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Tony Diaz

#14Tony Diaz

WR·Iowa·2026

Tony Diaz is a Slot Specialist WR for Iowa.

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 Tony Diaz'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.

2026 Production

Receiving
15 Receptions179 Rec yards1 Rec TD11.9 Yards/rec

Air yards

Where the ball goes, and how much of the gain is the throw rather than the run after it.

13
Targets
11.3y
Avg depth
8.6y
After catch
54%
Catch rate

The ball travels 11.3 yards in the air on an average target 2.3 yards deeper than the median. Another 8.6 comes after the catch.

Where he is targeted

targets · completion rate · yards
deep
2
0% · 0y
0
1
0% · 0y
short
5
60% · 38y
2
100% · 22y
3
67% · 24y
leftmiddleright

Depth and direction come from CFBD’s passing detail, which is backfilled after the games: this covers weeks 1–2 only. Spikes, throwaways and intentional grounding are excluded before any average.

Performance Analysis · 2026 · vs WR peers

  • Efficiency67
  • Volume51
  • Explosiveness33
  • Consistency50
  • Pass-Down91
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)67th %ile · average
Key findings
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.

NIL Market Tier· 2026

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
Brandon ChatmanNavy0.2300.612.0
Tyler BuchnerNotre Dame0.2500.312.8
Amare JonesTulane0.1800.012.8
Justin LynchTemple0.2400.315.1
Samajie GrantArizona0.2500.315.5

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

Game Log · box score + EPA, week by week

+0.1300.13Wk 1 vs Northern Illinois: +0.13 EPA/play1Wk 2 vs Iowa State: -0.00 EPA/play2
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsNorthern IllinoisW40-0-22.378412.01240.13
2vsIowa StateW16-133.189511.9056-0.00

Usage & Situational · Pro

Snap-share proxy
Overall
18.0%
Passing plays
34.8%
Rushing plays
1.5%
Standard downs
15.3%
Passing downs
24.4%
EPA by down type
Standard downs
0.09
Passing downs
0.33
Pass / Rush EPA
0.19 / —

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.
Tony Diaz Stats, EPA & Player Profile — Iowa · Gridpex