MLB Batting Splits 2025
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▲ |
|---|---|---|---|---|---|---|---|---|---|---|
 |
San Diego Padres | 11 | 2 | 0 | 1 | .182 | .231 | .182 | .413 | |
 |
New York Mets | 11 | 1 | 0 | 0 | .091 | .231 | .182 | .413 | |
 |
Pittsburgh Pirates | 11 | 1 | 0 | 0 | .091 | .231 | .182 | .413 | |
 |
Milwaukee Brewers | 11 | 2 | 0 | 1 | .182 | .231 | .182 | .413 | |
 |
Tampa Bay Rays | 14 | 3 | 0 | 1 | .214 | .200 | .214 | .414 | |
 |
Los Angeles Dodgers | 51 | 6 | 1 | 1 | .118 | .237 | .176 | .414 | |
|
Arizona Diamondbacks | 14 | 2 | 0 | 1 | .143 | .200 | .214 | .414 | |
 |
Toronto Blue Jays | 23 | 4 | 0 | 1 | .174 | .240 | .174 | .414 | |
 |
Tampa Bay Rays | 23 | 3 | 0 | 0 | .130 | .286 | .130 | .416 | |
|
New York Yankees | 38 | 7 | 0 | 3 | .184 | .205 | .211 | .416 | |
 |
St. Louis Cardinals | 12 | 2 | 0 | 0 | .167 | .167 | .250 | .417 | |
  |
Milwaukee Brewers | 18 | 3 | 0 | 0 | .167 | .250 | .167 | .417 | |
|
Los Angeles Dodgers | 12 | 2 | 0 | 0 | .167 | .167 | .250 | .417 | |
 |
Kansas City Royals | 12 | 2 | 0 | 2 | .167 | .167 | .250 | .417 | |
|
Chicago White Sox | 12 | 2 | 0 | 0 | .167 | .167 | .250 | .417 | |
  |
Baltimore Orioles | 12 | 1 | 1 | 3 | .083 | .083 | .333 | .417 | |
|
San Francisco Giants | 12 | 2 | 0 | 1 | .167 | .167 | .250 | .417 | |
|
Milwaukee Brewers | 12 | 1 | 1 | 1 | .083 | .083 | .333 | .417 | |
 |
Texas Rangers | 16 | 1 | 1 | 1 | .063 | .167 | .250 | .417 | |
 |
Cincinnati Reds | 12 | 1 | 1 | 2 | .083 | .083 | .333 | .417 | |
|
Washington Nationals | 18 | 3 | 0 | 0 | .167 | .250 | .167 | .417 | |
 |
Texas Rangers | 21 | 4 | 0 | 2 | .190 | .227 | .190 | .418 | |
|
Cleveland Indians | 35 | 6 | 0 | 3 | .171 | .189 | .229 | .418 | |
 |
Los Angeles Angels | 14 | 1 | 1 | 1 | .071 | .133 | .286 | .419 | |
|
Minnesota Twins | 32 | 4 | 0 | 2 | .125 | .263 | .156 | .419 | |
|
Pittsburgh Pirates | 19 | 2 | 0 | 0 | .105 | .261 | .158 | .419 | |
|
San Diego Padres | 19 | 2 | 0 | 2 | .105 | .261 | .158 | .419 | |
|
Cleveland Indians | 13 | 2 | 0 | 2 | .154 | .267 | .154 | .421 | |
|
Pittsburgh Pirates | 13 | 2 | 0 | 0 | .154 | .267 | .154 | .421 | |
 |
San Francisco Giants | 13 | 2 | 0 | 0 | .154 | .267 | .154 | .421 | |
|
Minnesota Twins | 21 | 2 | 1 | 2 | .095 | .136 | .286 | .422 | |
|
Boston Red Sox | 18 | 3 | 0 | 3 | .167 | .200 | .222 | .422 | |
|
New York Mets | 22 | 2 | 0 | 1 | .091 | .286 | .136 | .422 | |
|
Minnesota Twins | 24 | 3 | 0 | 4 | .125 | .214 | .208 | .423 | |
|
New York Yankees | 16 | 3 | 0 | 0 | .188 | .235 | .188 | .423 | |
|
Baltimore Orioles | 16 | 3 | 0 | 4 | .188 | .235 | .188 | .423 | |
|
Oakland Athletics | 11 | 1 | 0 | 0 | .091 | .333 | .091 | .424 | |
|
Washington Nationals | 25 | 3 | 1 | 1 | .120 | .185 | .240 | .425 | |
|
New York Yankees | 17 | 2 | 0 | 0 | .118 | .250 | .176 | .426 | |
|
Tampa Bay Rays | 22 | 2 | 1 | 1 | .091 | .200 | .227 | .427 | |
|
Kansas City Royals | 11 | 1 | 0 | 1 | .091 | .154 | .273 | .427 | |
|
Milwaukee Brewers | 25 | 3 | 0 | 2 | .120 | .267 | .160 | .427 | |
 |
New York Mets | 20 | 3 | 0 | 1 | .150 | .227 | .200 | .427 | |
|
Cincinnati Reds | 11 | 1 | 0 | 3 | .091 | .154 | .273 | .427 | |
|
San Francisco Giants | 21 | 4 | 0 | 0 | .190 | .190 | .238 | .429 | |
|
New York Mets | 23 | 3 | 1 | 3 | .130 | .125 | .304 | .429 | |
|
San Francisco Giants | 27 | 4 | 0 | 3 | .148 | .207 | .222 | .429 | |
|
Milwaukee Brewers | 14 | 3 | 0 | 0 | .214 | .214 | .214 | .429 | |
|
Milwaukee Brewers | 16 | 2 | 1 | 2 | .125 | .118 | .313 | .430 | |
|
Kansas City Royals | 25 | 5 | 0 | 1 | .200 | .231 | .200 | .431 |
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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MLB DFS Stacks
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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.