MLB Batting Splits 2019
Performance splits by handedness, home/away, and situational categories.
| Player | Team | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|
 |
19 | 7 | 2 | 2 | .368 | .400 | .789 | 1.189 | |
 |
21 | 8 | 2 | 5 | .381 | .381 | .762 | 1.143 | |
|
22 | 8 | 2 | 5 | .364 | .364 | .727 | 1.091 | |
 |
13 | 4 | 2 | 4 | .308 | .308 | .769 | 1.077 | |
 |
15 | 5 | 1 | 1 | .333 | .375 | .667 | 1.042 | |
  |
18 | 6 | 1 | 3 | .333 | .400 | .611 | 1.011 | |
 |
28 | 7 | 4 | 5 | .250 | .250 | .750 | 1.000 | |
 |
10 | 4 | 0 | 0 | .400 | .538 | .400 | .938 | |
 |
71 | 19 | 5 | 8 | .268 | .333 | .549 | .883 | |
|
15 | 5 | 0 | 2 | .333 | .412 | .467 | .878 | |
|
13 | 5 | 0 | 4 | .385 | .385 | .462 | .846 | |
 |
33 | 7 | 3 | 6 | .212 | .308 | .515 | .823 | |
|
20 | 6 | 1 | 1 | .300 | .300 | .500 | .800 | |
|
23 | 6 | 1 | 2 | .261 | .320 | .478 | .798 | |
|
25 | 8 | 0 | 0 | .320 | .346 | .440 | .786 | |
|
44 | 13 | 1 | 4 | .295 | .340 | .432 | .772 | |
|
19 | 5 | 1 | 1 | .263 | .333 | .421 | .754 | |
|
20 | 4 | 1 | 2 | .200 | .360 | .350 | .710 | |
  |
24 | 5 | 2 | 5 | .208 | .208 | .500 | .708 | |
 |
13 | 2 | 1 | 1 | .154 | .267 | .385 | .651 | |
|
36 | 6 | 1 | 3 | .167 | .286 | .333 | .619 | |
 |
29 | 6 | 1 | 1 | .207 | .303 | .310 | .613 | |
|
15 | 3 | 0 | 1 | .200 | .333 | .267 | .600 | |
 |
20 | 4 | 0 | 2 | .200 | .261 | .250 | .511 | |
|
22 | 3 | 1 | 2 | .136 | .174 | .273 | .447 | |
|
14 | 2 | 0 | 0 | .143 | .294 | .143 | .437 | |
|
18 | 3 | 0 | 2 | .167 | .167 | .222 | .389 | |
 |
18 | 1 | 1 | 4 | .056 | .150 | .222 | .372 | |
|
13 | 2 | 0 | 0 | .154 | .214 | .154 | .368 | |
 |
24 | 3 | 0 | 1 | .125 | .241 | .125 | .366 | |
 |
12 | 2 | 0 | 1 | .167 | .167 | .167 | .333 | |
|
23 | 2 | 0 | 1 | .087 | .160 | .130 | .290 | |
|
11 | 1 | 0 | 0 | .091 | .091 | .091 | .182 | |
 |
12 | 1 | 0 | 0 | .083 | .083 | .083 | .167 | |
|
12 | 1 | 0 | 0 | .083 | .083 | .083 | .167 |
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.