Player stats

Advanced stats from every play: EPA (expected points added), success rate, CPOE and more, by player. The leaders below use a qualifying bar (PFR's: 14 dropbacks, 6.25 carries or 1.875 targets per team game). Click any name for that player's full profile, or open the explorer to cut the plays any way you like.

Season leaders

Splits that hold up

Most situational splits don't repeat: a player's gap between, say, blitzed and not blitzed one season predicts almost nothing about the next. These are the exceptions: splits where the same player's edge over the league carried over from one season to the next (2016–25, correlation r with its 95% interval clear of zero). They're the splits most worth reading as skill. How we tested it.

Biggest swings this season

The largest gaps between a player in one situation and the same player everywhere else, beyond the gap the whole league shows there. This is the kind of stat that makes a highlight clip. Read these as stories, not traits: we checked 11,121 player splits and 194 cleared |z| ≥ 2.5. Pure chance would produce about 138. That's more than luck alone, but chance still explains most of them. The badge says how much that kind of split repeats from one season to the next.

• Josh Palmer BUF: +1.23 EPA/target between his own 21 and 50, vs -0.81 the rest of the time. mostly noise · r 0.04 18 vs 19 targets · league gap -0.00 · z = +4.0 · compare everyone
• Tee Higgins CIN: -0.40 EPA/target on short throws, vs +0.95 the rest of the time. mostly noise · r 0.09 43 vs 55 targets · league gap -0.10 · z = -4.0 · compare everyone
• Lamar Jackson BAL: +0.60 EPA/dropback between the opponent's 21 and 49, vs -0.10 the rest of the time. mostly noise · r 0.08 99 vs 267 dropbacks · league gap +0.04 · z = +3.9 · compare everyone
• Jauan Jennings SF: +0.71 EPA/target on 3rd down, vs -0.48 the rest of the time. mostly noise · r -0.02 35 vs 55 targets · league gap -0.08 · z = +3.8 · compare everyone
• Sam Darnold SEA: +0.72 EPA/dropback on 3rd & 4–6, vs -0.38 the rest of the time. mostly noise · r -0.12 37 vs 99 dropbacks · league gap +0.06 · z = +3.7 · compare everyone
• Noah Fant CIN: -1.43 EPA/target against Cover 2, vs +0.44 the rest of the time. mostly noise · r -0.09 16 vs 25 targets · league gap -0.07 · z = -3.6 · compare everyone
• Justin Fields NYJ: +0.24 EPA/dropback with win probability under 20%, vs -0.29 the rest of the time. mostly noise · r 0.05 115 vs 142 dropbacks · league gap -0.12 · z = +3.5 · compare everyone
• Drake London ATL: +1.15 EPA/target against Cover 2, vs -0.04 the rest of the time. mostly noise · r -0.09 24 vs 88 targets · league gap -0.07 · z = +3.5 · compare everyone
• Tetairoa McMillan CAR: -0.73 EPA/target on 4–6 to go, vs +0.44 the rest of the time. mostly noise · r 0.02 24 vs 98 targets · league gap +0.05 · z = -3.4 · compare everyone
• Joe Flacco CIN: -0.81 EPA/dropback when holding the ball 3.5s+, vs +0.11 the rest of the time. mostly noise · r 0.07 49 vs 363 dropbacks · league gap -0.17 · z = -3.4 · compare everyone
• Geno Smith LV: +0.27 EPA/dropback from a clean pocket, vs -0.92 otherwise. mostly noise · r 0.04 346 vs 173 dropbacks · league gap +0.73 · z = +3.4 · compare everyone
• DJ Moore CHI: +1.14 EPA/target under pressure, vs -0.05 otherwise. mostly noise · r 0.01 15 vs 70 targets · league gap -0.30 · z = +3.4 · compare everyone

Where this comes from. nflverse play-by-play (rebuilt daily), FTN charting for play action, pocket, blitz, box count, screens, motion and RPOs (2022 on), and NFL Next Gen Stats participation data for pressure, coverage and time to throw (2016–2025; not published for 2026 yet). EPA per play is noisy, about ±1.4 points a play, so 100 plays still carry roughly ±0.14 of luck. Box-score totals are checked against ESPN after every rebuild: see the check.