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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
1Tiaquelin MimsWRUAB vs Navy4.8
2Jesse LegreeWROregon State at UTEP4.8
3Cam'Ron LacyWRMiddle Tennessee at Jacksonville State4.5
4TK KeyesWRTroy at Utah State4.2
5Jordan AllenWRGeorgia Tech at Stanford4.2
6Audric HarrisWRHawai'i at Wyoming4.1
7Kainoa CarvalhoWRHawai'i at Wyoming4.0
8Tama UiliataWRHawai'i at Wyoming3.9
9Easton MesserWRFlorida Atlantic at UL Monroe3.8
10Ryan WingoWRTexas at Tennessee3.7
11EJ ReidWRUAB vs Navy3.6
12Hunter SummersWRArkansas State vs Kennesaw State3.6
13Darius CopelandWRLiberty at Coastal Carolina3.6
14Markus AllenWRMiddle Tennessee at Jacksonville State3.6
15Isaiah SategnaWROklahoma at Georgia3.5
16Makai JacksonWRLiberty at Coastal Carolina3.4
17Mario CraverWRTexas A&M at LSU3.4
18Chase HendricksWRCalifornia vs Clemson3.3
19John MontagueWRBoston College vs Virginia Tech3.2
20C.J. SmithWRUAB vs Navy3.1
21Justin BowickWROklahoma State at West Virginia3.0
22Wyatt YoungWROklahoma State at West Virginia3.0
23Trell HarrisWROklahoma at Georgia2.9
24Caden HighWRStanford vs Georgia Tech2.8
25Onterrio Smith Jr.WRSacramento State vs Massachusetts2.8
26Brendan JenkinsWRSouth Alabama at Kentucky2.7
27Na'eem Abdul-Rahim GladdingWRMaryland vs UCLA2.6
28Akeem WrightWRBoise State at Western Michigan2.6
29Sean WilsonWRDelaware at Virginia2.6
30Jeremiah KogerWRAuburn vs Vanderbilt2.6
31Cayden LeeWRMissouri at Mississippi State2.5
32Damarion WittenWRMiami (OH) vs UConn2.5
33Jaden BrayWRWest Virginia vs Oklahoma State2.5
34Joseph Griffin Jr.WRMassachusetts at Sacramento State2.5
35Tyrell HenryWRWisconsin at Penn State2.4
36Oran Singleton Jr.WRTulsa at Arkansas2.4
37Ashton HollinsWRGeorgia Southern vs Houston2.4
38Howard KinchenWRTroy at Utah State2.4
39Maleek HugginsWRMiami (OH) vs UConn2.4
40Rasean JonesWRBoise State at Western Michigan2.4
41Parker FulghumWRUL Monroe vs Florida Atlantic2.3
42Kelby ValsinWRFlorida Atlantic at UL Monroe2.3
43Javarius GreenWRBoston College vs Virginia Tech2.3
44Jacory Barney Jr.WRNebraska at Michigan State2.3
45Chauncy CobbWRArkansas State vs Kennesaw State2.3
46Carlos HernandezWRWake Forest at Louisville2.2
47Ty HardingWRMassachusetts at Sacramento State2.2
48Dawson PoughWRBoston College vs Virginia Tech2.2
49Andrew MarshWRMichigan vs Iowa2.2
50Josh RodriguezWROld Dominion vs James Madison2.2
51Chris Durr Jr.WRMaryland vs UCLA2.2
52Neo CliftonWRMiddle Tennessee at Jacksonville State2.2
53Gentz HilburnWRAkron vs UNLV2.2
54Bailen GeorgeWRNew Mexico at New Mexico State2.1
55DJ EppsWRWest Virginia vs Oklahoma State2.1
56Jack FoleyWRWake Forest at Louisville2.1
57Tyler KingWRNew Mexico State vs New Mexico2.1
58Dalen PensonWRGeorgia Tech at Stanford2.1
59Jamarion McDougleWRBall State at Kent State2.0
60Traylon RayWROle Miss at Florida2.0
61Isaiah ThackerWRBall State at Kent State2.0
62Emmett Mosley VWRTexas at Tennessee2.0
63Mikey MatthewsWRUCLA at Maryland2.0
64Cam ColemanWRTexas at Tennessee2.0
65Matt LongWRAir Force at Nevada2.0
66Jonanthony HallWRStanford vs Georgia Tech2.0
67JJ BuchananWRMichigan vs Iowa1.9
68Matthew ColemanWRSacramento State vs Massachusetts1.9
69Jaylen HamptonWRCharlotte vs Louisiana1.9
70Donovan OlugbodeWRMissouri at Mississippi State1.9
71Jimmy CallowayWRTulsa at Arkansas1.9
72Semaj MorganWRUCLA at Maryland1.9
73Javon BrownWRUConn at Miami (OH)1.9
74Javon RobinsonWRUtah State vs Troy1.9
75Zach MundellWRArmy at Temple1.9
76Kaleb WebbWRMaryland vs UCLA1.8
77Jamari PersonWRLiberty at Coastal Carolina1.8
78Jaron TibbsWRKansas State at Cincinnati1.8
79Jaden BarnesWRCharlotte vs Louisiana1.8
80Javon RossWRTulsa at Arkansas1.8

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.