MLB Batting Splits 2019
Performance splits by handedness, home/away, and situational categories.
| Player | Team | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|
 |
47 | 18 | 4 | 9 | .383 | .524 | .809 | 1.332 | |
 |
18 | 5 | 3 | 6 | .278 | .409 | .889 | 1.298 | |
 |
30 | 12 | 3 | 7 | .400 | .455 | .833 | 1.288 | |
 |
23 | 8 | 3 | 9 | .348 | .429 | .826 | 1.255 | |
|
19 | 7 | 1 | 9 | .368 | .480 | .737 | 1.217 | |
 |
58 | 21 | 6 | 14 | .362 | .456 | .741 | 1.197 | |
|
71 | 26 | 7 | 23 | .366 | .489 | .704 | 1.193 | |
 |
15 | 5 | 1 | 2 | .333 | .375 | .800 | 1.175 | |
 |
22 | 7 | 1 | 6 | .318 | .423 | .682 | 1.105 | |
 |
12 | 5 | 1 | 1 | .417 | .417 | .667 | 1.083 | |
|
11 | 5 | 0 | 3 | .455 | .500 | .545 | 1.045 | |
 |
27 | 9 | 3 | 8 | .333 | .333 | .704 | 1.037 | |
  |
28 | 9 | 2 | 6 | .321 | .406 | .607 | 1.013 | |
|
21 | 8 | 0 | 1 | .381 | .435 | .524 | .959 | |
|
49 | 15 | 2 | 8 | .306 | .358 | .592 | .950 | |
 |
28 | 7 | 2 | 6 | .250 | .250 | .607 | .857 | |
|
11 | 3 | 1 | 2 | .273 | .273 | .545 | .818 | |
 |
59 | 14 | 2 | 5 | .237 | .395 | .407 | .802 | |
  |
59 | 17 | 2 | 7 | .288 | .288 | .475 | .763 | |
|
31 | 7 | 1 | 5 | .226 | .368 | .387 | .756 | |
|
20 | 4 | 1 | 3 | .200 | .304 | .450 | .754 | |
 |
25 | 5 | 1 | 2 | .200 | .310 | .440 | .750 | |
|
12 | 4 | 0 | 0 | .333 | .333 | .417 | .750 | |
 |
41 | 9 | 2 | 9 | .220 | .333 | .415 | .748 | |
|
24 | 5 | 1 | 6 | .208 | .296 | .417 | .713 | |
|
16 | 4 | 0 | 3 | .250 | .294 | .375 | .669 | |
|
24 | 5 | 1 | 4 | .208 | .240 | .375 | .615 | |
|
11 | 2 | 0 | 3 | .182 | .333 | .182 | .515 | |
 |
22 | 4 | 0 | 1 | .182 | .308 | .182 | .490 | |
 |
14 | 2 | 0 | 0 | .143 | .143 | .143 | .286 | |
|
11 | 1 | 0 | 0 | .091 | .167 | .091 | .258 | |
|
13 | 1 | 0 | 1 | .077 | .077 | .077 | .154 |
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.