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Eric Richardson
Eric Richardson

#2Eric Richardson

WR·Wyoming·2025

Eric Richardson is a Versatile WR for Wyoming.

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 Eric Richardson'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

Receiving
10 Receptions112 Rec yards1 Rec TD11.2 Yards/rec

Performance Analysis · 2025 · vs WR peers

  • Efficiency0
  • Volume10
  • Explosiveness28
  • Consistency0
  • Pass-Down62
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)0th %ile · below avg
Game-to-game consistency0th %ile · below avg
Key findings
  • ▸Below-average efficiency vs WR peers — value comes through volume, not per-play impact.
  • ▸Limited usage share suggests a rotational or specialist role.
  • ▸High game-to-game variance — boom-or-bust profile.
  • ▸Strong second-half surge — EPA/play improved 0.09 from the first to second half of the season.
  • ▸Peak game: 0.52 EPA/play in Wk 9 vs Colorado State (SP+ -16).

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.

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
De'Michael HarrisSouthern Miss0.1300.715.2
Amare JonesTulane0.1800.012.8
Hyleck FosterMarshall0.1800.518.2
Davis BrysonKennesaw State0.2000.019.4
Eli HeidenreichNavy0.2200.815.4

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

Game Log · box score + EPA, week by week

+0.790−0.79Wk 3 vs Utah: -0.10 EPA/play3Wk 4 vs Colorado: +0.45 EPA/play4Wk 6 vs UNLV: -0.71 EPA/play6Wk 7 vs San José State: +0.15 EPA/play7Wk 8 vs Air Force: +0.17 EPA/play8Wk 9 vs Colorado State: +0.52 EPA/play9Wk 12 vs Fresno State: -0.79 EPA/play12
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
3vsUtahL6-3122.2144.004-0.10
4@ColoradoL20-37-8.314141.01410.45
6vsUNLVL17-314.3199.009-0.71
7vsSan José StateW35-28-14.33279.00110.15
8@Air ForceL21-24-3.2199.0090.17
9vsColorado StateW28-0-15.63227.30130.52
12@Fresno StateL3-241.8—————-0.79

Usage & Situational · Pro

Snap-share proxy
Overall
3.4%
Passing plays
6.3%
Rushing plays
0.5%
Standard downs
3.3%
Passing downs
3.5%
EPA by down type
Standard downs
-0.19
Passing downs
-0.12
Pass / Rush EPA
-0.07 / -1.18

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.