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 | 15 | 8 | 0 | 4 | .533 | .563 | .667 | 1.229 | |
 |
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 | |
 |
Oakland Athletics | 21 | 7 | 3 | 5 | .333 | .375 | .857 | 1.232 | |
|
St. Louis Cardinals | 10 | 3 | 1 | 3 | .300 | .533 | .700 | 1.233 | |
  |
Cincinnati Reds | 11 | 4 | 1 | 1 | .364 | .417 | .818 | 1.235 | |
 |
Atlanta Braves | 11 | 4 | 1 | 3 | .364 | .417 | .818 | 1.235 | |
|
Chicago White Sox | 11 | 4 | 1 | 1 | .364 | .417 | .818 | 1.235 | |
 |
Boston Red Sox | 11 | 5 | 0 | 2 | .455 | .600 | .636 | 1.236 | |
|
Baltimore Orioles | 19 | 8 | 0 | 1 | .421 | .500 | .737 | 1.237 | |
|
San Diego Padres | 12 | 6 | 0 | 2 | .500 | .571 | .667 | 1.238 | |
|
San Diego Padres | 10 | 4 | 1 | 3 | .400 | .538 | .700 | 1.238 | |
|
Pittsburgh Pirates | 16 | 7 | 1 | 3 | .438 | .550 | .688 | 1.238 | |
 |
Atlanta Braves | 10 | 4 | 1 | 4 | .400 | .538 | .700 | 1.238 | |
 |
Oakland Athletics | 10 | 4 | 1 | 1 | .400 | .538 | .700 | 1.238 | |
|
Seattle Mariners | 10 | 5 | 0 | 1 | .500 | .538 | .700 | 1.238 | |
 |
Chicago White Sox | 23 | 11 | 1 | 4 | .478 | .500 | .739 | 1.239 | |
|
Chicago White Sox | 21 | 8 | 2 | 8 | .381 | .435 | .810 | 1.244 | |
|
Houston Astros | 15 | 5 | 1 | 2 | .333 | .444 | .800 | 1.244 | |
|
Minnesota Twins | 17 | 6 | 2 | 3 | .353 | .421 | .824 | 1.245 | |
|
Washington Nationals | 10 | 5 | 0 | 1 | .500 | .545 | .700 | 1.245 | |
 |
Cincinnati Reds | 13 | 4 | 2 | 2 | .308 | .400 | .846 | 1.246 | |
 |
New York Mets | 11 | 4 | 1 | 5 | .364 | .429 | .818 | 1.247 | |
|
Kansas City Royals | 11 | 3 | 2 | 5 | .273 | .429 | .818 | 1.247 | |
 |
Los Angeles Dodgers | 22 | 6 | 4 | 8 | .273 | .429 | .818 | 1.247 | |
|
Houston Astros | 14 | 7 | 1 | 5 | .500 | .533 | .714 | 1.248 | |
|
Washington Nationals | 12 | 5 | 0 | 1 | .417 | .500 | .750 | 1.250 | |
|
Pittsburgh Pirates | 12 | 5 | 1 | 3 | .417 | .500 | .750 | 1.250 | |
 |
Oakland Athletics | 16 | 6 | 2 | 5 | .375 | .375 | .875 | 1.250 | |
|
Milwaukee Brewers | 12 | 5 | 1 | 2 | .417 | .500 | .750 | 1.250 | |
|
Baltimore Orioles | 12 | 5 | 1 | 7 | .417 | .417 | .833 | 1.250 | |
|
Tampa Bay Rays | 20 | 7 | 3 | 5 | .350 | .350 | .900 | 1.250 | |
 |
Philadelphia Phillies | 12 | 5 | 1 | 2 | .417 | .417 | .833 | 1.250 | |
|
Minnesota Twins | 25 | 10 | 2 | 8 | .400 | .531 | .720 | 1.251 | |
|
Cleveland Indians | 11 | 6 | 0 | 0 | .545 | .615 | .636 | 1.252 | |
|
Detroit Tigers | 11 | 6 | 0 | 3 | .545 | .615 | .636 | 1.252 | |
|
Washington Nationals | 11 | 6 | 0 | 2 | .545 | .615 | .636 | 1.252 | |
|
Kansas City Royals | 11 | 6 | 0 | 0 | .545 | .615 | .636 | 1.252 | |
 |
Cleveland Indians | 22 | 9 | 3 | 4 | .409 | .435 | .818 | 1.253 | |
|
San Diego Padres | 24 | 10 | 3 | 4 | .417 | .462 | .792 | 1.253 | |
|
Baltimore Orioles | 22 | 9 | 2 | 6 | .409 | .481 | .773 | 1.254 | |
|
Oakland Athletics | 10 | 4 | 1 | 1 | .400 | .455 | .800 | 1.255 | |
|
Miami Marlins | 10 | 4 | 0 | 3 | .400 | .455 | .800 | 1.255 | |
|
Houston Astros | 12 | 5 | 1 | 1 | .417 | .588 | .667 | 1.255 | |
|
Miami Marlins | 54 | 21 | 5 | 19 | .389 | .441 | .815 | 1.255 | |
|
Tampa Bay Rays | 24 | 9 | 3 | 6 | .375 | .423 | .833 | 1.256 | |
 |
Texas Rangers | 13 | 8 | 0 | 2 | .615 | .643 | .615 | 1.258 | |
|
Tampa Bay Rays | 18 | 5 | 4 | 9 | .278 | .316 | .944 | 1.260 | |
|
Los Angeles Dodgers | 17 | 9 | 1 | 6 | .529 | .556 | .706 | 1.261 |
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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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.