MLB Batting Splits 2026
Performance splits by handedness, home/away, and situational categories.
| Player | Team | Split | AB | H | HR | RBI | AVG | OBP | SLG | OPS ▼ |
|---|---|---|---|---|---|---|---|---|---|---|
  |
None On | 318 | 75 | 4 | 4 | .236 | .374 | .324 | .698 | |
  |
Lead Off Inning | 35 | 9 | 1 | 1 | .257 | .297 | .400 | .697 | |
  |
None On | 14 | 4 | 0 | 0 | .286 | .412 | .286 | .697 | |
  |
None On | 215 | 47 | 10 | 10 | .219 | .288 | .409 | .697 | |
  |
Runners On | 121 | 30 | 3 | 24 | .248 | .300 | .397 | .697 | |
  |
Scoring Position | 154 | 36 | 6 | 58 | .234 | .301 | .396 | .697 | |
  |
Scoring Position | 11 | 4 | 0 | 5 | .364 | .333 | .364 | .697 | |
  |
None On | 128 | 33 | 2 | 2 | .258 | .354 | .344 | .697 | |
|
None On | 325 | 73 | 10 | 10 | .225 | .319 | .378 | .697 | |
|
Runners On | 151 | 32 | 8 | 29 | .212 | .292 | .404 | .696 | |
  |
Runners On | 151 | 40 | 3 | 35 | .265 | .331 | .364 | .696 | |
  |
Lead Off Inning | 99 | 25 | 3 | 3 | .253 | .302 | .394 | .696 | |
|
None On | 82 | 20 | 2 | 2 | .244 | .354 | .341 | .696 | |
  |
Lead Off Inning | 96 | 21 | 3 | 3 | .219 | .342 | .354 | .696 | |
  |
None On | 376 | 82 | 16 | 16 | .218 | .297 | .399 | .696 | |
  |
Runners On | 23 | 7 | 0 | 8 | .304 | .304 | .391 | .696 | |
  |
Runners On | 246 | 60 | 4 | 54 | .244 | .338 | .358 | .696 | |
  |
Lead Off Inning | 49 | 13 | 1 | 1 | .265 | .308 | .388 | .695 | |
|
Lead Off Inning | 138 | 35 | 3 | 3 | .254 | .318 | .377 | .695 | |
|
Lead Off Inning | 55 | 12 | 3 | 4 | .218 | .259 | .436 | .695 | |
  |
Lead Off Inning | 34 | 9 | 1 | 1 | .265 | .342 | .353 | .695 | |
|
Runners On | 81 | 20 | 3 | 22 | .247 | .287 | .407 | .695 | |
|
None On | 239 | 49 | 13 | 13 | .205 | .272 | .423 | .695 | |
|
None On | 336 | 89 | 7 | 7 | .265 | .308 | .387 | .695 | |
|
Runners On | 268 | 57 | 13 | 71 | .213 | .277 | .418 | .695 |
Understanding Situational Splits
Situational splits capture a hitter's performance in high-leverage game contexts — runners in scoring position (RISP), two-out situations, and clutch at-bats. These splits reveal which hitters elevate their game when it matters most.
RISP (Runners in Scoring Position)
RISP splits show how a hitter performs with runners on 2nd and/or 3rd. Some hitters elevate with RISP while others tighten up. For prop betting, high RISP splits indicate a hitter who thrives under pressure and may exceed their base projections in run-producing situations.
Two-Out Situations
Two-out hitting is a specific skill. Hitters who maintain high averages with 2 outs extend innings and create run-scoring opportunities. The "scoring position, 2 out" split is the ultimate clutch metric — it captures rally-extending at-bats under maximum pressure.
DFS & Betting Value
Situational splits help identify "clutch" hitters whose RBI and run totals outpace their overall stat line. A hitter with elite RISP splits batting 4th or 5th in a potent lineup is a prime RBI prop target. These splits also help explain why some hitters consistently outperform their projections.
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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
Is clutch hitting a real skill?
- This is debated, but the evidence suggests that while most clutch performance is random variation, some hitters do have a repeatable ability to perform in high-leverage situations. Hitters with consistently high RISP splits across multiple seasons are more likely to have a real skill than those with one hot year.
How do I use RISP splits for prop betting?
- Target hitters with strong RISP splits for RBI props, especially when they bat in the middle of a potent lineup. If the lineup around them gets on base frequently, a high-RISP hitter will have more opportunities to drive in runs. Combine with the opposing pitcher's RISP-allowed stats for the clearest edge.
What is the "scoring position, 2 out" split?
- This is arguably the highest-pressure regular-season at-bat situation — runners on 2nd/3rd with 2 outs. Hitters who thrive here extend innings and produce outsized run totals. It's a small-sample split, so look for consistency across seasons rather than relying on one year's data.