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Jalen Moss

#18Jalen Moss

Jalen Moss is a Slot Specialist WR for Arizona State.

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 Jalen Moss'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
16 Receptions273 Rec yards1 Rec TD17.1 Yards/rec

Performance Analysis · 2025 · vs WR peers

  • Efficiency100
  • Volume15
  • Explosiveness67
  • Consistency68
  • 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 consistency68th %ile · average
Key findings
  • Top-10% efficiency among WRs — elite opponent-adjusted EPA rate.
  • Limited usage share suggests a rotational or specialist role.
  • 3 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 0.48 from the first to second half of the season.
  • Peak game: 0.72 EPA/play in Wk 9 vs Houston (SP+ 7).

NIL Market Tier· 2025

On3 valuation ↗
Starter

Meaningful starter. Local collective + position-group 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
Tyler BuchnerNotre Dame0.2500.312.8
Brandon ChatmanNavy0.2300.612.0
Samajie GrantArizona0.2500.315.5
Justin LynchTemple0.2400.315.1
Amare JonesTulane0.2300.813.3

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

Game Log · box score + EPA, week by week

+0.7200.72Wk 7 vs Utah: -0.03 EPA/play7Wk 9 vs Houston: +0.72 EPA/play9Wk 10 vs Iowa State: -0.20 EPA/play10Wk 12 vs West Virginia: +0.65 EPA/play12Wk 14 vs Arizona: +0.66 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
7@UtahL10-4222.22157.5012-0.03
9vsHoustonL16-247.422613.00180.72
10@Iowa StateW24-199.935217.3038-0.20
12vsWest VirginiaW25-23-6.834113.70250.65
14vsArizonaL7-2312.011010.00100.66
20vsDukeL39-426.6512925.8151

Usage & Situational · Pro

Snap-share proxy
Overall
5.3%
Passing plays
10.1%
Rushing plays
0.4%
Standard downs
3.4%
Passing downs
8.8%
EPA by down type
Standard downs
0.00
Passing downs
0.39
Pass / Rush EPA
0.41 / -3.98

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.