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Will Nixon

#24Will Nixon

Will Nixon is a Pass-Catching Back for Syracuse.

What projects, and what doesn't · RBs · held out 2019-2025

How well one season predicts the next, measured on seasons the model never trained on. 1.00 would be perfectly predictable; 0.00 means last year told us nothing.

  • Usage share (volume)0.52
    Beats guessing the RB average by 18%. n=4,219 RB seasons
  • EPA per play (efficiency)0.10
    Not projectable — we do not forecast this. n=3,575 RB seasons
  • Total EPA (value)0.41
    Beats guessing the RB average by 9%. n=3,575 RB seasons

Across all positions, usage carries year to year at 0.47 and efficiency at 0.07. So Will Nixon's projection is a projection of opportunity — how much of the offense he runs through. How well he converts it is something this model does not claim to know a year in advance, and the number above is why.

2025 Production

Rushing
432 Rush yards3 Rush TD107 Carries4.0 Yards/carry
Receiving
24 Receptions173 Rec yards0 Rec TD7.2 Yards/rec
Returns
3 Kick returns37 KR yards0 KR TD

Performance Analysis · 2025 · vs RB peers

  • Efficiency0
  • Volume47
  • Explosiveness20
  • Consistency0
  • Receiving85
Player type
Pass-Catching Back

Third-down weapon out of the backfield. Routes, hands, and separation in coverage define this role as much as rushing.

3rd-down backReceiving threatPass protection
Peer percentiles
Opponent-adjusted EPA (WEPA/play)0th %ile · below avg
Game-to-game consistency0th %ile · below avg
Key findings
  • Below-average efficiency vs RB peers — value comes through volume, not per-play impact.
  • High game-to-game variance — boom-or-bust profile.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • Strong second-half surge — EPA/play improved 0.09 from the first to second half of the season.
  • Peak game: 0.55 EPA/play in Wk 11 vs Miami (SP+ 21).

NIL Market Tier· 2025

On3 valuation ↗
Contributor

Rotational contributor. Smaller collective or local deals.

Tier is a model estimate based on position, school brand, performance rank, and usage — not a reported deal. NIL deals are private. For a real market valuation, see On3's NIL profile, which factors in social following and actual deal tracking.

Game Log · box score + EPA, week by week

+0.5500.55Wk 1 vs Tennessee: +0.13 EPA/play1Wk 2 vs UConn: -0.08 EPA/play2Wk 3 vs Colgate: +0.11 EPA/play3Wk 4 vs Clemson: +0.24 EPA/play4Wk 5 vs Duke: -0.14 EPA/play5Wk 6 vs SMU: -0.31 EPA/play6Wk 8 vs Pittsburgh: -0.01 EPA/play8Wk 9 vs Georgia Tech: +0.01 EPA/play9Wk 10 vs North Carolina: +0.07 EPA/play10Wk 11 vs Miami: +0.55 EPA/play11Wk 13 vs Notre Dame: -0.21 EPA/play13Wk 14 vs Boston College: +0.07 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+CarRush YdsAvgRush TDRecRec YdsRec TDEPA/play
1vsTennesseeL26-4515.09333.7022900.13
2vsUConnW27-205.19303.306470-0.08
3vsColgateW66-2412665.510.11
4@ClemsonW34-219.510464.6132300.24
5vsDukeL3-386.67253.60-0.14
6@SMUL18-3113.47101.403250-0.31
8vsPittsburghL13-308.4591.80280-0.01
9@Georgia TechL16-419.36172.8121500.01
10vsNorth CarolinaL10-27-6.65295.801200.07
11@MiamiL10-3820.77618.701800.55
13@Notre DameL7-7024.414332.40210-0.21
14vsBoston CollegeL12-34-8.516734.6021500.07

Usage & Situational · Pro

Snap-share proxy
Overall
16.4%
Passing plays
7.7%
Rushing plays
26.0%
Standard downs
19.2%
Passing downs
10.4%
EPA by down type
Standard downs
-0.01
Passing downs
0.13
Pass / Rush EPA
0.27 / -0.06

Usage = share of team plays (CFBD has no true snap counts).

EPA = expected points added (opponent-adjusted). NIL estimates are model-based ranges, not reported deals. Data: CollegeFootballData. Not betting advice.