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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

Air yards

Where the ball goes, and how much of the gain is the throw rather than the run after it.

6
Targets
13.3y
Avg depth
6.0y
After catch
83%
Catch rate

The ball travels 13.3 yards in the air on an average target 4.4 yards deeper than the median. Another 6.0 comes after the catch.

Where he is targeted

targets · completion rate · yards
deep
1
100% · 42y
0
0
short
2
100% · 38y
1
0% · 0y
2
100% · 11y
leftmiddleright

Depth and direction come from CFBD’s passing detail, which is backfilled after the games: this covers weeks 1–2 only. Spikes, throwaways and intentional grounding are excluded before any average.

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.