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Blake Smith

#16Blake Smith

Blake Smith is a Versatile TE for Texas State.

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 Blake Smith'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 Receptions105 Rec yards0 Rec TD10.5 Yards/rec

Performance Analysis · 2025 · vs TE peers

  • Efficiency100
  • Volume7
  • Explosiveness23
  • Consistency76
  • 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 consistency76th %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.
  • 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 0.29 from the first to second half of the season.
  • Peak game: 1.37 EPA/play in Wk 11 vs Louisiana (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

+1.3701.37Wk 1 vs Eastern Michigan: +1.08 EPA/play1Wk 3 vs Arizona State: +1.28 EPA/play3Wk 10 vs James Madison: -0.33 EPA/play10Wk 11 vs Louisiana: +1.37 EPA/play11Wk 13 vs UL Monroe: +0.57 EPA/play13
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsEastern MichiganW52-27-14.72189.0091.08
3@Arizona StateL15-343.92199.50101.28
10vsJames MadisonL20-5212.32157.5010-0.33
11@LouisianaL39-42-10.111111.00111.37
13vsUL MonroeW31-14-21.622010.00110.57
20vsRiceW41-10-14.812222.0022

Usage & Situational · Pro

Snap-share proxy
Overall
2.4%
Passing plays
5.4%
Rushing plays
0.0%
Standard downs
2.6%
Passing downs
2.1%
EPA by down type
Standard downs
0.50
Passing downs
0.98
Pass / Rush EPA
0.62 / —

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.