MLB Batting Splits 2019
Performance splits by handedness, home/away, and situational categories.
| Player | Team | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|
 |
14 | 9 | 4 | 4 | .643 | .667 | 1.500 | 2.167 | |
 |
15 | 7 | 2 | 5 | .467 | .529 | .867 | 1.396 | |
  |
25 | 8 | 3 | 8 | .320 | .370 | .840 | 1.210 | |
 |
74 | 29 | 4 | 15 | .392 | .471 | .703 | 1.173 | |
 |
22 | 9 | 1 | 2 | .409 | .500 | .591 | 1.091 | |
 |
11 | 4 | 1 | 3 | .364 | .364 | .727 | 1.091 | |
 |
24 | 10 | 1 | 4 | .417 | .462 | .625 | 1.087 | |
|
62 | 18 | 5 | 9 | .290 | .397 | .613 | 1.010 | |
|
11 | 5 | 0 | 4 | .455 | .500 | .455 | .955 | |
|
22 | 8 | 1 | 1 | .364 | .364 | .591 | .955 | |
 |
64 | 14 | 5 | 9 | .219 | .383 | .563 | .945 | |
 |
26 | 7 | 2 | 5 | .269 | .387 | .538 | .926 | |
|
10 | 3 | 0 | 1 | .300 | .364 | .500 | .864 | |
  |
14 | 5 | 0 | 2 | .357 | .357 | .500 | .857 | |
|
27 | 7 | 2 | 7 | .259 | .276 | .556 | .831 | |
|
22 | 8 | 0 | 0 | .364 | .462 | .364 | .825 | |
 |
27 | 8 | 0 | 1 | .296 | .321 | .444 | .766 | |
 |
27 | 7 | 2 | 6 | .259 | .259 | .481 | .741 | |
|
20 | 5 | 1 | 2 | .250 | .286 | .450 | .736 | |
|
26 | 5 | 2 | 5 | .192 | .276 | .423 | .699 | |
 |
25 | 6 | 1 | 3 | .240 | .296 | .400 | .696 | |
|
18 | 4 | 1 | 3 | .222 | .263 | .389 | .652 | |
 |
14 | 3 | 0 | 1 | .214 | .267 | .357 | .624 | |
|
20 | 3 | 0 | 2 | .150 | .370 | .200 | .570 | |
|
25 | 5 | 0 | 0 | .200 | .259 | .280 | .539 | |
 |
28 | 5 | 1 | 2 | .179 | .226 | .286 | .512 | |
|
10 | 2 | 0 | 2 | .200 | .200 | .300 | .500 | |
|
13 | 1 | 0 | 0 | .077 | .250 | .077 | .327 | |
|
10 | 1 | 0 | 0 | .100 | .100 | .200 | .300 | |
 |
10 | 1 | 0 | 1 | .100 | .100 | .100 | .200 | |
|
11 | 1 | 0 | 1 | .091 | .091 | .091 | .182 | |
|
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.