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Cade Keith

#88Cade Keith

Cade Keith is a Versatile TE for New Mexico.

What projects, and what doesn't · TEs · 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)0.42
    Beats guessing the TE average by 9%. n=2,225 TE seasons
  • EPA per play (efficiency)0.04
    Not projectable — we do not forecast this. n=2,016 TE seasons
  • Total EPA (value)0.46
    Beats guessing the TE average by 13%. n=2,016 TE seasons

Across all positions, usage carries year to year at 0.47 and efficiency at 0.07. So Cade Keith'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
20 Receptions253 Rec yards3 Rec TD12.7 Yards/rec

Performance Analysis · 2025 · vs TE peers

  • Efficiency100
  • Volume9
  • Explosiveness38
  • Consistency45
  • Pass-Down100
Player type
Versatile TE

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 consistency45th %ile · average
Key findings
  • Top-10% efficiency among TEs — elite opponent-adjusted EPA rate.
  • Limited usage share suggests a rotational or specialist role.
  • 4 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • Strong second-half surge — EPA/play improved 0.23 from the first to second half of the season.
  • Peak game: 2.65 EPA/play in Wk 5 vs New Mexico State (SP+ -16).

NIL Market Tier· 2025

On3 valuation ↗
Elite

Top-3 player at position nationally. Collective + national brand 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 · TE · 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
Ty ThompsonTulane0.4200.720.2
Seth GreenMinnesota0.3900.032.4
Johnny LanganRutgers0.3000.017.7
Evan SvobodaWyoming0.2900.521.8
Jordan MyersRice0.2700.215.9

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

Game Log · box score + EPA, week by week

+2.6502.65Wk 1 vs Michigan: -0.35 EPA/play1Wk 2 vs Idaho State: -0.14 EPA/play2Wk 3 vs UCLA: -0.31 EPA/play3Wk 5 vs New Mexico State: +2.65 EPA/play5Wk 6 vs San José State: +0.60 EPA/play6Wk 7 vs Boise State: +0.29 EPA/play7Wk 9 vs Utah State: +0.95 EPA/play9Wk 10 vs UNLV: +2.09 EPA/play10Wk 14 vs San Diego State: -0.56 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1@MichiganL17-3412.4252.504-0.35
2vsIdaho StateW32-22144.004-0.14
3@UCLAW35-10-8.7100.000-0.31
5vsNew Mexico StateW38-20-15.522412.01192.65
6@San José StateL28-35-14.32199.50150.60
7@Boise StateL25-413.122211.00130.29
9vsUtah StateW33-14-3.1710414.91400.95
10@UNLVW40-354.325025.00452.09
14vsSan Diego StateW23-176.712525.0125-0.56

Usage & Situational · Pro

Snap-share proxy
Overall
3.3%
Passing plays
7.1%
Rushing plays
0.0%
Standard downs
3.9%
Passing downs
2.1%
EPA by down type
Standard downs
0.59
Passing downs
1.33
Pass / Rush EPA
0.70 / —

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.