MLB Batting Splits 2019
Performance splits by handedness, home/away, and situational categories.
| Player | Team | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|
  |
12 | 6 | 2 | 4 | .500 | .500 | 1.083 | 1.583 | |
 |
11 | 7 | 0 | 1 | .636 | .692 | .727 | 1.420 | |
 |
26 | 11 | 2 | 5 | .423 | .484 | .731 | 1.215 | |
 |
18 | 8 | 0 | 0 | .444 | .545 | .611 | 1.157 | |
 |
13 | 5 | 1 | 1 | .385 | .385 | .692 | 1.077 | |
 |
20 | 6 | 2 | 5 | .300 | .375 | .650 | 1.025 | |
 |
52 | 19 | 2 | 10 | .365 | .431 | .538 | .969 | |
 |
46 | 11 | 5 | 8 | .239 | .280 | .630 | .910 | |
 |
64 | 15 | 5 | 9 | .234 | .347 | .531 | .878 | |
 |
20 | 7 | 0 | 3 | .350 | .409 | .450 | .859 | |
|
12 | 3 | 1 | 2 | .250 | .250 | .583 | .833 | |
 |
19 | 4 | 1 | 4 | .211 | .423 | .368 | .791 | |
|
56 | 11 | 4 | 9 | .196 | .308 | .464 | .772 | |
|
51 | 14 | 0 | 5 | .275 | .321 | .431 | .753 | |
 |
27 | 5 | 2 | 3 | .185 | .267 | .444 | .711 | |
 |
17 | 5 | 0 | 1 | .294 | .294 | .412 | .706 | |
|
12 | 3 | 0 | 0 | .250 | .308 | .333 | .641 | |
|
15 | 3 | 0 | 0 | .200 | .368 | .267 | .635 | |
  |
18 | 4 | 1 | 2 | .222 | .222 | .389 | .611 | |
|
21 | 5 | 0 | 2 | .238 | .273 | .333 | .606 | |
|
18 | 3 | 1 | 3 | .167 | .250 | .333 | .583 | |
|
13 | 2 | 1 | 3 | .154 | .154 | .385 | .538 | |
|
10 | 2 | 0 | 1 | .200 | .333 | .200 | .533 | |
 |
25 | 4 | 1 | 1 | .160 | .192 | .320 | .512 | |
|
14 | 3 | 0 | 1 | .214 | .214 | .286 | .500 | |
|
11 | 2 | 0 | 0 | .182 | .308 | .182 | .490 | |
 |
27 | 4 | 0 | 2 | .148 | .172 | .296 | .469 | |
|
23 | 2 | 1 | 1 | .087 | .222 | .217 | .440 | |
|
12 | 2 | 0 | 2 | .167 | .167 | .250 | .417 | |
|
12 | 2 | 0 | 1 | .167 | .231 | .167 | .397 | |
 |
19 | 2 | 0 | 0 | .105 | .227 | .158 | .385 | |
|
11 | 1 | 0 | 2 | .091 | .154 | .182 | .336 |
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.