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Who has to play well

Analysis

Every other player number on this site is a level — yards, EPA, a projection. This one is a slope: how far a team’s win probability moves between one of its players having a bad day and a good one. Week 4, 58 games, 762 offensive players.

It is not a prediction that anybody will play well. Per-play efficiency barely carries from one season to the next, so we do not forecast a player’s level and this page never tries to. What it measures is how much it matters.

PositionAllQBRBWRTE
#PlayerWin prob. swing
1Kevin Roche Jr.TEGeorgia Tech at Stanford3.2
2Kyle FrendtTEWyoming vs Hawai'i2.8
3Rocky BeersTEOklahoma at Georgia2.4
4Kari AshleyTETCU at UCF2.3
5Brady CloughTEBoston College vs Virginia Tech2.2
6Mason MiniTECalifornia vs Clemson2.2
7Fabian RogoschTETroy at Utah State2.0
8Jayvontay ConnerTEVanderbilt at Auburn1.9
9Dorian FlemingTEMaryland vs UCLA1.8
10Jake WilsonTEWyoming vs Hawai'i1.8
11Tayvion GallowayTEMiddle Tennessee at Jacksonville State1.8
12Chris CorboTEGeorgia Tech at Stanford1.8
13Jamel HowseTEApp State at NC State1.8
14Cade KeithTENew Mexico at New Mexico State1.7
15Darrin FugittTEApp State at NC State1.7
16Tate HooverTEBall State at Kent State1.7
17Jamari HarroldTEKennesaw State at Arkansas State1.6
18Jeremiah ScobyTEBowling Green vs South Florida1.6
19Jayden SavouryTEMichigan State vs Nebraska1.5
20Benjamin BlackburnTEStanford vs Georgia Tech1.5
21Eric OlsenTEOregon State at UTEP1.4
22Caleb OdomTEOle Miss at Florida1.4
23DJ VonnahmeTEIowa at Michigan1.4
24Hayden HansenTEOklahoma at Georgia1.3
25Xavier WatsonTEUConn at Miami (OH)1.3
26Peter ClarkeTETemple vs Army1.3
27Garrett OakleyTEKansas State at Cincinnati1.2
28Elijah AlexanderTEAkron vs UNLV1.2
29Benjamin BrahmerTEPenn State vs Wisconsin1.2
30Jacob HarrisTEWisconsin at Penn State1.2
31Brett NorfleetTEMissouri at Mississippi State1.2
32Jason FowlerTENorthern Illinois at Georgia State1.2
33Noah BenneeTEUtah at Iowa State1.1
34Jaleel SkinnerTELouisville vs Wake Forest1.1
35Emaree WinstonTETexas at Tennessee1.1
36Devon TauaefaTEHawai'i at Wyoming1.1
37Luke ReynoldsTEVirginia Tech at Boston College1.1
38Keyan BurnettTEUNLV at Akron1.1
39Grant HollierTEGeorgia State vs Northern Illinois1.0
40Caden JensenTELouisiana at Charlotte1.0
41D.C. TempleTEOregon State at UTEP1.0
42Broderick PetersTESouthern Miss at Tulane1.0
43Carson KolbTEOklahoma State at West Virginia1.0
44Gavin GroverTECincinnati vs Kansas State1.0
45Mark BowmanTEUSC vs Oregon1.0
46Sam LeeTEToledo vs San Diego State0.9
47Addison OstrengaTEIowa at Michigan0.9
48Antonio JohnsonTEFlorida Atlantic at UL Monroe0.9
49Kamrean JohnsonTEWake Forest at Louisville0.9
50Kelsey JohnsonTELiberty at Coastal Carolina0.8
51Cash CheeksTEUTEP vs Oregon State0.8
52Jake JohnsonTEAuburn vs Vanderbilt0.8
53Jabari BushTEArkansas State vs Kennesaw State0.8
54Cyrus EllisonTECoastal Carolina vs Liberty0.8
55Scott Isacks IIITEUAB vs Navy0.8
56Micah Riley-DuckerTETexas A&M at LSU0.8
57Christian RossTEMiami (OH) vs UConn0.8
58Leon Haughton Jr.TEOld Dominion vs James Madison0.8
59Jaden PlattTEArkansas vs Tulsa0.8
60Ka'Morreun PimptonTETCU at UCF0.7
61Luke DehnickeTENorthwestern at Indiana0.7
62Willie RodriguezTEKentucky vs South Alabama0.7
63Brock ChappellTELouisiana at Charlotte0.7
64Cole RuskTEArizona at Washington State0.7
65Will AnciauxTEKansas State at Cincinnati0.7
66Dylan WadeTEUCF vs TCU0.7
67Cole KellerTEJames Madison at Old Dominion0.7
68Ja'Ricous HairstonTEVirginia Tech at Boston College0.7
69Ethan DavisTETennessee vs Texas0.7
70Jason JeffaresTECharlotte vs Louisiana0.6
71Ty LockwoodTEArkansas vs Tulsa0.6
72Elijah SessomsTEDelaware at Virginia0.6
73Reece AdkinsTEMassachusetts at Sacramento State0.6
74Baron NaoneTEWashington vs Minnesota0.5
75Pierce WalshTEMinnesota at Washington0.5
76Rod GibbsTESouth Alabama at Kentucky0.5
77Luke LindenmeyerTENebraska at Michigan State0.5
78Patrick OvermyerTEHouston at Georgia Southern0.5
79Christian BentancurTEClemson at California0.5
80Trey'Dez GreenTELSU vs Texas A&M0.5

How the number is built

Four steps. His expected production in this game, from his usage share, his team’s volume and the way volume swings with the score. Then his plausible range around it — the 25th to 75th percentile of what players at his volume actually produce against expectation, blended with his own record as he accumulates games. Then that range is converted to points of scoring margin by his share of his unit’s ordinary game-to-game swing. Then the game is re-simulated at both ends.

Why positions are comparable. Passing yards, carries and catches are never compared to each other. Each is converted into points of scoring margin and then into win probability inside the same game’s simulation, and the win-probability swing is what this page ranks. That is also why quarterbacks sit at the top: they are genuinely responsible for more of a passing game than any one receiver, not because their stat line is bigger.

What it does not cover

Offensive players only. There is no per-defender leverage model on this site yet, so no edge rusher or cornerback appears here. A board that ranked only offense while implying it ranked everybody would be the more misleading of the two options.

A running quarterback’s carries are scored with his passing, not with the run game, so a true dual-threat is understated. And team-mates’ production is treated as independent when it partly is not — targets moving between two receivers is noise that cancels for the offense as a whole, which leaves the receiving side slightly overstated against the thrower.

FBS against FBS only. Rebuilt weekly; this board was generated 2026-09-25.