MLB Batting Splits 2026
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|---|
  |
August | 66 | 15 | 1 | 9 | .227 | .325 | .333 | .658 | |
  |
September | 32 | 8 | 1 | 5 | .250 | .314 | .344 | .658 | |
  |
April | 36 | 9 | 1 | 1 | .250 | .325 | .333 | .658 | |
  |
June | 102 | 20 | 6 | 10 | .196 | .274 | .382 | .657 | |
  |
April | 38 | 9 | 0 | 4 | .237 | .341 | .316 | .657 | |
  |
Last 15 Days | 41 | 9 | 2 | 4 | .220 | .267 | .390 | .657 | |
  |
August | 90 | 22 | 2 | 8 | .244 | .324 | .333 | .657 | |
  |
September | 46 | 10 | 2 | 7 | .217 | .265 | .391 | .657 | |
|
Last 30 Days | 44 | 10 | 1 | 4 | .227 | .271 | .386 | .657 | |
  |
September | 72 | 16 | 3 | 12 | .222 | .296 | .361 | .657 | |
  |
Last 30 Days | 88 | 19 | 4 | 11 | .216 | .271 | .386 | .657 | |
|
June | 81 | 17 | 4 | 13 | .210 | .275 | .383 | .657 | |
  |
May | 98 | 21 | 3 | 9 | .214 | .300 | .357 | .657 | |
  |
Last 30 Days | 56 | 16 | 0 | 7 | .286 | .318 | .339 | .657 | |
|
June | 101 | 23 | 4 | 14 | .228 | .271 | .386 | .657 | |
  |
Last 30 Days | 50 | 12 | 1 | 3 | .240 | .296 | .360 | .656 | |
|
Last 30 Days | 81 | 22 | 0 | 10 | .272 | .323 | .333 | .656 | |
|
Last 7 Days | 23 | 5 | 1 | 2 | .217 | .308 | .348 | .656 | |
|
August | 89 | 20 | 5 | 14 | .225 | .263 | .393 | .656 | |
  |
April | 27 | 7 | 0 | 2 | .259 | .286 | .370 | .656 | |
  |
August | 31 | 9 | 0 | 2 | .290 | .333 | .323 | .656 | |
  |
April | 35 | 8 | 0 | 1 | .229 | .341 | .314 | .656 | |
  |
August | 85 | 21 | 2 | 9 | .247 | .326 | .329 | .656 | |
|
Last 15 Days | 21 | 4 | 1 | 2 | .190 | .227 | .429 | .656 | |
|
July | 76 | 17 | 2 | 7 | .224 | .326 | .329 | .655 |
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.