Skip to content
Tyler Brown

#6Tyler Brown

Tyler Brown is a Versatile WR for Clemson. Tyler's 2025 season produced 15.3 total EPA across 36 plays.

What projects, and what doesn't · WRs · 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)0.47
    Beats guessing the WR average by 16%. n=6,302 WR seasons
  • EPA per play (efficiency)0.09
    Not projectable — we do not forecast this. n=5,767 WR seasons
  • Total EPA (value)0.45
    Beats guessing the WR average by 12%. n=5,767 WR seasons

Across all positions, usage carries year to year at 0.47 and efficiency at 0.07. So Tyler Brown'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
22 Receptions191 Rec yards0 Rec TD8.7 Yards/rec
Returns
2 Kick returns41 KR yards0 KR TD

Performance Analysis · 2025 · vs WR peers

  • Efficiency100
  • Volume16
  • Explosiveness11
  • Consistency20
  • Pass-Down14
Player type
Versatile WR

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 consistency20th %ile · below avg
Key findings
  • Top-10% efficiency among WRs — elite opponent-adjusted EPA rate.
  • Limited usage share suggests a rotational or specialist role.
  • High game-to-game variance — boom-or-bust profile.
  • 5 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • Peak game: 1.02 EPA/play in Wk 13 vs Furman.

NIL Market Tier· 2025

On3 valuation ↗
Star

Top-10 nationally. Multiple mid-to-large collective deals expected.

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 · WR · 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
Dane KinamonAir Force0.4100.716.0
Keytaon ThompsonVirginia0.3700.615.2
Micah DavisAir Force0.3700.616.3
JoJo NatsonUtah State0.3901.019.9
Savion WilliamsTCU0.4501.125.2

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

Game Log · box score + EPA, week by week

+1.0201.02Wk 1 vs LSU: +0.08 EPA/play1Wk 2 vs Troy: +0.75 EPA/play2Wk 3 vs Georgia Tech: +0.43 EPA/play3Wk 4 vs Syracuse: +0.88 EPA/play4Wk 6 vs North Carolina: -1.00 EPA/play6Wk 7 vs Boston College: -0.65 EPA/play7Wk 8 vs SMU: +0.14 EPA/play8Wk 10 vs Duke: +0.51 EPA/play10Wk 13 vs Furman: +1.02 EPA/play13
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsLSUL10-1710.344310.80170.08
2vsTroyW27-16-4.844511.30230.75
3@Georgia TechL21-249.3273.5060.43
4vsSyracuseL21-34-13.133311.00140.88
6@North CarolinaW38-10-6.6294.505-1.00
7@Boston CollegeW41-10-8.5122.002-0.65
8vsSMUL24-3513.4199.0090.14
10vsDukeL45-466.62126.0060.51
13vsFurmanW45-101.02
20vsPenn StateL10-2218.133110.3020

Usage & Situational · Pro

Snap-share proxy
Overall
5.6%
Passing plays
8.3%
Rushing plays
2.1%
Standard downs
5.1%
Passing downs
6.8%
EPA by down type
Standard downs
0.50
Passing downs
0.28
Pass / Rush EPA
0.28 / 1.17

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.