MLB Batting Splits 2026
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|---|
  |
June | 92 | 18 | 6 | 14 | .196 | .260 | .413 | .673 | |
  |
Last 30 Days | 10 | 3 | 0 | 1 | .300 | .273 | .400 | .673 | |
  |
April | 81 | 21 | 1 | 13 | .259 | .291 | .383 | .673 | |
  |
September | 50 | 10 | 2 | 2 | .200 | .273 | .400 | .673 | |
  |
August | 58 | 12 | 2 | 4 | .207 | .277 | .397 | .673 | |
|
September | 10 | 3 | 0 | 1 | .300 | .273 | .400 | .673 | |
  |
August | 104 | 25 | 2 | 12 | .240 | .307 | .365 | .672 | |
|
April | 75 | 16 | 1 | 4 | .213 | .352 | .320 | .672 | |
|
Last 15 Days | 34 | 7 | 1 | 3 | .206 | .289 | .382 | .672 | |
  |
August | 103 | 21 | 5 | 12 | .204 | .255 | .417 | .672 | |
  |
Last 30 Days | 86 | 19 | 3 | 10 | .221 | .277 | .395 | .672 | |
  |
Last 30 Days | 105 | 25 | 2 | 7 | .238 | .310 | .362 | .672 | |
  |
August | 32 | 7 | 2 | 5 | .219 | .265 | .406 | .671 | |
  |
September | 61 | 14 | 3 | 9 | .230 | .262 | .410 | .671 | |
  |
August | 93 | 21 | 4 | 16 | .226 | .284 | .387 | .671 | |
|
Last 30 Days | 64 | 15 | 3 | 10 | .234 | .265 | .406 | .671 | |
|
Last 30 Days | 82 | 17 | 4 | 14 | .207 | .244 | .427 | .671 | |
|
June | 76 | 17 | 3 | 7 | .224 | .289 | .382 | .671 | |
|
June | 36 | 8 | 2 | 4 | .222 | .282 | .389 | .671 | |
  |
Last 15 Days | 38 | 9 | 1 | 8 | .237 | .302 | .368 | .671 | |
  |
May | 103 | 23 | 4 | 10 | .223 | .252 | .417 | .670 | |
|
Last 7 Days | 25 | 5 | 1 | 2 | .200 | .310 | .360 | .670 | |
|
May | 56 | 14 | 1 | 7 | .250 | .313 | .357 | .670 | |
  |
July | 75 | 18 | 1 | 9 | .240 | .296 | .373 | .670 | |
|
June | 97 | 24 | 3 | 19 | .247 | .288 | .381 | .670 |
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.