MLB Batting Splits 2019
Performance splits by handedness, home/away, and situational categories.
| Player | Team | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▲ |
|---|---|---|---|---|---|---|---|---|---|
 |
10 | 0 | 0 | 0 | .000 | .000 | .000 | .000 | |
 |
14 | 0 | 0 | 0 | .000 | .125 | .000 | .125 | |
  |
17 | 3 | 0 | 2 | .176 | .176 | .176 | .353 | |
|
14 | 1 | 0 | 1 | .071 | .235 | .143 | .378 | |
|
16 | 3 | 0 | 0 | .188 | .235 | .250 | .485 | |
 |
19 | 4 | 1 | 2 | .211 | .211 | .368 | .579 | |
 |
18 | 4 | 0 | 1 | .222 | .333 | .278 | .611 | |
 |
12 | 3 | 0 | 1 | .250 | .286 | .333 | .619 | |
 |
69 | 18 | 1 | 6 | .261 | .288 | .333 | .621 | |
 |
22 | 5 | 0 | 0 | .227 | .261 | .364 | .625 | |
 |
27 | 8 | 1 | 3 | .296 | .296 | .407 | .704 | |
 |
19 | 3 | 1 | 2 | .158 | .407 | .316 | .723 | |
|
23 | 5 | 2 | 4 | .217 | .217 | .522 | .739 | |
|
21 | 6 | 1 | 1 | .286 | .348 | .429 | .776 | |
|
26 | 7 | 1 | 4 | .269 | .321 | .462 | .783 | |
  |
14 | 3 | 1 | 3 | .214 | .294 | .500 | .794 | |
|
15 | 4 | 1 | 3 | .267 | .267 | .533 | .800 | |
 |
72 | 21 | 3 | 9 | .292 | .393 | .472 | .865 | |
 |
65 | 19 | 4 | 12 | .292 | .329 | .554 | .882 | |
 |
73 | 26 | 2 | 7 | .356 | .420 | .479 | .899 | |
|
31 | 10 | 1 | 2 | .323 | .364 | .548 | .912 | |
|
22 | 6 | 1 | 3 | .273 | .429 | .500 | .929 | |
 |
24 | 7 | 1 | 1 | .292 | .393 | .542 | .935 | |
|
25 | 6 | 3 | 6 | .240 | .296 | .640 | .936 | |
|
28 | 9 | 3 | 4 | .321 | .387 | .643 | 1.030 | |
 |
26 | 10 | 1 | 2 | .385 | .429 | .654 | 1.082 | |
|
51 | 18 | 3 | 13 | .353 | .455 | .647 | 1.102 | |
|
18 | 7 | 1 | 7 | .389 | .450 | .667 | 1.117 | |
 |
28 | 10 | 4 | 5 | .357 | .471 | .857 | 1.328 | |
|
20 | 7 | 4 | 8 | .350 | .435 | 1.000 | 1.435 | |
 |
10 | 6 | 1 | 1 | .600 | .667 | .900 | 1.567 | |
|
12 | 7 | 2 | 6 | .583 | .643 | 1.333 | 1.976 |
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.