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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.
1.413 OPS
AVG .408
OBP .469
SLG .944
HR 10
AB 71
H 29
RBI 26
1.407 OPS
AVG .371
OBP .522
SLG .886
HR 4
AB 35
H 13
RBI 10
1.308 OPS
AVG .385
OBP .385
SLG .923
HR 2
AB 13
H 5
RBI 3
1.274 OPS
AVG .333
OBP .357
SLG .917
HR 2
AB 12
H 4
RBI 5
1.244 OPS
AVG .458
OBP .536
SLG .708
HR 0
AB 24
H 11
RBI 4
1.174 OPS
AVG .389
OBP .433
SLG .741
HR 5
AB 54
H 21
RBI 13
1.145 OPS
AVG .333
OBP .545
SLG .600
HR 1
AB 15
H 5
RBI 3
1.128 OPS
AVG .417
OBP .462
SLG .667
HR 1
AB 12
H 5
RBI 5
1.097 OPS
AVG .353
OBP .450
SLG .647
HR 1
AB 17
H 6
RBI 4
1.079 OPS
AVG .292
OBP .370
SLG .708
HR 3
AB 24
H 7
RBI 10
1.047 OPS
AVG .333
OBP .455
SLG .593
HR 2
AB 27
H 9
RBI 4
1.000 OPS
AVG .313
OBP .313
SLG .688
HR 1
AB 16
H 5
RBI 3
.976 OPS
AVG .308
OBP .438
SLG .538
HR 1
AB 13
H 4
RBI 2
.933 OPS
AVG .200
OBP .333
SLG .600
HR 2
AB 15
H 3
RBI 4
AVG .333
OBP .370
SLG .542
HR 1
AB 24
H 8
RBI 6
.857 OPS
AVG .289
OBP .357
SLG .500
HR 2
AB 38
H 11
RBI 3
.855 OPS
AVG .182
OBP .400
SLG .455
HR 1
AB 11
H 2
RBI 1
.843 OPS
AVG .261
OBP .307
SLG .536
HR 5
AB 69
H 18
RBI 14
.821 OPS
AVG .368
OBP .400
SLG .421
HR 0
AB 19
H 7
RBI 1
.812 OPS
AVG .302
OBP .321
SLG .491
HR 1
AB 53
H 16
RBI 10
.808 OPS
AVG .250
OBP .308
SLG .500
HR 2
AB 24
H 6
RBI 5
.801 OPS
AVG .182
OBP .438
SLG .364
HR 0
AB 11
H 2
RBI 2
.800 OPS
AVG .333
OBP .467
SLG .333
HR 0
AB 12
H 4
RBI 0
.782 OPS
AVG .297
OBP .350
SLG .432
HR 1
AB 37
H 11
RBI 3
.778 OPS
AVG .256
OBP .313
SLG .465
HR 2
AB 43
H 11
RBI 7
.747 OPS
AVG .231
OBP .286
SLG .462
HR 1
AB 26
H 6
RBI 4
.745 OPS
AVG .240
OBP .345
SLG .400
HR 1
AB 25
H 6
RBI 7
.715 OPS
AVG .158
OBP .346
SLG .368
HR 1
AB 19
H 3
RBI 2
.700 OPS
AVG .300
OBP .300
SLG .400
HR 0
AB 10
H 3
RBI 1
.667 OPS
AVG .185
OBP .333
SLG .333
HR 1
AB 27
H 5
RBI 2
.629 OPS
AVG .143
OBP .200
SLG .429
HR 1
AB 14
H 2
RBI 1
.545 OPS
AVG .273
OBP .273
SLG .273
HR 0
AB 11
H 3
RBI 1
.478 OPS
AVG .133
OBP .278
SLG .200
HR 0
AB 15
H 2
RBI 0
.429 OPS
AVG .143
OBP .143
SLG .286
HR 1
AB 21
H 3
RBI 1
AVG .154
OBP .214
SLG .154
HR 0
AB 13
H 2
RBI 2
.273 OPS
AVG .136
OBP .136
SLG .136
HR 0
AB 22
H 3
RBI 3
.270 OPS
AVG .053
OBP .217
SLG .053
HR 0
AB 19
H 1
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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