MLB Batting Splits 2025
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|---|
 |
Houston Astros | 10 | 4 | 1 | 2 | .400 | .500 | .700 | 1.200 | |
 |
Atlanta Braves | 10 | 4 | 1 | 4 | .400 | .500 | .700 | 1.200 | |
 |
Baltimore Orioles | 39 | 14 | 5 | 12 | .359 | .405 | .795 | 1.200 | |
  |
San Francisco Giants | 10 | 4 | 0 | 2 | .400 | .400 | .800 | 1.200 | |
 |
Cincinnati Reds | 10 | 4 | 1 | 1 | .400 | .400 | .800 | 1.200 | |
|
Arizona Diamondbacks | 10 | 5 | 0 | 0 | .500 | .500 | .700 | 1.200 | |
|
Pittsburgh Pirates | 15 | 6 | 2 | 2 | .400 | .400 | .800 | 1.200 | |
|
Kansas City Royals | 10 | 4 | 0 | 4 | .400 | .400 | .800 | 1.200 | |
 |
New York Mets | 18 | 6 | 2 | 4 | .333 | .478 | .722 | 1.200 | |
 |
Miami Marlins | 10 | 4 | 1 | 2 | .400 | .500 | .700 | 1.200 | |
 |
Cincinnati Reds | 15 | 4 | 3 | 4 | .267 | .267 | .933 | 1.200 | |
 |
New York Mets | 10 | 5 | 0 | 2 | .500 | .500 | .700 | 1.200 | |
 |
Chicago Cubs | 22 | 9 | 1 | 4 | .409 | .519 | .682 | 1.200 | |
 |
Boston Red Sox | 10 | 6 | 0 | 1 | .600 | .600 | .600 | 1.200 | |
  |
Cleveland Indians | 12 | 7 | 0 | 0 | .583 | .615 | .583 | 1.199 | |
|
Texas Rangers | 13 | 5 | 1 | 1 | .385 | .429 | .769 | 1.198 | |
|
Arizona Diamondbacks | 13 | 6 | 1 | 2 | .462 | .429 | .769 | 1.198 | |
|
Cincinnati Reds | 13 | 5 | 1 | 5 | .385 | .429 | .769 | 1.198 | |
|
Baltimore Orioles | 18 | 8 | 1 | 7 | .444 | .474 | .722 | 1.196 | |
|
St. Louis Cardinals | 28 | 13 | 1 | 6 | .464 | .516 | .679 | 1.195 | |
|
Toronto Blue Jays | 18 | 9 | 0 | 3 | .500 | .526 | .667 | 1.193 | |
 |
Houston Astros | 13 | 5 | 1 | 2 | .385 | .500 | .692 | 1.192 | |
|
Tampa Bay Rays | 13 | 6 | 0 | 2 | .462 | .500 | .692 | 1.192 | |
|
Washington Nationals | 13 | 6 | 1 | 2 | .462 | .500 | .692 | 1.192 | |
|
San Francisco Giants | 19 | 7 | 2 | 6 | .368 | .455 | .737 | 1.191 | |
|
Colorado Rockies | 12 | 3 | 2 | 4 | .250 | .357 | .833 | 1.190 | |
 |
Los Angeles Dodgers | 18 | 8 | 1 | 2 | .444 | .524 | .667 | 1.190 | |
|
San Diego Padres | 11 | 4 | 1 | 4 | .364 | .462 | .727 | 1.189 | |
|
Los Angeles Angels | 16 | 6 | 2 | 2 | .375 | .375 | .813 | 1.188 | |
|
Los Angeles Angels | 19 | 8 | 2 | 7 | .421 | .450 | .737 | 1.187 | |
|
Los Angeles Angels | 13 | 7 | 0 | 0 | .538 | .571 | .615 | 1.187 | |
|
Minnesota Twins | 48 | 17 | 5 | 11 | .354 | .415 | .771 | 1.186 | |
 |
Texas Rangers | 17 | 6 | 2 | 2 | .353 | .421 | .765 | 1.186 | |
|
Oakland Athletics | 23 | 7 | 4 | 8 | .304 | .360 | .826 | 1.186 | |
|
Minnesota Twins | 14 | 5 | 1 | 4 | .357 | .471 | .714 | 1.185 | |
 |
Los Angeles Dodgers | 10 | 5 | 0 | 1 | .500 | .583 | .600 | 1.183 | |
|
Oakland Athletics | 10 | 5 | 0 | 0 | .500 | .583 | .600 | 1.183 | |
 |
Los Angeles Dodgers | 18 | 5 | 3 | 4 | .278 | .350 | .833 | 1.183 | |
|
Cincinnati Reds | 10 | 5 | 0 | 0 | .500 | .583 | .600 | 1.183 | |
|
Los Angeles Angels | 20 | 10 | 0 | 0 | .500 | .583 | .600 | 1.183 | |
|
Minnesota Twins | 11 | 5 | 0 | 1 | .455 | .455 | .727 | 1.182 | |
|
Minnesota Twins | 11 | 4 | 1 | 3 | .364 | .364 | .818 | 1.182 | |
|
Los Angeles Dodgers | 11 | 5 | 0 | 1 | .455 | .455 | .727 | 1.182 | |
|
Philadelphia Phillies | 11 | 5 | 1 | 2 | .455 | .455 | .727 | 1.182 | |
|
Milwaukee Brewers | 11 | 4 | 1 | 3 | .364 | .364 | .818 | 1.182 | |
|
Cleveland Indians | 11 | 6 | 0 | 2 | .545 | .545 | .636 | 1.182 | |
|
San Diego Padres | 11 | 6 | 0 | 0 | .545 | .545 | .636 | 1.182 | |
|
Chicago Cubs | 14 | 6 | 0 | 3 | .429 | .467 | .714 | 1.181 | |
|
Washington Nationals | 12 | 4 | 1 | 5 | .333 | .429 | .750 | 1.179 | |
|
Cincinnati Reds | 15 | 4 | 3 | 4 | .267 | .313 | .867 | 1.179 |
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.