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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.
1.628 OPS
AVG .417
OBP .462
SLG 1.167
HR 3
AB 12
H 5
RBI 6
1.462 OPS
AVG .385
OBP .385
SLG 1.077
HR 3
AB 13
H 5
RBI 4
1.250 OPS
AVG .381
OBP .536
SLG .714
HR 2
AB 21
H 8
RBI 2
1.189 OPS
AVG .364
OBP .462
SLG .727
HR 1
AB 11
H 4
RBI 2
1.129 OPS
AVG .250
OBP .379
SLG .750
HR 4
AB 24
H 6
RBI 5
1.124 OPS
AVG .304
OBP .385
SLG .739
HR 2
AB 23
H 7
RBI 5
1.098 OPS
AVG .250
OBP .348
SLG .750
HR 3
AB 20
H 5
RBI 5
1.038 OPS
AVG .400
OBP .538
SLG .500
HR 0
AB 10
H 4
RBI 0
.981 OPS
AVG .296
OBP .333
SLG .648
HR 6
AB 54
H 16
RBI 13
.956 OPS
AVG .308
OBP .379
SLG .577
HR 1
AB 26
H 8
RBI 3
AVG .250
OBP .357
SLG .583
HR 1
AB 12
H 3
RBI 1
.930 OPS
AVG .273
OBP .385
SLG .545
HR 1
AB 11
H 3
RBI 1
.864 OPS
AVG .318
OBP .318
SLG .545
HR 1
AB 22
H 7
RBI 2
.843 OPS
AVG .281
OBP .343
SLG .500
HR 2
AB 32
H 9
RBI 5
.800 OPS
AVG .280
OBP .400
SLG .400
HR 0
AB 25
H 7
RBI 4
.773 OPS
AVG .200
OBP .273
SLG .500
HR 1
AB 10
H 2
RBI 1
.770 OPS
AVG .246
OBP .307
SLG .464
HR 4
AB 69
H 17
RBI 11
.740 OPS
AVG .250
OBP .276
SLG .464
HR 2
AB 28
H 7
RBI 4
.710 OPS
AVG .133
OBP .176
SLG .533
HR 2
AB 15
H 2
RBI 4
.699 OPS
AVG .281
OBP .324
SLG .375
HR 0
AB 32
H 9
RBI 4
.696 OPS
AVG .240
OBP .296
SLG .400
HR 1
AB 25
H 6
RBI 4
.693 OPS
AVG .180
OBP .293
SLG .400
HR 3
AB 50
H 9
RBI 7
.684 OPS
AVG .227
OBP .320
SLG .364
HR 0
AB 22
H 5
RBI 0
.671 OPS
AVG .208
OBP .296
SLG .375
HR 0
AB 24
H 5
RBI 2
.583 OPS
AVG .167
OBP .167
SLG .417
HR 1
AB 12
H 2
RBI 1
.497 OPS
AVG .154
OBP .267
SLG .231
HR 0
AB 13
H 2
RBI 0
.417 OPS
AVG .167
OBP .167
SLG .250
HR 0
AB 12
H 2
RBI 0
.376 OPS
AVG .133
OBP .176
SLG .200
HR 0
AB 15
H 2
RBI 2
.335 OPS
AVG .077
OBP .143
SLG .192
HR 1
AB 26
H 2
RBI 1
.301 OPS
AVG .043
OBP .214
SLG .087
HR 0
AB 23
H 1
RBI 0
.276 OPS
AVG .143
OBP .133
SLG .143
HR 0
AB 14
H 2
RBI 3
.275 OPS
AVG .080
OBP .115
SLG .160
HR 0
AB 25
H 2
RBI 1
.232 OPS
AVG .095
OBP .136
SLG .095
HR 0
AB 21
H 2
RBI 1
AVG .077
OBP .143
SLG .077
HR 0
AB 13
H 1
RBI 1
.214 OPS
AVG .000
OBP .214
SLG .000
HR 0
AB 11
H 0
RBI 2
AVG .000
OBP .083
SLG .000
HR 0
AB 11
H 0
RBI 0
.083 OPS
AVG .000
OBP .083
SLG .000
HR 0
AB 11
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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