MLB Batting Splits 2020
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|---|
 |
Philadelphia Phillies | 17 | 10 | 3 | 7 | .588 | .588 | 1.294 | 1.882 | |
 |
Cleveland Indians | 12 | 8 | 1 | 2 | .667 | .714 | 1.167 | 1.881 | |
 |
Oakland Athletics | 10 | 6 | 2 | 4 | .600 | .583 | 1.200 | 1.783 | |
  |
Washington Nationals | 11 | 6 | 2 | 5 | .545 | .583 | 1.182 | 1.765 | |
 |
Boston Red Sox | 25 | 12 | 5 | 11 | .480 | .552 | 1.160 | 1.712 | |
 |
Baltimore Orioles | 15 | 8 | 2 | 5 | .533 | .588 | 1.067 | 1.655 | |
|
Seattle Mariners | 26 | 12 | 5 | 10 | .462 | .481 | 1.154 | 1.635 | |
|
Cincinnati Reds | 16 | 6 | 3 | 7 | .375 | .524 | 1.063 | 1.586 | |
 |
Houston Astros | 14 | 6 | 3 | 6 | .429 | .429 | 1.143 | 1.571 | |
 |
Milwaukee Brewers | 15 | 9 | 0 | 4 | .600 | .625 | .933 | 1.558 | |
|
Houston Astros | 11 | 5 | 2 | 5 | .455 | .500 | 1.000 | 1.500 | |
|
Houston Astros | 10 | 5 | 1 | 6 | .500 | .583 | .900 | 1.483 | |
|
New York Yankees | 19 | 8 | 3 | 8 | .421 | .522 | .947 | 1.469 | |
|
Oakland Athletics | 13 | 5 | 2 | 5 | .385 | .467 | 1.000 | 1.467 | |
 |
Houston Astros | 18 | 7 | 2 | 4 | .389 | .577 | .889 | 1.466 | |
|
Washington Nationals | 12 | 5 | 2 | 4 | .417 | .462 | 1.000 | 1.462 | |
 |
Milwaukee Brewers | 13 | 6 | 2 | 6 | .462 | .462 | 1.000 | 1.462 | |
 |
Houston Astros | 10 | 4 | 2 | 3 | .400 | .455 | 1.000 | 1.455 | |
|
New York Mets | 24 | 11 | 3 | 11 | .458 | .536 | .917 | 1.452 | |
|
Houston Astros | 20 | 9 | 3 | 7 | .450 | .450 | 1.000 | 1.450 | |
 |
Washington Nationals | 19 | 7 | 3 | 5 | .368 | .500 | .947 | 1.447 | |
|
Los Angeles Dodgers | 13 | 5 | 2 | 3 | .385 | .500 | .923 | 1.423 | |
 |
New York Mets | 12 | 4 | 3 | 6 | .333 | .333 | 1.083 | 1.417 | |
 |
St. Louis Cardinals | 10 | 4 | 2 | 4 | .400 | .400 | 1.000 | 1.400 | |
|
Washington Nationals | 35 | 15 | 4 | 11 | .429 | .512 | .857 | 1.369 | |
 |
Detroit Tigers | 12 | 5 | 1 | 2 | .417 | .611 | .750 | 1.361 | |
|
Pittsburgh Pirates | 14 | 7 | 1 | 3 | .500 | .500 | .857 | 1.357 | |
|
Arizona Diamondbacks | 38 | 14 | 5 | 11 | .368 | .455 | .895 | 1.349 | |
|
Detroit Tigers | 41 | 16 | 5 | 15 | .390 | .457 | .878 | 1.335 | |
|
Oakland Athletics | 26 | 12 | 3 | 5 | .462 | .517 | .808 | 1.325 | |
|
Seattle Mariners | 35 | 13 | 5 | 12 | .371 | .452 | .857 | 1.310 | |
|
Oakland Athletics | 13 | 8 | 0 | 1 | .615 | .615 | .692 | 1.308 | |
|
Houston Astros | 10 | 2 | 2 | 4 | .200 | .500 | .800 | 1.300 | |
|
San Francisco Giants | 17 | 10 | 0 | 4 | .588 | .588 | .706 | 1.294 | |
|
Detroit Tigers | 41 | 18 | 5 | 13 | .439 | .465 | .829 | 1.294 | |
|
Miami Marlins | 11 | 4 | 1 | 4 | .364 | .462 | .818 | 1.280 | |
|
Pittsburgh Pirates | 15 | 6 | 1 | 4 | .400 | .471 | .800 | 1.271 | |
|
Washington Nationals | 24 | 8 | 4 | 9 | .333 | .385 | .875 | 1.260 | |
|
Pittsburgh Pirates | 20 | 5 | 4 | 8 | .250 | .407 | .850 | 1.257 | |
|
Boston Red Sox | 36 | 14 | 4 | 9 | .389 | .450 | .806 | 1.256 | |
|
Colorado Rockies | 41 | 17 | 4 | 11 | .415 | .468 | .780 | 1.249 | |
|
Texas Rangers | 19 | 7 | 3 | 8 | .368 | .400 | .842 | 1.242 | |
|
Baltimore Orioles | 42 | 14 | 7 | 18 | .333 | .356 | .881 | 1.237 | |
|
St. Louis Cardinals | 12 | 4 | 1 | 3 | .333 | .467 | .750 | 1.217 | |
|
Arizona Diamondbacks | 23 | 7 | 4 | 8 | .304 | .346 | .870 | 1.216 | |
|
Atlanta Braves | 12 | 5 | 1 | 4 | .417 | .462 | .750 | 1.212 | |
|
New York Mets | 17 | 8 | 1 | 4 | .471 | .500 | .706 | 1.206 | |
  |
Detroit Tigers | 13 | 5 | 2 | 4 | .385 | .357 | .846 | 1.203 | |
|
Kansas City Royals | 20 | 9 | 2 | 5 | .450 | .450 | .750 | 1.200 | |
|
Cincinnati Reds | 10 | 4 | 1 | 3 | .400 | .400 | .800 | 1.200 |
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.