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Jordan Napier

#2Jordan Napier

Jordan Napier is a Versatile WR for San Diego State. Jordan's 2025 season ranks in the 100th percentile nationally by opponent-adjusted EPA per play across 71 plays — a elite rate for the WR.

What projects, and what doesn't · WRs · 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)0.47
    Beats guessing the WR average by 16%. n=6,302 WR seasons
  • EPA per play (efficiency)0.09
    Not projectable — we do not forecast this. n=5,767 WR seasons
  • Total EPA (value)0.45
    Beats guessing the WR average by 12%. n=5,767 WR seasons

Across all positions, usage carries year to year at 0.47 and efficiency at 0.07. So Jordan Napier'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
40 Rush yards1 Rush TD11 Carries3.6 Yards/carry
Receiving
48 Receptions632 Rec yards2 Rec TD13.2 Yards/rec
Returns
12 Kick returns265 KR yards0 KR TD22 Punt returns193 PR yards1 PR TD

Performance Analysis · 2025 · vs WR peers

  • Efficiency100
  • Volume34
  • Explosiveness41
  • Consistency28
  • Pass-Down69
Player type
Versatile WR

Balanced profile without a single dominant trait — contributes across multiple dimensions.

Balanced usageMulti-role
Peer percentiles
Opponent-adjusted EPA (WEPA/play)100th %ile · elite
Game-to-game consistency28th %ile · below avg
Key findings
  • Top-10% efficiency among WRs — elite opponent-adjusted EPA rate.
  • High game-to-game variance — boom-or-bust profile.
  • 5 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • Production faded as the season progressed — 0.15 EPA/play decline from first to second half.
  • Peak game: 1.73 EPA/play in Wk 6 vs Colorado State (SP+ -16).

NIL Market Tier· 2025

On3 valuation ↗
Star

Top-10 nationally. Multiple mid-to-large collective deals expected.

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.

Historical Comparables · WR · efficiency + volume + value

Players from 2013–2025 matched on EPA efficiency, play volume, and adjusted value tier — not just one metric.

PlayerTeamWEPA/playLine valTotal EPA
Noah ShortArmy0.3000.520.7
Chris TyreeNotre Dame0.3100.623.6
Malik DunnerBall State0.2900.422.0
Xavier WhiteTexas Tech0.3000.518.6
Ainias SmithTexas A&M0.3100.517.0

Comps are statistical — efficiency, volume, and value tier all factor in. Style and conference context differ.

Game Log · box score + EPA, week by week

+1.7301.73Wk 1 vs Stony Brook: -0.58 EPA/play1Wk 2 vs Washington State: -0.11 EPA/play2Wk 4 vs California: +0.97 EPA/play4Wk 5 vs Northern Illinois: +0.23 EPA/play5Wk 6 vs Colorado State: +1.73 EPA/play6Wk 7 vs Nevada: +1.50 EPA/play7Wk 9 vs Fresno State: -0.62 EPA/play9Wk 10 vs Wyoming: +0.54 EPA/play10Wk 11 vs Hawai'i: +1.07 EPA/play11Wk 12 vs Boise State: -1.01 EPA/play12
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsStony BrookW42-03186.008-0.58
2@Washington StateL13-363.87699.9023-0.11
4vsCaliforniaW34-0-3.2915417.11800.97
5@Northern IllinoisW6-3-16.76528.70190.23
6vsColorado StateW45-24-15.6715321.91611.73
7@NevadaW44-10-13.4511022.00411.50
9@Fresno StateW23-01.84143.507-0.62
10vsWyomingW24-7-11.344310.80220.54
11@Hawai'iL6-381.722110.50131.07
12vsBoise StateW17-73.11-2-2.000-1.01

Usage & Situational · Pro

Snap-share proxy
Overall
11.9%
Passing plays
28.9%
Rushing plays
2.7%
Standard downs
11.9%
Passing downs
12.0%
EPA by down type
Standard downs
0.30
Passing downs
0.41
Pass / Rush EPA
0.43 / -0.26

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.