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MLB Batting Splits 2019

Performance splits by handedness, home/away, and situational categories.

Batting splits break down a hitter's performance across different game situations. Platoon splits (vs LHP/RHP) are the most predictive for DFS and prop betting. Minimum 10 at-bats displayed.
1.511 OPS
AVG .462
OBP .588
SLG .923
HR 2
AB 13
H 6
RBI 4
1.359 OPS
AVG .313
OBP .421
SLG .938
HR 3
AB 16
H 5
RBI 8
1.339 OPS
AVG .476
OBP .577
SLG .762
HR 1
AB 21
H 10
RBI 3
1.285 OPS
AVG .300
OBP .385
SLG .900
HR 2
AB 10
H 3
RBI 4
1.275 OPS
AVG .385
OBP .429
SLG .846
HR 2
AB 13
H 5
RBI 3
1.260 OPS
AVG .452
OBP .486
SLG .774
HR 1
AB 31
H 14
RBI 7
1.150 OPS
AVG .333
OBP .400
SLG .750
HR 1
AB 12
H 4
RBI 2
1.132 OPS
AVG .389
OBP .410
SLG .722
HR 2
AB 36
H 14
RBI 8
1.129 OPS
AVG .467
OBP .529
SLG .600
HR 0
AB 15
H 7
RBI 1
1.063 OPS
AVG .400
OBP .423
SLG .640
HR 1
AB 25
H 10
RBI 3
1.033 OPS
AVG .300
OBP .400
SLG .633
HR 3
AB 30
H 9
RBI 10
1.026 OPS
AVG .319
OBP .373
SLG .652
HR 6
AB 69
H 22
RBI 20
AVG .292
OBP .370
SLG .583
HR 2
AB 24
H 7
RBI 4
.906 OPS
AVG .273
OBP .429
SLG .477
HR 2
AB 44
H 12
RBI 3
.904 OPS
AVG .235
OBP .316
SLG .588
HR 2
AB 17
H 4
RBI 4
.903 OPS
AVG .318
OBP .448
SLG .455
HR 1
AB 22
H 7
RBI 3
.885 OPS
AVG .350
OBP .435
SLG .450
HR 0
AB 20
H 7
RBI 2
.867 OPS
AVG .333
OBP .333
SLG .533
HR 1
AB 15
H 5
RBI 2
.844 OPS
AVG .222
OBP .288
SLG .556
HR 5
AB 54
H 12
RBI 11
.833 OPS
AVG .167
OBP .333
SLG .500
HR 1
AB 12
H 2
RBI 1
.827 OPS
AVG .267
OBP .294
SLG .533
HR 1
AB 15
H 4
RBI 4
.779 OPS
AVG .200
OBP .259
SLG .520
HR 2
AB 25
H 5
RBI 4
.769 OPS
AVG .385
OBP .385
SLG .385
HR 0
AB 13
H 5
RBI 0
.731 OPS
AVG .167
OBP .231
SLG .500
HR 1
AB 12
H 2
RBI 1
.714 OPS
AVG .302
OBP .356
SLG .358
HR 0
AB 53
H 16
RBI 3
AVG .333
OBP .368
SLG .333
HR 0
AB 18
H 6
RBI 2
.696 OPS
AVG .208
OBP .321
SLG .375
HR 1
AB 24
H 5
RBI 2
.695 OPS
AVG .214
OBP .267
SLG .429
HR 1
AB 14
H 3
RBI 2
.669 OPS
AVG .250
OBP .294
SLG .375
HR 0
AB 16
H 4
RBI 2
.653 OPS
AVG .188
OBP .278
SLG .375
HR 1
AB 16
H 3
RBI 2
.649 OPS
AVG .190
OBP .292
SLG .357
HR 2
AB 42
H 8
RBI 5
.577 OPS
AVG .182
OBP .243
SLG .333
HR 1
AB 33
H 6
RBI 4
.515 OPS
AVG .136
OBP .333
SLG .182
HR 0
AB 22
H 3
RBI 3
.421 OPS
AVG .154
OBP .267
SLG .154
HR 0
AB 13
H 2
RBI 0
.377 OPS
AVG .091
OBP .286
SLG .091
HR 0
AB 11
H 1
RBI 1
.333 OPS
AVG .105
OBP .227
SLG .105
HR 0
AB 19
H 2
RBI 0
.167 OPS
AVG .000
OBP .167
SLG .000
HR 0
AB 10
H 0
RBI 0

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.

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.
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