MLB Batting Splits 2019
Performance splits by handedness, home/away, and situational categories.
| Player | Team | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|
 |
15 | 7 | 2 | 4 | .467 | .579 | 1.000 | 1.579 | |
 |
13 | 4 | 2 | 2 | .308 | .438 | .769 | 1.207 | |
 |
36 | 14 | 1 | 9 | .389 | .488 | .694 | 1.183 | |
 |
19 | 5 | 3 | 5 | .263 | .391 | .737 | 1.128 | |
 |
11 | 2 | 2 | 4 | .182 | .400 | .727 | 1.127 | |
  |
15 | 5 | 1 | 1 | .333 | .412 | .667 | 1.078 | |
 |
70 | 23 | 4 | 9 | .329 | .440 | .571 | 1.012 | |
|
21 | 8 | 0 | 4 | .381 | .480 | .524 | 1.004 | |
|
29 | 8 | 3 | 5 | .276 | .344 | .655 | .999 | |
|
52 | 15 | 4 | 10 | .288 | .383 | .615 | .999 | |
|
22 | 8 | 1 | 3 | .364 | .440 | .500 | .940 | |
 |
29 | 9 | 1 | 3 | .310 | .375 | .552 | .927 | |
 |
61 | 18 | 2 | 9 | .295 | .368 | .525 | .892 | |
 |
21 | 7 | 0 | 1 | .333 | .391 | .476 | .867 | |
 |
26 | 8 | 0 | 4 | .308 | .514 | .346 | .860 | |
|
51 | 13 | 3 | 11 | .255 | .333 | .510 | .843 | |
|
17 | 5 | 1 | 4 | .294 | .333 | .471 | .804 | |
|
11 | 4 | 0 | 0 | .364 | .417 | .364 | .780 | |
|
24 | 7 | 1 | 3 | .292 | .320 | .458 | .778 | |
 |
27 | 5 | 2 | 7 | .185 | .233 | .481 | .715 | |
|
59 | 13 | 1 | 4 | .220 | .324 | .339 | .663 | |
|
65 | 15 | 2 | 8 | .231 | .292 | .369 | .661 | |
|
24 | 7 | 0 | 2 | .292 | .320 | .333 | .653 | |
|
20 | 4 | 1 | 2 | .200 | .238 | .400 | .638 | |
  |
64 | 15 | 2 | 7 | .234 | .246 | .375 | .621 | |
 |
30 | 7 | 1 | 2 | .233 | .281 | .333 | .615 | |
|
24 | 4 | 1 | 4 | .167 | .276 | .333 | .609 | |
|
13 | 2 | 1 | 1 | .154 | .154 | .385 | .538 | |
|
24 | 2 | 1 | 3 | .083 | .241 | .208 | .450 | |
|
15 | 2 | 0 | 2 | .133 | .222 | .200 | .422 | |
 |
19 | 2 | 0 | 1 | .105 | .150 | .158 | .308 | |
|
13 | 1 | 0 | 0 | .077 | .143 | .077 | .220 | |
|
11 | 0 | 0 | 2 | .000 | .214 | .000 | .214 |
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.