | 6 | 0 | 0 | .353 | .353 | .647 | 1.000 | |
|
Atlanta Braves | 13 | 4 | 1 | 2 | .308 | .308 | .692 | 1.000 | |
|
Boston Red Sox | 10 | 3 | 1 | 3 | .300 | .300 | .700 | 1.000 | |
 |
Miami Marlins | 12 | 4 | 1 | 5 | .333 | .333 | .667 | 1.000 | |
|
Chicago Cubs | 11 | 4 | 0 | 2 | .364 | .364 | .636 | 1.000 | |
|
San Francisco Giants | 10 | 4 | 0 | 3 | .400 | .400 | .600 | 1.000 | |
|
Miami Marlins | 11 | 4 | 1 | 2 | .364 | .364 | .636 | 1.000 | |
 |
Chicago White Sox | 12 | 5 | 0 | 0 | .417 | .500 | .500 | 1.000 | |
|
Colorado Rockies | 11 | 5 | 0 | 1 | .455 | .455 | .545 | 1.000 | |
|
Cincinnati Reds | 12 | 4 | 1 | 2 | .333 | .333 | .667 | 1.000 | |
|
Seattle Mariners | 11 | 5 | 0 | 1 | .455 | .455 | .545 | 1.000 | |
|
Baltimore Orioles | 20 | 9 | 0 | 0 | .450 | .500 | .500 | 1.000 | |
|
New York Yankees | 14 | 6 | 0 | 1 | .429 | .429 | .571 | 1.000 | |
|
Oakland Athletics | 14 | 5 | 1 | 3 | .357 | .357 | .643 | 1.000 | |
|
New York Yankees | 14 | 4 | 1 | 4 | .286 | .500 | .500 | 1.000 | |
|
Detroit Tigers | 11 | 4 | 1 | 2 | .364 | .364 | .636 | 1.000 | |
|
Arizona Diamondbacks | 15 | 6 | 0 | 4 | .400 | .400 | .600 | 1.000 | |
|
San Francisco Giants | 13 | 3 | 2 | 2 | .231 | .231 | .769 | 1.000 | |
|
St. Louis Cardinals | 20 | 5 | 2 | 5 | .250 | .400 | .600 | 1.000 | |
|
Washington Nationals | 13 | 5 | 1 | 4 | .385 | .385 | .615 | 1.000 | |
|
New York Yankees | 12 | 3 | 2 | 2 | .250 | .250 | .750 | 1.000 | |
|
Arizona Diamondbacks | 14 | 6 | 0 | 2 | .429 | .429 | .571 | 1.000 | |
|
Minnesota Twins | 10 | 4 | 0 | 1 | .400 | .500 | .500 | 1.000 |
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.