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Jevyon Ducker

Jevyon Ducker

Jevyon Ducker is a Pass-Catching Back for Temple. Jevyon's 2025 season ranks in the 0th percentile nationally by opponent-adjusted EPA per play across 185 plays — a developing rate for the RB.

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 Jevyon Ducker'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
809 Rush yards7 Rush TD157 Carries5.2 Yards/carry
Receiving
23 Receptions105 Rec yards2 Rec TD4.6 Yards/rec

Performance Analysis · 2025 · vs RB peers

  • Efficiency0
  • Volume76
  • Explosiveness44
  • Consistency46
  • Receiving75
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 consistency46th %ile · average
Key findings
  • Below-average efficiency vs RB peers — value comes through volume, not per-play impact.
  • Peak game: 0.59 EPA/play in Wk 2 vs Howard.

NIL Market Tier· 2025

On3 valuation ↗
Starter

Meaningful starter. Local collective + position-group 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.

Historical Comparables · RB · 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
Saquon BarkleyPenn State0.3403.997.9
Dalvin CookFlorida State0.3404.399.3
Breece HallIowa State0.3404.5102.3

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

Game Log · box score + EPA, week by week

+0.5900.59Wk 1 vs Massachusetts: +0.10 EPA/play1Wk 2 vs Howard: +0.59 EPA/play2Wk 3 vs Oklahoma: -0.12 EPA/play3Wk 4 vs Georgia Tech: +0.31 EPA/play4Wk 6 vs UTSA: -0.31 EPA/play6Wk 7 vs Navy: +0.07 EPA/play7Wk 8 vs Charlotte: +0.48 EPA/play8Wk 9 vs Tulsa: +0.30 EPA/play9Wk 10 vs East Carolina: +0.01 EPA/play10Wk 11 vs Army: -0.04 EPA/play11Wk 13 vs Tulane: -0.04 EPA/play13Wk 14 vs North Texas: +0.31 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+CarRush YdsAvgRush TDRecRec YdsRec TDEPA/play
1@MassachusettsW42-10-36.6191286.702500.10
2vsHowardW55-710878.710.59
3vsOklahomaL3-4218.37243.40350-0.12
4@Georgia TechL24-459.314765.4111500.31
6vsUTSAW27-213.716342.10230-0.31
7vsNavyL31-326.224974.021400.07
8@CharlotteW49-14-26.7911412.711500.48
9@TulsaW38-37-10.016784.9042320.30
10vsEast CarolinaL14-458.015453.011100.01
11@ArmyL13-140.88465.803180-0.04
13vsTulaneL13-376.37172.404210-0.04
14@North TexasL25-5213.812635.311500.31

Usage & Situational · Pro

Snap-share proxy
Overall
26.6%
Passing plays
10.9%
Rushing plays
41.9%
Standard downs
30.5%
Passing downs
18.1%
EPA by down type
Standard downs
0.17
Passing downs
-0.04
Pass / Rush EPA
-0.04 / 0.17

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.