MLB Batting Splits 2019
Performance splits by handedness, home/away, and situational categories.
| Player | Team | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|
 |
21 | 9 | 4 | 7 | .429 | .536 | 1.095 | 1.631 | |
 |
11 | 5 | 0 | 2 | .455 | .571 | .909 | 1.481 | |
|
23 | 10 | 3 | 8 | .435 | .533 | .870 | 1.403 | |
 |
16 | 7 | 1 | 5 | .438 | .526 | .813 | 1.339 | |
 |
74 | 28 | 9 | 21 | .378 | .435 | .797 | 1.233 | |
 |
24 | 6 | 4 | 5 | .250 | .400 | .792 | 1.192 | |
 |
12 | 3 | 2 | 4 | .250 | .438 | .750 | 1.188 | |
 |
51 | 18 | 5 | 11 | .353 | .382 | .725 | 1.107 | |
 |
73 | 23 | 5 | 16 | .315 | .420 | .589 | 1.009 | |
 |
27 | 9 | 2 | 8 | .333 | .333 | .630 | .963 | |
|
65 | 24 | 1 | 9 | .369 | .406 | .554 | .960 | |
 |
21 | 8 | 0 | 0 | .381 | .480 | .476 | .956 | |
  |
10 | 2 | 1 | 1 | .200 | .429 | .500 | .929 | |
|
13 | 4 | 1 | 5 | .308 | .333 | .538 | .872 | |
|
76 | 21 | 3 | 7 | .276 | .325 | .474 | .799 | |
|
23 | 8 | 0 | 1 | .348 | .400 | .391 | .791 | |
|
25 | 5 | 2 | 5 | .200 | .259 | .440 | .699 | |
|
21 | 5 | 1 | 1 | .238 | .304 | .381 | .685 | |
 |
63 | 15 | 3 | 9 | .238 | .300 | .381 | .681 | |
 |
10 | 1 | 1 | 1 | .100 | .250 | .400 | .650 | |
 |
48 | 7 | 3 | 5 | .146 | .255 | .375 | .630 | |
 |
12 | 2 | 0 | 0 | .167 | .333 | .167 | .500 | |
|
19 | 3 | 0 | 2 | .158 | .273 | .211 | .483 | |
|
22 | 3 | 0 | 3 | .136 | .344 | .136 | .480 | |
|
19 | 4 | 0 | 2 | .211 | .211 | .263 | .474 | |
 |
10 | 2 | 0 | 1 | .200 | .273 | .200 | .473 | |
  |
11 | 2 | 0 | 0 | .182 | .250 | .182 | .432 | |
|
53 | 6 | 0 | 4 | .113 | .203 | .151 | .354 |
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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DraftKings MLB Optimizer
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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.