MLB Batting Splits 2026
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|---|
  |
Last 15 Days | 39 | 11 | 3 | 7 | .282 | .326 | .615 | .941 | |
  |
July | 89 | 26 | 7 | 19 | .292 | .323 | .618 | .941 | |
  |
Last 15 Days | 41 | 13 | 0 | 4 | .317 | .429 | .512 | .941 | |
  |
August | 12 | 3 | 1 | 3 | .250 | .357 | .583 | .940 | |
  |
Last 15 Days | 36 | 12 | 2 | 4 | .333 | .385 | .556 | .940 | |
  |
June | 89 | 28 | 5 | 20 | .315 | .388 | .551 | .939 | |
  |
April | 38 | 13 | 1 | 5 | .342 | .413 | .526 | .939 | |
  |
April | 90 | 25 | 8 | 10 | .278 | .350 | .589 | .939 | |
  |
Last 7 Days | 14 | 5 | 0 | 0 | .357 | .438 | .500 | .938 | |
|
July | 91 | 25 | 6 | 21 | .275 | .389 | .549 | .938 | |
|
April | 62 | 20 | 3 | 9 | .323 | .373 | .565 | .938 | |
  |
March | 16 | 7 | 0 | 0 | .438 | .438 | .500 | .938 | |
|
August | 78 | 23 | 4 | 13 | .295 | .451 | .487 | .938 | |
  |
May | 90 | 22 | 8 | 18 | .244 | .382 | .556 | .937 | |
  |
Last 15 Days | 45 | 15 | 1 | 9 | .333 | .426 | .511 | .937 | |
  |
Last 30 Days | 60 | 19 | 2 | 15 | .317 | .419 | .517 | .936 | |
|
March | 21 | 7 | 1 | 4 | .333 | .364 | .571 | .935 | |
  |
September | 61 | 15 | 6 | 15 | .246 | .361 | .574 | .935 | |
  |
March | 21 | 8 | 0 | 4 | .381 | .458 | .476 | .935 | |
|
May | 41 | 12 | 4 | 13 | .293 | .326 | .610 | .935 | |
|
Last 15 Days | 43 | 13 | 2 | 8 | .302 | .400 | .535 | .935 | |
|
Last 30 Days | 104 | 28 | 9 | 18 | .269 | .347 | .587 | .934 | |
|
Last 15 Days | 46 | 10 | 4 | 12 | .217 | .368 | .565 | .934 | |
  |
June | 93 | 25 | 7 | 20 | .269 | .352 | .581 | .933 | |
|
May | 96 | 30 | 3 | 19 | .313 | .422 | .510 | .933 |
Understanding Monthly Splits
Monthly splits track a hitter's performance across the season. April through October each bring different conditions — weather, fatigue, roster composition, and pitcher workload all shift as the season progresses. Identifying hot and cold streaks is essential for in-season DFS and betting.
Early Season (March-April)
Cold weather suppresses offense league-wide. Pitchers are often fresher and throwing harder. Small sample sizes make early-season splits volatile — a 10-game hot streak in April can produce a misleading .400 AVG. Weight these splits cautiously until June.
Peak Season (May-August)
Warm weather boosts offense, and sample sizes become meaningful. By July, monthly splits reveal real trends — a hitter who consistently rakes in summer months is a reliable warm-weather producer. August fatigue can affect some players, especially catchers and older veterans.
Stretch Run (September-October)
September roster expansions change matchup dynamics. October splits only apply to playoff teams. For DFS and betting, September splits are useful for identifying hitters who finish strong under pressure — these "second-half" hitters are often undervalued by the market.
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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
Are monthly batting splits predictive?
- Monthly splits are more descriptive than predictive for individual months. However, consistent patterns across multiple seasons (e.g., a hitter who always rakes in July-August) can signal real tendencies. Use monthly splits to identify hot streaks and cold spells within the current season rather than predicting future months.
Why do hitters perform differently by month?
- Weather is the biggest factor — cold April air suppresses fly balls, while summer heat helps the ball carry. Pitcher fatigue accumulates over the season, often boosting hitter stats in August-September. Some hitters also have personal patterns tied to conditioning, injury history, or mechanical adjustments.
How should I use monthly splits for DFS?
- Use current-month splits to identify who is hot right now. A hitter slashing .350/.400/.600 in the current month is likely seeing the ball well and making hard contact. Combine monthly form with matchup data for the strongest DFS plays. Don't chase month-old hot streaks that have already cooled.