MLB Batting Splits 2019
Performance splits by handedness, home/away, and situational categories.
| Player | Team | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|
 |
29 | 12 | 4 | 8 | .414 | .452 | .931 | 1.383 | |
 |
13 | 5 | 1 | 1 | .385 | .556 | .769 | 1.325 | |
 |
11 | 5 | 0 | 1 | .455 | .625 | .545 | 1.170 | |
 |
40 | 16 | 3 | 7 | .400 | .455 | .700 | 1.155 | |
 |
21 | 6 | 3 | 6 | .286 | .375 | .762 | 1.137 | |
|
41 | 15 | 3 | 10 | .366 | .426 | .659 | 1.084 | |
 |
10 | 3 | 1 | 2 | .300 | .429 | .600 | 1.029 | |
 |
15 | 5 | 1 | 3 | .333 | .333 | .667 | 1.000 | |
|
20 | 6 | 1 | 5 | .300 | .391 | .600 | .991 | |
|
23 | 6 | 2 | 3 | .261 | .346 | .609 | .955 | |
  |
72 | 22 | 5 | 14 | .306 | .366 | .569 | .935 | |
|
24 | 6 | 1 | 4 | .250 | .486 | .417 | .902 | |
|
53 | 15 | 4 | 12 | .283 | .345 | .547 | .892 | |
 |
37 | 10 | 2 | 4 | .270 | .325 | .514 | .839 | |
 |
12 | 3 | 0 | 2 | .250 | .400 | .417 | .817 | |
 |
21 | 6 | 1 | 5 | .286 | .385 | .429 | .813 | |
|
13 | 2 | 1 | 3 | .154 | .250 | .538 | .788 | |
 |
12 | 4 | 0 | 0 | .333 | .333 | .417 | .750 | |
|
24 | 7 | 0 | 1 | .292 | .320 | .417 | .737 | |
|
12 | 3 | 0 | 1 | .250 | .400 | .333 | .733 | |
|
66 | 15 | 3 | 5 | .227 | .320 | .409 | .729 | |
  |
24 | 5 | 2 | 4 | .208 | .269 | .458 | .728 | |
|
23 | 6 | 1 | 2 | .261 | .320 | .391 | .711 | |
 |
19 | 4 | 1 | 3 | .211 | .286 | .421 | .707 | |
|
28 | 5 | 1 | 7 | .179 | .378 | .321 | .700 | |
|
71 | 16 | 2 | 9 | .225 | .276 | .380 | .657 | |
|
30 | 7 | 1 | 4 | .233 | .281 | .367 | .648 | |
|
66 | 11 | 3 | 7 | .167 | .214 | .318 | .532 | |
|
61 | 11 | 1 | 9 | .180 | .239 | .246 | .485 | |
|
12 | 2 | 0 | 1 | .167 | .231 | .250 | .481 | |
|
10 | 1 | 0 | 0 | .100 | .182 | .200 | .382 | |
|
17 | 1 | 1 | 1 | .059 | .111 | .235 | .346 | |
 |
10 | 1 | 0 | 1 | .100 | .182 | .100 | .282 | |
|
13 | 1 | 0 | 0 | .077 | .143 | .077 | .220 | |
|
11 | 0 | 0 | 0 | .000 | .000 | .000 | .000 |
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.