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 | 26 | 3 | 1 | 4 | .115 | .179 | .231 | .409 | |
 |
Last 7 Days | 22 | 4 | 0 | 0 | .182 | .182 | .227 | .409 | |
 |
July | 50 | 7 | 1 | 5 | .140 | .189 | .220 | .409 | |
  |
April | 20 | 2 | 0 | 2 | .100 | .308 | .100 | .408 | |
 |
March | 10 | 1 | 0 | 2 | .100 | .308 | .100 | .408 | |
|
September | 31 | 4 | 1 | 2 | .129 | .182 | .226 | .408 | |
 |
Last 7 Days | 27 | 4 | 1 | 2 | .148 | .148 | .259 | .407 | |
  |
April | 44 | 6 | 0 | 2 | .136 | .269 | .136 | .406 | |
|
Last 15 Days | 42 | 7 | 0 | 0 | .167 | .239 | .167 | .406 | |
 |
June | 43 | 4 | 1 | 3 | .093 | .220 | .186 | .406 | |
|
Last 15 Days | 44 | 5 | 1 | 3 | .114 | .200 | .205 | .405 | |
|
Last 15 Days | 35 | 4 | 0 | 3 | .114 | .205 | .200 | .405 | |
 |
May | 40 | 5 | 1 | 1 | .125 | .205 | .200 | .405 | |
|
April | 66 | 8 | 1 | 5 | .121 | .237 | .167 | .404 | |
 |
August | 65 | 9 | 1 | 3 | .138 | .188 | .215 | .404 | |
 |
August | 59 | 9 | 1 | 3 | .153 | .167 | .237 | .404 | |
 |
May | 80 | 11 | 1 | 6 | .138 | .216 | .188 | .403 | |
|
March | 10 | 2 | 0 | 1 | .200 | .200 | .200 | .400 | |
|
April | 30 | 5 | 0 | 1 | .167 | .167 | .233 | .400 | |
|
March | 17 | 3 | 0 | 0 | .176 | .222 | .176 | .399 | |
|
September | 61 | 8 | 1 | 7 | .131 | .185 | .213 | .398 | |
 |
May | 19 | 2 | 0 | 1 | .105 | .292 | .105 | .397 | |
|
April | 81 | 14 | 0 | 7 | .173 | .198 | .198 | .395 | |
 |
March | 14 | 2 | 0 | 0 | .143 | .250 | .143 | .393 | |
|
March | 14 | 2 | 0 | 0 | .143 | .250 | .143 | .393 | |
 |
Last 15 Days | 47 | 7 | 0 | 4 | .149 | .180 | .213 | .393 | |
 |
Last 30 Days | 25 | 4 | 0 | 3 | .160 | .192 | .200 | .392 | |
 |
May | 28 | 3 | 0 | 3 | .107 | .212 | .179 | .391 | |
|
Last 30 Days | 48 | 7 | 1 | 3 | .146 | .180 | .208 | .388 | |
|
August | 15 | 2 | 0 | 1 | .133 | .188 | .200 | .388 | |
|
Last 30 Days | 15 | 2 | 0 | 1 | .133 | .188 | .200 | .388 | |
|
June | 37 | 6 | 0 | 3 | .162 | .225 | .162 | .387 | |
 |
June | 41 | 7 | 0 | 2 | .171 | .190 | .195 | .386 | |
|
April | 10 | 1 | 0 | 1 | .100 | .286 | .100 | .386 | |
|
Last 15 Days | 13 | 1 | 1 | 4 | .077 | .077 | .308 | .385 | |
|
July | 13 | 1 | 1 | 2 | .077 | .077 | .308 | .385 | |
|
July | 31 | 5 | 0 | 1 | .161 | .188 | .194 | .381 | |
|
Last 15 Days | 52 | 9 | 0 | 4 | .173 | .189 | .192 | .381 | |
|
Last 30 Days | 50 | 7 | 0 | 0 | .140 | .218 | .160 | .378 | |
|
September | 50 | 7 | 0 | 0 | .140 | .218 | .160 | .378 | |
|
Last 15 Days | 18 | 3 | 0 | 3 | .167 | .211 | .167 | .377 | |
|
April | 23 | 2 | 1 | 2 | .087 | .160 | .217 | .377 | |
|
June | 18 | 3 | 0 | 0 | .167 | .211 | .167 | .377 | |
|
Last 7 Days | 18 | 3 | 0 | 0 | .167 | .211 | .167 | .377 | |
|
Last 30 Days | 41 | 7 | 0 | 4 | .171 | .205 | .171 | .375 | |
|
June | 18 | 2 | 0 | 1 | .111 | .261 | .111 | .372 | |
|
March | 13 | 1 | 0 | 0 | .077 | .294 | .077 | .371 | |
|
April | 91 | 12 | 0 | 3 | .132 | .216 | .154 | .370 | |
|
Last 7 Days | 13 | 2 | 0 | 3 | .154 | .214 | .154 | .368 | |
|
July | 72 | 11 | 1 | 5 | .153 | .173 | .194 | .368 |
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.