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D'Andre Rogers

D'Andre Rogers

TE·TCU·2025

D'Andre Rogers is a Slot Specialist TE for TCU. D'Andre's 2025 season produced 24.2 total EPA across 40 plays.

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 D'Andre Rogers'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
34 Receptions319 Rec yards2 Rec TD9.4 Yards/rec

Performance Analysis · 2025 · vs TE peers

  • Efficiency100
  • Volume14
  • Explosiveness16
  • Consistency82
  • Pass-Down100
Player type
Slot Specialist TE

The offense's primary passing-down weapon — routes, separation, and reliability on 3rd down define this role.

3rd-down converterRoute technicianHigh passing-down share
Peer percentiles
Opponent-adjusted EPA (WEPA/play)100th %ile · elite
Game-to-game consistency82th %ile · above avg
Key findings
  • Top-10% efficiency among TEs — elite opponent-adjusted EPA rate.
  • Limited usage share suggests a rotational or specialist role.
  • High game-to-game consistency — reliable floor each week.
  • 8 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 0.18 from the first to second half of the season.
  • Peak game: 1.43 EPA/play in Wk 11 vs Iowa State (SP+ 10).

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

+1.4301.43Wk 1 vs North Carolina: +0.88 EPA/play1Wk 3 vs Abilene Christian: +0.17 EPA/play3Wk 4 vs SMU: +0.66 EPA/play4Wk 5 vs Arizona State: +0.88 EPA/play5Wk 6 vs Colorado: +0.64 EPA/play6Wk 7 vs Kansas State: +0.16 EPA/play7Wk 8 vs Baylor: +0.62 EPA/play8Wk 9 vs West Virginia: +0.13 EPA/play9Wk 11 vs Iowa State: +1.43 EPA/play11Wk 13 vs Houston: +0.47 EPA/play13Wk 14 vs Cincinnati: +1.07 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1@North CarolinaW48-14-6.65438.61140.88
3vsAbilene ChristianW42-21188.0080.17
4vsSMUW35-2413.433110.30140.66
5@Arizona StateL24-273.946015.00390.88
6vsColoradoW35-21-8.33279.00140.64
7@Kansas StateL28-417.03279.00130.16
8vsBaylorW42-361.44307.51130.62
9@West VirginiaW23-17-6.83237.70160.13
11vsIowa StateL17-209.933210.70161.43
13@HoustonW17-147.4273.5080.47
14vsCincinnatiW45-234.511212.00121.07
20vsUSCW30-2716.92199.5013

Usage & Situational · Pro

Snap-share proxy
Overall
4.8%
Passing plays
9.2%
Rushing plays
0.0%
Standard downs
4.0%
Passing downs
6.6%
EPA by down type
Standard downs
0.26
Passing downs
1.03
Pass / Rush EPA
0.60 / —

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.