MLB Batting Splits 2025
Performance splits by handedness, home/away, and situational categories.
| Player | Team | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|
 |
52 | 10 | 2 | 6 | .192 | .232 | .327 | .559 | |
 |
76 | 10 | 4 | 10 | .132 | .241 | .316 | .557 | |
 |
67 | 13 | 2 | 5 | .194 | .257 | .299 | .555 | |
 |
97 | 19 | 2 | 7 | .196 | .225 | .330 | .555 | |
 |
34 | 6 | 1 | 4 | .176 | .231 | .324 | .554 | |
 |
68 | 13 | 1 | 7 | .191 | .304 | .250 | .554 | |
 |
92 | 20 | 1 | 10 | .217 | .260 | .293 | .553 | |
|
62 | 13 | 1 | 4 | .210 | .246 | .306 | .553 | |
 |
62 | 14 | 0 | 2 | .226 | .262 | .290 | .552 | |
|
42 | 6 | 2 | 3 | .143 | .265 | .286 | .551 | |
|
79 | 16 | 0 | 7 | .203 | .284 | .266 | .550 | |
  |
43 | 9 | 1 | 6 | .209 | .222 | .326 | .548 | |
 |
71 | 16 | 0 | 6 | .225 | .309 | .239 | .548 | |
  |
88 | 16 | 1 | 9 | .182 | .263 | .284 | .547 | |
 |
16 | 4 | 0 | 0 | .250 | .294 | .250 | .544 | |
|
56 | 13 | 0 | 0 | .232 | .259 | .286 | .544 | |
|
38 | 8 | 0 | 0 | .211 | .302 | .237 | .539 | |
 |
80 | 17 | 1 | 1 | .213 | .276 | .263 | .538 | |
 |
27 | 5 | 1 | 3 | .185 | .241 | .296 | .538 | |
|
46 | 8 | 1 | 2 | .174 | .255 | .283 | .538 | |
|
58 | 13 | 0 | 2 | .224 | .297 | .241 | .538 | |
|
45 | 8 | 0 | 3 | .178 | .315 | .222 | .537 | |
 |
58 | 13 | 1 | 6 | .224 | .224 | .310 | .534 | |
|
73 | 11 | 4 | 7 | .151 | .205 | .329 | .534 | |
 |
63 | 11 | 1 | 8 | .175 | .257 | .270 | .527 | |
|
94 | 19 | 0 | 8 | .202 | .240 | .287 | .527 | |
|
38 | 6 | 1 | 3 | .158 | .289 | .237 | .526 | |
|
74 | 16 | 0 | 4 | .216 | .272 | .243 | .515 | |
 |
75 | 14 | 2 | 10 | .187 | .218 | .293 | .511 | |
|
83 | 13 | 2 | 7 | .157 | .213 | .289 | .503 | |
|
29 | 5 | 0 | 0 | .172 | .294 | .207 | .501 | |
|
46 | 8 | 0 | 5 | .174 | .278 | .217 | .495 | |
|
71 | 14 | 0 | 3 | .197 | .284 | .211 | .495 | |
 |
70 | 13 | 0 | 8 | .186 | .234 | .257 | .491 | |
|
98 | 18 | 2 | 9 | .184 | .214 | .276 | .489 | |
|
16 | 3 | 0 | 1 | .188 | .235 | .250 | .485 | |
|
70 | 15 | 0 | 2 | .214 | .225 | .257 | .482 | |
|
83 | 16 | 1 | 6 | .193 | .200 | .277 | .477 | |
 |
28 | 3 | 0 | 4 | .107 | .297 | .179 | .476 | |
|
54 | 11 | 0 | 3 | .204 | .271 | .204 | .475 | |
 |
64 | 9 | 2 | 9 | .141 | .203 | .266 | .469 | |
|
38 | 7 | 1 | 2 | .184 | .205 | .263 | .468 | |
|
16 | 3 | 0 | 1 | .188 | .278 | .188 | .465 | |
|
28 | 6 | 0 | 2 | .214 | .207 | .250 | .457 | |
|
21 | 3 | 0 | 1 | .143 | .217 | .238 | .455 | |
|
63 | 8 | 2 | 6 | .127 | .214 | .238 | .452 | |
|
14 | 1 | 0 | 0 | .071 | .235 | .214 | .450 | |
|
36 | 6 | 0 | 2 | .167 | .250 | .194 | .444 | |
|
17 | 3 | 0 | 1 | .176 | .263 | .176 | .440 | |
|
29 | 4 | 1 | 6 | .138 | .188 | .241 | .429 |
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.