MLB Batting Splits 2025
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▲ |
|---|---|---|---|---|---|---|---|---|---|---|
 |
Philadelphia Phillies | 35 | 13 | 3 | 6 | .371 | .405 | .743 | 1.148 | |
 |
Boston Red Sox | 18 | 7 | 1 | 4 | .389 | .593 | .556 | 1.148 | |
 |
New York Mets | 20 | 6 | 3 | 6 | .300 | .400 | .750 | 1.150 | |
  |
Washington Nationals | 18 | 7 | 1 | 4 | .389 | .429 | .722 | 1.151 | |
 |
Washington Nationals | 11 | 3 | 2 | 6 | .273 | .333 | .818 | 1.152 | |
|
Toronto Blue Jays | 11 | 3 | 2 | 4 | .273 | .333 | .818 | 1.152 | |
 |
Atlanta Braves | 11 | 3 | 2 | 4 | .273 | .333 | .818 | 1.152 | |
  |
Atlanta Braves | 11 | 3 | 2 | 4 | .273 | .333 | .818 | 1.152 | |
|
Colorado Rockies | 19 | 8 | 1 | 2 | .421 | .522 | .632 | 1.153 | |
 |
Oakland Athletics | 13 | 6 | 0 | 1 | .462 | .462 | .692 | 1.154 | |
 |
Atlanta Braves | 13 | 6 | 1 | 5 | .462 | .462 | .692 | 1.154 | |
|
Arizona Diamondbacks | 13 | 5 | 1 | 3 | .385 | .385 | .769 | 1.154 | |
 |
Houston Astros | 13 | 5 | 1 | 6 | .385 | .385 | .769 | 1.154 | |
 |
Kansas City Royals | 13 | 5 | 1 | 3 | .385 | .385 | .769 | 1.154 | |
 |
Toronto Blue Jays | 13 | 5 | 0 | 1 | .385 | .385 | .769 | 1.154 | |
 |
Baltimore Orioles | 13 | 7 | 0 | 4 | .538 | .538 | .615 | 1.154 | |
|
Pittsburgh Pirates | 13 | 6 | 0 | 1 | .462 | .462 | .692 | 1.154 | |
|
Philadelphia Phillies | 13 | 5 | 0 | 1 | .385 | .385 | .769 | 1.154 | |
|
Cincinnati Reds | 10 | 4 | 1 | 2 | .400 | .455 | .700 | 1.155 | |
|
Arizona Diamondbacks | 12 | 6 | 0 | 1 | .500 | .571 | .583 | 1.155 | |
|
Philadelphia Phillies | 17 | 6 | 2 | 4 | .353 | .450 | .706 | 1.156 | |
|
Washington Nationals | 23 | 9 | 2 | 8 | .391 | .417 | .739 | 1.156 | |
|
Los Angeles Angels | 21 | 7 | 3 | 5 | .333 | .348 | .810 | 1.157 | |
|
Toronto Blue Jays | 17 | 4 | 3 | 7 | .235 | .333 | .824 | 1.157 | |
|
Kansas City Royals | 23 | 8 | 3 | 7 | .348 | .375 | .783 | 1.158 | |
|
Los Angeles Angels | 26 | 10 | 3 | 8 | .385 | .429 | .731 | 1.159 | |
|
San Diego Padres | 11 | 6 | 0 | 1 | .545 | .615 | .545 | 1.161 | |
|
Detroit Tigers | 22 | 9 | 2 | 3 | .409 | .435 | .727 | 1.162 | |
|
Seattle Mariners | 10 | 3 | 1 | 2 | .300 | .462 | .700 | 1.162 | |
 |
San Diego Padres | 10 | 4 | 1 | 5 | .400 | .364 | .800 | 1.164 | |
|
Detroit Tigers | 12 | 5 | 1 | 1 | .417 | .500 | .667 | 1.167 | |
 |
Pittsburgh Pirates | 12 | 4 | 2 | 4 | .333 | .333 | .833 | 1.167 | |
|
Chicago Cubs | 12 | 5 | 1 | 3 | .417 | .417 | .750 | 1.167 | |
|
Toronto Blue Jays | 12 | 4 | 2 | 5 | .333 | .333 | .833 | 1.167 | |
|
Arizona Diamondbacks | 12 | 5 | 1 | 2 | .417 | .500 | .667 | 1.167 | |
 |
Milwaukee Brewers | 12 | 4 | 2 | 2 | .333 | .333 | .833 | 1.167 | |
|
Philadelphia Phillies | 12 | 5 | 1 | 1 | .417 | .500 | .667 | 1.167 | |
 |
Washington Nationals | 12 | 5 | 1 | 6 | .417 | .417 | .750 | 1.167 | |
|
Washington Nationals | 12 | 5 | 1 | 6 | .417 | .417 | .750 | 1.167 | |
|
Pittsburgh Pirates | 13 | 4 | 1 | 3 | .308 | .400 | .769 | 1.169 | |
|
San Diego Padres | 13 | 4 | 2 | 3 | .308 | .400 | .769 | 1.169 | |
|
New York Mets | 26 | 12 | 0 | 7 | .462 | .516 | .654 | 1.170 | |
|
Kansas City Royals | 20 | 8 | 1 | 1 | .400 | .520 | .650 | 1.170 | |
|
Oakland Athletics | 25 | 8 | 3 | 6 | .320 | .370 | .800 | 1.170 | |
 |
Minnesota Twins | 21 | 9 | 2 | 6 | .429 | .409 | .762 | 1.171 | |
|
New York Mets | 16 | 5 | 2 | 4 | .313 | .421 | .750 | 1.171 | |
|
Minnesota Twins | 15 | 6 | 0 | 0 | .400 | .571 | .600 | 1.171 | |
|
Cleveland Indians | 21 | 8 | 2 | 5 | .381 | .458 | .714 | 1.173 | |
|
Toronto Blue Jays | 38 | 15 | 4 | 6 | .395 | .410 | .763 | 1.173 | |
|
Atlanta Braves | 11 | 5 | 0 | 1 | .455 | .538 | .636 | 1.175 |
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.