MLB Batting Splits 2019
Performance splits by handedness, home/away, and situational categories.
| Player | Team | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|
 |
25 | 11 | 4 | 8 | .440 | .531 | .920 | 1.451 | |
 |
22 | 7 | 4 | 5 | .318 | .423 | .864 | 1.287 | |
 |
14 | 6 | 0 | 5 | .429 | .429 | .857 | 1.286 | |
 |
10 | 2 | 2 | 3 | .200 | .429 | .800 | 1.229 | |
|
22 | 8 | 2 | 6 | .364 | .500 | .682 | 1.182 | |
 |
66 | 27 | 3 | 9 | .409 | .473 | .667 | 1.140 | |
|
21 | 9 | 1 | 5 | .429 | .462 | .667 | 1.128 | |
 |
68 | 20 | 9 | 18 | .294 | .368 | .735 | 1.104 | |
|
73 | 21 | 8 | 20 | .288 | .373 | .644 | 1.017 | |
 |
38 | 11 | 3 | 7 | .289 | .372 | .632 | 1.004 | |
|
10 | 2 | 2 | 3 | .200 | .200 | .800 | 1.000 | |
|
26 | 8 | 1 | 4 | .308 | .333 | .577 | .910 | |
 |
25 | 7 | 2 | 4 | .280 | .345 | .560 | .905 | |
  |
23 | 7 | 1 | 3 | .304 | .360 | .522 | .882 | |
|
42 | 11 | 3 | 6 | .262 | .279 | .571 | .850 | |
|
74 | 21 | 4 | 12 | .284 | .354 | .473 | .827 | |
  |
60 | 16 | 2 | 6 | .267 | .333 | .483 | .817 | |
 |
28 | 7 | 2 | 4 | .250 | .276 | .536 | .812 | |
 |
70 | 21 | 1 | 4 | .300 | .355 | .457 | .812 | |
|
28 | 7 | 1 | 2 | .250 | .344 | .464 | .808 | |
 |
64 | 21 | 1 | 10 | .328 | .353 | .438 | .790 | |
|
10 | 3 | 0 | 2 | .300 | .462 | .300 | .762 | |
 |
26 | 8 | 0 | 1 | .308 | .357 | .385 | .742 | |
|
29 | 7 | 1 | 3 | .241 | .290 | .448 | .739 | |
|
23 | 5 | 1 | 5 | .217 | .250 | .435 | .685 | |
|
21 | 6 | 0 | 0 | .286 | .348 | .333 | .681 | |
|
11 | 3 | 0 | 0 | .273 | .385 | .273 | .657 | |
 |
65 | 15 | 1 | 3 | .231 | .315 | .308 | .623 | |
|
26 | 3 | 1 | 2 | .115 | .258 | .231 | .489 | |
|
12 | 1 | 1 | 3 | .083 | .077 | .333 | .410 | |
|
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.
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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.