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Joshisa Trader

#2Joshisa Trader

WR·Miami·2025

Joshisa Trader is a Slot Specialist WR for Miami.

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 Joshisa Trader'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
13 Receptions178 Rec yards1 Rec TD13.7 Yards/rec

Performance Analysis · 2025 · vs WR peers

  • Efficiency100
  • Volume9
  • Explosiveness45
  • Consistency77
  • Pass-Down100
Player type
Slot Specialist WR

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 consistency77th %ile · above 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 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.
  • Peak game: 2.03 EPA/play in Wk 14 vs Pittsburgh (SP+ 8).

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
Keytaon ThompsonVirginia0.3200.412.5

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

Game Log · box score + EPA, week by week

+2.0302.03Wk 10 vs SMU: +0.68 EPA/play10Wk 11 vs Syracuse: +0.04 EPA/play11Wk 12 vs NC State: +0.61 EPA/play12Wk 13 vs Virginia Tech: +0.93 EPA/play13Wk 14 vs Pittsburgh: +2.03 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
10@SMUL20-2613.458116.21360.68
11vsSyracuseW38-10-13.13196.30100.04
12vsNC StateW41-74.814444.00440.61
13@Virginia TechW34-17-10.111414.00140.93
14@PittsburghW38-78.411010.00102.03
20vsOle MissW31-2724.0133.003
20vsOhio StateW24-1430.1177.007

Usage & Situational · Pro

Snap-share proxy
Overall
3.3%
Passing plays
7.3%
Rushing plays
0.0%
Standard downs
2.3%
Passing downs
6.3%
EPA by down type
Standard downs
0.09
Passing downs
0.77
Pass / Rush EPA
0.41 / —

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.