MLB Batting Splits 2025
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|---|
 |
September | 97 | 27 | 10 | 18 | .278 | .391 | .639 | 1.030 | |
 |
Last 7 Days | 23 | 8 | 1 | 3 | .348 | .464 | .565 | 1.030 | |
 |
August | 93 | 32 | 7 | 22 | .344 | .382 | .645 | 1.028 | |
 |
March | 13 | 3 | 2 | 6 | .231 | .333 | .692 | 1.026 | |
 |
Last 30 Days | 54 | 21 | 2 | 6 | .389 | .450 | .574 | 1.024 | |
|
Last 30 Days | 99 | 27 | 10 | 18 | .273 | .395 | .626 | 1.021 | |
 |
Last 15 Days | 36 | 9 | 5 | 6 | .250 | .325 | .694 | 1.019 | |
 |
September | 50 | 18 | 2 | 9 | .360 | .458 | .560 | 1.018 | |
 |
May | 106 | 35 | 7 | 23 | .330 | .410 | .604 | 1.014 | |
|
Last 15 Days | 24 | 7 | 2 | 7 | .292 | .346 | .667 | 1.013 | |
 |
Last 15 Days | 39 | 11 | 4 | 17 | .282 | .370 | .641 | 1.011 | |
|
Last 30 Days | 56 | 20 | 4 | 12 | .357 | .403 | .607 | 1.010 | |
|
Last 7 Days | 17 | 6 | 1 | 3 | .353 | .421 | .588 | 1.009 | |
  |
March | 13 | 4 | 1 | 1 | .308 | .471 | .538 | 1.009 | |
|
July | 90 | 33 | 4 | 17 | .367 | .408 | .600 | 1.008 | |
|
April | 67 | 19 | 8 | 15 | .284 | .351 | .657 | 1.008 | |
 |
August | 82 | 27 | 4 | 11 | .329 | .471 | .537 | 1.008 | |
 |
May | 95 | 33 | 6 | 18 | .347 | .407 | .600 | 1.007 | |
|
July | 99 | 32 | 8 | 20 | .323 | .350 | .657 | 1.006 | |
|
July | 99 | 33 | 7 | 24 | .333 | .387 | .616 | 1.004 | |
 |
Last 7 Days | 21 | 8 | 1 | 2 | .381 | .480 | .524 | 1.004 | |
 |
March | 15 | 6 | 0 | 0 | .400 | .471 | .533 | 1.004 | |
 |
March | 15 | 6 | 0 | 3 | .400 | .471 | .533 | 1.004 | |
|
Last 15 Days | 26 | 8 | 2 | 7 | .308 | .387 | .615 | 1.002 | |
 |
September | 33 | 10 | 3 | 5 | .303 | .395 | .606 | 1.001 | |
|
Last 30 Days | 33 | 10 | 3 | 5 | .303 | .395 | .606 | 1.001 | |
|
Last 7 Days | 19 | 8 | 0 | 3 | .421 | .421 | .579 | 1.000 | |
|
May | 10 | 2 | 2 | 2 | .200 | .200 | .800 | 1.000 | |
|
August | 14 | 4 | 1 | 3 | .286 | .500 | .500 | 1.000 | |
|
Last 7 Days | 14 | 5 | 0 | 2 | .357 | .500 | .500 | 1.000 | |
|
April | 14 | 6 | 0 | 1 | .429 | .429 | .571 | 1.000 | |
|
Last 7 Days | 12 | 4 | 1 | 3 | .333 | .333 | .667 | 1.000 | |
|
Last 30 Days | 51 | 18 | 2 | 9 | .353 | .450 | .549 | .999 | |
 |
March | 14 | 3 | 1 | 4 | .214 | .353 | .643 | .996 | |
|
May | 96 | 35 | 4 | 10 | .365 | .450 | .542 | .992 | |
|
July | 30 | 11 | 2 | 5 | .367 | .424 | .567 | .991 | |
|
Last 15 Days | 46 | 15 | 3 | 6 | .326 | .404 | .587 | .991 | |
|
June | 88 | 28 | 7 | 19 | .318 | .378 | .614 | .991 | |
|
August | 103 | 30 | 9 | 20 | .291 | .397 | .592 | .989 | |
|
Last 7 Days | 19 | 4 | 3 | 7 | .211 | .250 | .737 | .987 | |
|
June | 75 | 28 | 1 | 8 | .373 | .478 | .507 | .985 | |
|
June | 95 | 32 | 7 | 18 | .337 | .385 | .600 | .985 | |
|
September | 77 | 28 | 4 | 19 | .364 | .398 | .584 | .982 | |
|
April | 93 | 30 | 7 | 15 | .323 | .390 | .591 | .982 | |
|
May | 39 | 13 | 3 | 6 | .333 | .366 | .615 | .981 | |
|
July | 74 | 21 | 8 | 20 | .284 | .346 | .635 | .981 | |
|
March | 16 | 3 | 2 | 2 | .188 | .350 | .625 | .975 | |
|
May | 106 | 39 | 4 | 16 | .368 | .437 | .538 | .975 | |
|
August | 111 | 36 | 7 | 23 | .324 | .414 | .559 | .973 | |
  |
May | 13 | 4 | 1 | 1 | .308 | .357 | .615 | .973 |
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.