MLB Batting Splits 2026
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|---|
  |
April | 79 | 22 | 5 | 14 | .278 | .367 | .494 | .860 | |
  |
Last 7 Days | 22 | 7 | 1 | 4 | .318 | .360 | .500 | .860 | |
|
June | 100 | 29 | 5 | 20 | .290 | .330 | .530 | .860 | |
  |
July | 100 | 30 | 7 | 17 | .300 | .330 | .530 | .860 | |
  |
June | 89 | 26 | 4 | 14 | .292 | .388 | .472 | .860 | |
  |
Last 30 Days | 87 | 26 | 5 | 12 | .299 | .365 | .494 | .859 | |
  |
August | 74 | 24 | 2 | 15 | .324 | .359 | .500 | .859 | |
  |
July | 54 | 16 | 3 | 13 | .296 | .322 | .537 | .859 | |
  |
April | 93 | 22 | 7 | 16 | .237 | .343 | .516 | .859 | |
  |
Last 15 Days | 32 | 10 | 1 | 6 | .313 | .421 | .438 | .859 | |
  |
May | 101 | 27 | 6 | 17 | .267 | .353 | .505 | .858 | |
|
Last 30 Days | 71 | 21 | 4 | 8 | .296 | .351 | .507 | .858 | |
  |
Last 30 Days | 61 | 17 | 3 | 12 | .279 | .366 | .492 | .858 | |
  |
August | 84 | 27 | 2 | 11 | .321 | .370 | .488 | .858 | |
  |
August | 70 | 22 | 3 | 6 | .314 | .372 | .486 | .858 | |
|
May | 76 | 25 | 2 | 13 | .329 | .358 | .500 | .858 | |
  |
June | 97 | 33 | 2 | 12 | .340 | .363 | .495 | .858 | |
  |
July | 25 | 6 | 0 | 2 | .240 | .457 | .400 | .857 | |
|
July | 94 | 28 | 4 | 14 | .298 | .368 | .489 | .857 | |
  |
August | 105 | 33 | 3 | 14 | .314 | .333 | .524 | .857 | |
|
July | 12 | 3 | 0 | 1 | .250 | .357 | .500 | .857 | |
  |
Last 15 Days | 42 | 12 | 2 | 7 | .286 | .333 | .524 | .857 | |
|
August | 98 | 30 | 3 | 10 | .306 | .398 | .459 | .857 | |
|
September | 80 | 26 | 2 | 4 | .325 | .419 | .438 | .857 | |
  |
Last 30 Days | 106 | 31 | 3 | 18 | .292 | .356 | .500 | .856 |
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.