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Treyton Welch

#81Treyton Welch

Treyton Welch is a Versatile TE for Wyoming.

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 Treyton Welch'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.

2023 Production

Receiving
31 Receptions308 Rec yards2 Rec TD9.9 Yards/rec

Performance Analysis · 2023 · vs TE peers

  • Efficiency100
  • Volume15
  • Explosiveness20
  • Consistency53
  • 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 consistency53th %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 0.61 from the first to second half of the season.
  • Peak game: 1.58 EPA/play in Wk 11 vs UNLV (SP+ 1).

NIL Market Tier· 2023

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

+1.5801.58Wk 1 vs Texas Tech: +0.85 EPA/play1Wk 2 vs Portland State: -0.39 EPA/play2Wk 3 vs Texas: -0.30 EPA/play3Wk 5 vs New Mexico: -0.18 EPA/play5Wk 6 vs Fresno State: +0.99 EPA/play6Wk 9 vs Boise State: +0.67 EPA/play9Wk 11 vs UNLV: +1.58 EPA/play11Wk 12 vs Hawai'i: +0.16 EPA/play12
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsTexas TechW35-336.133110.30190.85
2vsPortland StateW31-17133.003-0.39
3@TexasL10-3123.23227.3018-0.30
5vsNew MexicoW35-26-16.53227.3022-0.18
6vsFresno StateW24-192.567412.31190.99
7@Air ForceL27-345.933812.7122
9@Boise StateL7-325.93289.30130.67
11@UNLVL14-341.435016.70321.58
12vsHawai'iW42-9-16.42189.00100.16
20vsToledoW16-153.74225.509

Usage & Situational · Pro

Snap-share proxy
Overall
5.2%
Passing plays
11.6%
Rushing plays
0.3%
Standard downs
5.3%
Passing downs
5.0%
EPA by down type
Standard downs
0.39
Passing downs
0.90
Pass / Rush EPA
0.54 / —

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.