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Nico Ragaini

#89Nico Ragaini

WR·Iowa·2023

Nico Ragaini is a Slot Specialist WR for Iowa. Nico's 2023 season produced 11.9 total EPA across 44 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 Nico Ragaini'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
31 Receptions255 Rec yards0 Rec TD8.2 Yards/rec

Performance Analysis · 2023 · vs WR peers

  • Efficiency80
  • Volume18
  • Explosiveness8
  • Consistency58
  • 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)80th %ile · above avg
Game-to-game consistency58th %ile · average
Key findings
  • Above-average efficiency for the WR position (80th percentile).
  • Limited usage share suggests a rotational or specialist role.
  • 5 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • Peak game: 2.04 EPA/play in Wk 1 vs Utah State (SP+ -11).

NIL Market Tier· 2023

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
Tyler BuchnerNotre Dame0.2500.312.8
Samajie GrantArizona0.2500.315.5
Justin LynchTemple0.2400.315.1
Nick NashSan José State0.3100.514.0
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

+2.0402.04Wk 1 vs Utah State: +2.04 EPA/play1Wk 2 vs Iowa State: +0.23 EPA/play2Wk 3 vs Western Michigan: -0.02 EPA/play3Wk 4 vs Penn State: -0.11 EPA/play4Wk 5 vs Michigan State: +0.43 EPA/play5Wk 7 vs Wisconsin: -0.04 EPA/play7Wk 8 vs Minnesota: +0.65 EPA/play8Wk 10 vs Northwestern: +0.97 EPA/play10Wk 11 vs Rutgers: +0.34 EPA/play11Wk 12 vs Illinois: +1.05 EPA/play12Wk 13 vs Nebraska: -0.26 EPA/play13Wk 14 vs Michigan: +0.09 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsUtah StateW24-14-10.923618.00292.04
2@Iowa StateW20-137.5284.0080.23
3vsWestern MichiganW41-10-15.9144.004-0.02
4@Penn StateL0-3123.5144.004-0.11
5vsMichigan StateW26-16-6.82189.00140.43
7@WisconsinW15-69.42136.507-0.04
8vsMinnesotaL10-120.44287.00110.65
10vsNorthwesternW10-7-1.3188.0080.97
11vsRutgersW22-03.544812.00170.34
12vsIllinoisW15-13-2.55469.20131.05
13@NebraskaW13-100.32147.008-0.26
14vsMichiganL0-2631.33258.30120.09
20vsTennesseeL0-3516.2231.504

Usage & Situational · Pro

Snap-share proxy
Overall
6.3%
Passing plays
13.3%
Rushing plays
0.7%
Standard downs
4.9%
Passing downs
9.2%
EPA by down type
Standard downs
-0.12
Passing downs
0.66
Pass / Rush EPA
0.36 / -0.95

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.