MLB Batting Splits 2019
Performance splits by handedness, home/away, and situational categories.
| Player | Team | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|
 |
25 | 12 | 3 | 5 | .480 | .552 | .840 | 1.392 | |
 |
11 | 3 | 2 | 2 | .273 | .385 | .818 | 1.203 | |
 |
12 | 6 | 0 | 0 | .500 | .500 | .667 | 1.167 | |
 |
21 | 9 | 1 | 6 | .429 | .458 | .571 | 1.030 | |
 |
13 | 4 | 1 | 3 | .308 | .400 | .615 | 1.015 | |
 |
71 | 20 | 7 | 15 | .282 | .342 | .648 | .990 | |
  |
24 | 9 | 1 | 2 | .375 | .444 | .542 | .986 | |
|
25 | 9 | 1 | 3 | .360 | .407 | .560 | .967 | |
 |
24 | 6 | 3 | 7 | .250 | .333 | .625 | .958 | |
|
23 | 9 | 0 | 2 | .391 | .500 | .435 | .935 | |
 |
19 | 6 | 1 | 2 | .316 | .458 | .474 | .932 | |
 |
60 | 19 | 2 | 13 | .317 | .414 | .517 | .931 | |
 |
20 | 4 | 2 | 9 | .200 | .292 | .550 | .842 | |
 |
28 | 8 | 1 | 7 | .286 | .333 | .500 | .833 | |
|
21 | 4 | 2 | 2 | .190 | .320 | .476 | .796 | |
|
15 | 5 | 0 | 4 | .333 | .313 | .467 | .779 | |
|
12 | 4 | 0 | 1 | .333 | .333 | .417 | .750 | |
|
24 | 6 | 1 | 4 | .250 | .308 | .417 | .724 | |
|
31 | 5 | 1 | 5 | .161 | .357 | .355 | .712 | |
 |
64 | 12 | 3 | 10 | .188 | .316 | .391 | .706 | |
|
24 | 6 | 1 | 1 | .250 | .280 | .417 | .697 | |
|
14 | 4 | 0 | 1 | .286 | .313 | .357 | .670 | |
  |
20 | 4 | 0 | 2 | .200 | .304 | .300 | .604 | |
|
30 | 6 | 0 | 4 | .200 | .333 | .233 | .567 | |
|
75 | 18 | 1 | 4 | .240 | .269 | .293 | .563 | |
 |
21 | 5 | 0 | 1 | .238 | .304 | .238 | .542 | |
|
23 | 4 | 0 | 0 | .174 | .321 | .217 | .539 | |
|
13 | 1 | 1 | 2 | .077 | .200 | .308 | .508 | |
 |
26 | 4 | 1 | 5 | .154 | .185 | .269 | .454 | |
 |
10 | 2 | 0 | 1 | .200 | .200 | .200 | .400 | |
|
25 | 4 | 0 | 5 | .160 | .192 | .160 | .352 | |
|
15 | 1 | 0 | 1 | .067 | .125 | .067 | .192 |
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.