MLB Batting Splits 2026
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|---|
  |
May | 108 | 33 | 2 | 15 | .306 | .375 | .426 | .801 | |
  |
July | 77 | 18 | 4 | 7 | .234 | .372 | .429 | .801 | |
  |
Last 15 Days | 12 | 4 | 0 | 1 | .333 | .385 | .417 | .801 | |
  |
Last 7 Days | 22 | 5 | 1 | 2 | .227 | .346 | .455 | .801 | |
  |
Last 30 Days | 97 | 29 | 5 | 14 | .299 | .317 | .485 | .801 | |
  |
August | 76 | 18 | 4 | 15 | .237 | .341 | .461 | .801 | |
|
Last 30 Days | 12 | 4 | 0 | 1 | .333 | .385 | .417 | .801 | |
|
July | 86 | 26 | 2 | 9 | .302 | .371 | .430 | .801 | |
|
September | 12 | 4 | 0 | 1 | .333 | .385 | .417 | .801 | |
  |
Last 15 Days | 41 | 11 | 1 | 3 | .268 | .362 | .439 | .801 | |
  |
July | 30 | 8 | 0 | 5 | .267 | .333 | .467 | .800 | |
|
March | 20 | 6 | 1 | 2 | .300 | .300 | .500 | .800 | |
|
May | 96 | 27 | 3 | 10 | .281 | .352 | .448 | .800 | |
|
Last 15 Days | 51 | 16 | 0 | 8 | .314 | .368 | .431 | .800 | |
  |
March | 10 | 2 | 1 | 1 | .200 | .200 | .600 | .800 | |
  |
Last 7 Days | 10 | 2 | 1 | 1 | .200 | .200 | .600 | .800 | |
  |
July | 89 | 23 | 5 | 9 | .258 | .305 | .494 | .800 | |
  |
May | 73 | 18 | 4 | 13 | .247 | .321 | .479 | .800 | |
  |
June | 15 | 4 | 1 | 4 | .267 | .267 | .533 | .800 | |
  |
September | 69 | 19 | 2 | 10 | .275 | .351 | .449 | .800 | |
|
Last 15 Days | 20 | 4 | 2 | 7 | .200 | .200 | .600 | .800 | |
  |
September | 12 | 4 | 0 | 1 | .333 | .467 | .333 | .800 | |
|
Last 30 Days | 12 | 4 | 0 | 1 | .333 | .467 | .333 | .800 | |
  |
Last 30 Days | 91 | 23 | 3 | 13 | .253 | .349 | .451 | .800 | |
  |
September | 94 | 25 | 5 | 17 | .266 | .320 | .479 | .799 |
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.