MLB Batting Splits 2020
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▲ |
|---|---|---|---|---|---|---|---|---|---|---|
 |
Boston Red Sox | 11 | 0 | 0 | 0 | .000 | .000 | .000 | .000 | |
 |
San Diego Padres | 11 | 0 | 0 | 0 | .000 | .000 | .000 | .000 | |
  |
Philadelphia Phillies | 10 | 0 | 0 | 0 | .000 | .000 | .000 | .000 | |
 |
Cleveland Indians | 14 | 0 | 0 | 0 | .000 | .000 | .000 | .000 | |
 |
Texas Rangers | 18 | 0 | 0 | 0 | .000 | .053 | .000 | .053 | |
 |
Texas Rangers | 14 | 0 | 0 | 0 | .000 | .067 | .000 | .067 | |
 |
Los Angeles Dodgers | 12 | 0 | 0 | 1 | .000 | .071 | .000 | .071 | |
|
Los Angeles Dodgers | 10 | 0 | 0 | 0 | .000 | .091 | .000 | .091 | |
 |
Philadelphia Phillies | 10 | 0 | 0 | 1 | .000 | .091 | .000 | .091 | |
|
Kansas City Royals | 15 | 0 | 0 | 0 | .000 | .118 | .000 | .118 | |
|
Chicago White Sox | 13 | 0 | 0 | 0 | .000 | .133 | .000 | .133 | |
 |
Arizona Diamondbacks | 12 | 0 | 0 | 0 | .000 | .143 | .000 | .143 | |
 |
New York Yankees | 11 | 0 | 0 | 0 | .000 | .154 | .000 | .154 | |
|
Miami Marlins | 17 | 1 | 0 | 1 | .059 | .105 | .059 | .164 | |
|
Baltimore Orioles | 10 | 0 | 0 | 1 | .000 | .167 | .000 | .167 | |
|
Cincinnati Reds | 12 | 1 | 0 | 1 | .083 | .083 | .083 | .167 | |
|
Minnesota Twins | 10 | 1 | 0 | 0 | .100 | .100 | .100 | .200 | |
 |
Detroit Tigers | 22 | 1 | 0 | 0 | .045 | .125 | .091 | .216 | |
 |
Toronto Blue Jays | 13 | 1 | 0 | 0 | .077 | .143 | .077 | .220 | |
|
Seattle Mariners | 18 | 2 | 0 | 0 | .111 | .111 | .111 | .222 | |
 |
Philadelphia Phillies | 21 | 2 | 0 | 1 | .095 | .091 | .143 | .234 | |
|
San Diego Padres | 15 | 1 | 0 | 1 | .067 | .176 | .067 | .243 | |
|
Seattle Mariners | 12 | 1 | 0 | 0 | .083 | .083 | .167 | .250 | |
 |
Milwaukee Brewers | 31 | 3 | 0 | 0 | .097 | .097 | .161 | .258 | |
|
New York Yankees | 14 | 1 | 0 | 1 | .071 | .188 | .071 | .259 | |
|
Washington Nationals | 14 | 1 | 0 | 0 | .071 | .188 | .071 | .259 | |
|
Atlanta Braves | 33 | 2 | 0 | 1 | .061 | .205 | .061 | .266 | |
|
Atlanta Braves | 10 | 1 | 0 | 0 | .100 | .182 | .100 | .282 | |
|
Chicago White Sox | 14 | 2 | 0 | 0 | .143 | .143 | .143 | .286 | |
|
Los Angeles Angels | 10 | 0 | 0 | 0 | .000 | .286 | .000 | .286 | |
|
Los Angeles Angels | 26 | 2 | 1 | 4 | .077 | .111 | .192 | .303 | |
  |
St. Louis Cardinals | 35 | 3 | 0 | 2 | .086 | .200 | .114 | .314 | |
|
Los Angeles Dodgers | 15 | 2 | 0 | 0 | .133 | .188 | .133 | .321 | |
|
Minnesota Twins | 11 | 1 | 0 | 0 | .091 | .231 | .091 | .322 | |
|
Arizona Diamondbacks | 17 | 2 | 0 | 1 | .118 | .211 | .118 | .328 | |
|
New York Yankees | 12 | 2 | 0 | 1 | .167 | .167 | .167 | .333 | |
|
San Francisco Giants | 15 | 2 | 0 | 1 | .133 | .133 | .200 | .333 | |
|
Arizona Diamondbacks | 31 | 3 | 1 | 2 | .097 | .152 | .194 | .345 | |
|
Minnesota Twins | 11 | 1 | 0 | 0 | .091 | .167 | .182 | .348 | |
|
Pittsburgh Pirates | 16 | 1 | 0 | 0 | .063 | .286 | .063 | .348 | |
|
New York Yankees | 11 | 1 | 0 | 1 | .091 | .167 | .182 | .348 | |
|
Seattle Mariners | 18 | 2 | 0 | 0 | .111 | .238 | .111 | .349 | |
|
Arizona Diamondbacks | 10 | 1 | 0 | 0 | .100 | .250 | .100 | .350 | |
|
Toronto Blue Jays | 10 | 1 | 0 | 0 | .100 | .250 | .100 | .350 | |
|
Minnesota Twins | 10 | 1 | 0 | 0 | .100 | .250 | .100 | .350 | |
|
Milwaukee Brewers | 36 | 5 | 0 | 1 | .139 | .184 | .167 | .351 | |
|
Seattle Mariners | 21 | 2 | 0 | 2 | .095 | .269 | .095 | .364 | |
|
Kansas City Royals | 22 | 4 | 0 | 2 | .182 | .182 | .182 | .364 | |
|
Chicago Cubs | 11 | 2 | 0 | 0 | .182 | .182 | .182 | .364 | |
|
San Francisco Giants | 20 | 2 | 0 | 0 | .100 | .217 | .150 | .367 |
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.