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Koby Young

#2Koby Young

Koby Young is a Versatile WR for Houston.

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 Koby Young'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
12 Receptions191 Rec yards0 Rec TD15.9 Yards/rec

Performance Analysis · 2025 · vs WR peers

  • Efficiency100
  • Volume11
  • Explosiveness59
  • Consistency66
  • Pass-Down100
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 consistency66th %ile · average
Key findings
  • Top-10% efficiency among WRs — 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 0.40 from the first to second half of the season.
  • Peak game: 1.75 EPA/play in Wk 6 vs Texas Tech (SP+ 28).

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

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

Game Log · box score + EPA, week by week

+1.7501.75Wk 1 vs Stephen F. Austin: -0.51 EPA/play1Wk 6 vs Texas Tech: +1.75 EPA/play6Wk 8 vs Arizona: -0.12 EPA/play8Wk 9 vs Arizona State: +1.04 EPA/play9Wk 10 vs West Virginia: +0.96 EPA/play10Wk 11 vs UCF: +1.11 EPA/play11Wk 13 vs TCU: +0.27 EPA/play13
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsStephen F. AustinW27-0-0.51
5@Oregon StateW27-24-15.9
6vsTexas TechL11-3527.614343.00431.75
8vsArizonaW31-2812.0166.006-0.12
9@Arizona StateW24-163.922713.50191.04
10vsWest VirginiaL35-45-6.845614.00300.96
11@UCFW30-27-1.222713.50181.11
13vsTCUL14-178.30.27
20vsLSUW38-3510.323216.0021

Usage & Situational · Pro

Snap-share proxy
Overall
3.8%
Passing plays
8.7%
Rushing plays
0.2%
Standard downs
3.5%
Passing downs
4.4%
EPA by down type
Standard downs
0.26
Passing downs
0.81
Pass / Rush EPA
0.44 / 1.01

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.