MLB Batting Splits 2025
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|---|
 |
Atlanta Braves | 11 | 4 | 1 | 3 | .364 | .417 | .818 | 1.235 | |
 |
Chicago White Sox | 11 | 4 | 1 | 1 | .364 | .417 | .818 | 1.235 | |
  |
Cincinnati Reds | 11 | 4 | 1 | 1 | .364 | .417 | .818 | 1.235 | |
 |
St. Louis Cardinals | 10 | 3 | 1 | 3 | .300 | .533 | .700 | 1.233 | |
 |
Oakland Athletics | 21 | 7 | 3 | 5 | .333 | .375 | .857 | 1.232 | |
|
Los Angeles Angels | 20 | 7 | 3 | 5 | .350 | .381 | .850 | 1.231 | |
 |
New York Yankees | 13 | 6 | 1 | 5 | .462 | .462 | .769 | 1.231 | |
|
Los Angeles Angels | 13 | 6 | 1 | 3 | .462 | .462 | .769 | 1.231 | |
  |
Baltimore Orioles | 15 | 8 | 0 | 4 | .533 | .563 | .667 | 1.229 | |
|
New York Yankees | 11 | 4 | 1 | 4 | .364 | .500 | .727 | 1.227 | |
 |
Texas Rangers | 11 | 5 | 0 | 3 | .455 | .500 | .727 | 1.227 | |
 |
Miami Marlins | 22 | 8 | 3 | 5 | .364 | .364 | .864 | 1.227 | |
 |
Minnesota Twins | 29 | 9 | 5 | 12 | .310 | .364 | .862 | 1.226 | |
|
Pittsburgh Pirates | 13 | 6 | 0 | 4 | .462 | .533 | .692 | 1.226 | |
 |
Texas Rangers | 41 | 16 | 3 | 6 | .390 | .444 | .780 | 1.225 | |
|
Baltimore Orioles | 16 | 6 | 2 | 3 | .375 | .412 | .813 | 1.224 | |
|
Toronto Blue Jays | 22 | 6 | 4 | 8 | .273 | .360 | .864 | 1.224 | |
|
Colorado Rockies | 25 | 11 | 2 | 6 | .440 | .464 | .760 | 1.224 | |
 |
Chicago White Sox | 12 | 3 | 2 | 5 | .250 | .308 | .917 | 1.224 | |
|
Boston Red Sox | 21 | 7 | 3 | 5 | .333 | .462 | .762 | 1.223 | |
|
Chicago White Sox | 16 | 7 | 1 | 4 | .438 | .471 | .750 | 1.221 | |
 |
Miami Marlins | 15 | 4 | 3 | 3 | .267 | .353 | .867 | 1.220 | |
 |
Chicago White Sox | 11 | 6 | 0 | 0 | .545 | .583 | .636 | 1.220 | |
|
Colorado Rockies | 37 | 15 | 4 | 10 | .405 | .436 | .784 | 1.220 | |
 |
Baltimore Orioles | 23 | 10 | 2 | 6 | .435 | .480 | .739 | 1.219 | |
 |
Detroit Tigers | 19 | 7 | 2 | 3 | .368 | .429 | .789 | 1.218 | |
|
Chicago Cubs | 12 | 4 | 2 | 4 | .333 | .385 | .833 | 1.218 | |
|
Los Angeles Dodgers | 12 | 4 | 2 | 4 | .333 | .385 | .833 | 1.218 | |
|
Arizona Diamondbacks | 10 | 3 | 1 | 1 | .300 | .417 | .800 | 1.217 | |
|
Detroit Tigers | 10 | 3 | 1 | 1 | .300 | .417 | .800 | 1.217 | |
|
San Francisco Giants | 19 | 6 | 2 | 4 | .316 | .480 | .737 | 1.217 | |
|
Pittsburgh Pirates | 10 | 4 | 1 | 3 | .400 | .417 | .800 | 1.217 | |
|
Washington Nationals | 16 | 8 | 0 | 2 | .500 | .529 | .688 | 1.217 | |
|
Los Angeles Angels | 24 | 9 | 2 | 5 | .375 | .423 | .792 | 1.215 | |
|
Kansas City Royals | 13 | 7 | 0 | 0 | .538 | .600 | .615 | 1.215 | |
|
Detroit Tigers | 25 | 8 | 3 | 5 | .320 | .414 | .800 | 1.214 | |
|
Cleveland Indians | 14 | 7 | 1 | 2 | .500 | .500 | .714 | 1.214 | |
|
Cleveland Indians | 21 | 10 | 1 | 4 | .476 | .500 | .714 | 1.214 | |
|
Philadelphia Phillies | 14 | 5 | 2 | 3 | .357 | .357 | .857 | 1.214 | |
|
Los Angeles Dodgers | 14 | 6 | 1 | 3 | .429 | .429 | .786 | 1.214 | |
|
Los Angeles Dodgers | 12 | 5 | 1 | 2 | .417 | .462 | .750 | 1.212 | |
|
Arizona Diamondbacks | 29 | 12 | 3 | 8 | .414 | .419 | .793 | 1.212 | |
|
Minnesota Twins | 28 | 8 | 5 | 11 | .286 | .355 | .857 | 1.212 | |
|
Los Angeles Dodgers | 12 | 5 | 1 | 2 | .417 | .462 | .750 | 1.212 | |
|
Chicago Cubs | 24 | 6 | 5 | 11 | .250 | .333 | .875 | 1.208 | |
|
Chicago Cubs | 22 | 9 | 2 | 6 | .409 | .480 | .727 | 1.207 | |
|
Texas Rangers | 45 | 13 | 6 | 11 | .289 | .448 | .756 | 1.204 | |
 |
Chicago Cubs | 13 | 4 | 2 | 2 | .308 | .357 | .846 | 1.203 | |
|
Atlanta Braves | 13 | 4 | 2 | 4 | .308 | .357 | .846 | 1.203 | |
|
Cincinnati Reds | 23 | 9 | 1 | 4 | .391 | .462 | .739 | 1.201 |
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.