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 | 24 | 6 | 1 | 3 | .250 | .280 | .375 | .655 | |
  |
Last 30 Days | 84 | 18 | 3 | 6 | .214 | .298 | .357 | .655 | |
  |
September | 28 | 8 | 0 | 2 | .286 | .333 | .321 | .655 | |
  |
March | 15 | 3 | 0 | 0 | .200 | .455 | .200 | .655 | |
  |
Last 30 Days | 51 | 12 | 1 | 4 | .235 | .322 | .333 | .655 | |
|
August | 82 | 18 | 3 | 7 | .220 | .301 | .354 | .655 | |
  |
September | 66 | 13 | 1 | 7 | .197 | .321 | .333 | .654 | |
  |
Last 30 Days | 48 | 13 | 1 | 2 | .271 | .300 | .354 | .654 | |
|
April | 74 | 16 | 3 | 6 | .216 | .289 | .365 | .654 | |
  |
July | 86 | 21 | 1 | 9 | .244 | .293 | .360 | .654 | |
  |
June | 69 | 12 | 5 | 11 | .174 | .219 | .435 | .654 | |
  |
Last 30 Days | 78 | 18 | 3 | 8 | .231 | .295 | .359 | .654 | |
|
May | 106 | 23 | 5 | 18 | .217 | .239 | .415 | .654 | |
  |
July | 72 | 19 | 0 | 4 | .264 | .321 | .333 | .654 | |
  |
August | 38 | 8 | 1 | 3 | .211 | .286 | .368 | .654 | |
  |
June | 16 | 4 | 0 | 2 | .250 | .278 | .375 | .653 | |
  |
July | 33 | 6 | 2 | 5 | .182 | .289 | .364 | .653 | |
  |
August | 104 | 28 | 2 | 12 | .269 | .278 | .375 | .653 | |
  |
July | 39 | 9 | 0 | 1 | .231 | .268 | .385 | .653 | |
  |
August | 31 | 6 | 2 | 2 | .194 | .265 | .387 | .652 | |
|
September | 76 | 14 | 4 | 6 | .184 | .271 | .382 | .652 | |
|
Last 15 Days | 56 | 13 | 2 | 5 | .232 | .295 | .357 | .652 | |
  |
July | 91 | 25 | 0 | 4 | .275 | .333 | .319 | .652 | |
|
April | 95 | 25 | 0 | 2 | .263 | .336 | .316 | .652 | |
  |
Last 30 Days | 35 | 6 | 1 | 4 | .171 | .310 | .343 | .652 |
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.