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Erik Brooks

#3Erik Brooks

Erik Brooks is a Versatile WR for Fresno State. Erik's 2023 season ranks in the 100th percentile nationally by opponent-adjusted EPA per play across 62 plays — a elite rate for the WR.

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 Erik Brooks'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.

2023 Production

Receiving
59 Receptions771 Rec yards5 Rec TD13.1 Yards/rec
Returns
1 Kick returns35 KR yards0 KR TD19 Punt returns174 PR yards0 PR TD

Performance Analysis · 2023 · vs WR peers

  • Efficiency100
  • Volume23
  • Explosiveness40
  • Consistency77
  • 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 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.
  • 7 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • Peak game: 2.43 EPA/play in Wk 11 vs San José State (SP+ -3).

NIL Market Tier· 2023

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
Quadree HendersonPittsburgh0.5301.633.4

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

Game Log · box score + EPA, week by week

+2.4302.43Wk 1 vs Purdue: +1.96 EPA/play1Wk 2 vs Eastern Washington: +1.19 EPA/play2Wk 3 vs Arizona State: +0.34 EPA/play3Wk 4 vs Kent State: +1.58 EPA/play4Wk 5 vs Nevada: +1.24 EPA/play5Wk 6 vs Wyoming: +0.02 EPA/play6Wk 7 vs Utah State: +1.43 EPA/play7Wk 9 vs UNLV: +1.57 EPA/play9Wk 11 vs San José State: +2.43 EPA/play11Wk 12 vs New Mexico: -0.27 EPA/play12Wk 13 vs San Diego State: +0.33 EPA/play13
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1@PurdueW39-35-7.3917018.92491.96
2vsEastern WashingtonW34-3189511.91291.19
3@Arizona StateW29-0-11.3111049.50160.34
4vsKent StateW53-10-26.347919.81401.58
5vsNevadaW27-9-22.023718.50231.24
6@WyomingL19-24-3.6294.5050.02
7@Utah StateW37-32-10.935719.00231.43
9vsUNLVW31-241.42147.01101.57
10vsBoise StateW37-305.9
11@San José StateL18-42-3.435919.70352.43
12vsNew MexicoL17-25-16.55173.408-0.27
13@San Diego StateL18-33-10.355310.60150.33
20vsNew Mexico StateW37-10-1.857715.4035

Usage & Situational · Pro

Snap-share proxy
Overall
8.1%
Passing plays
13.3%
Rushing plays
0.0%
Standard downs
8.1%
Passing downs
8.1%
EPA by down type
Standard downs
0.83
Passing downs
1.24
Pass / Rush EPA
0.96 / —

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.