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Reed Harris

#3Reed Harris

Reed Harris is a Versatile WR for Boston College. Reed's 2025 season ranks in the 100th percentile nationally by opponent-adjusted EPA per play across 66 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 Reed Harris'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
39 Receptions673 Rec yards5 Rec TD17.3 Yards/rec

Performance Analysis · 2025 · vs WR peers

  • Efficiency100
  • Volume25
  • Explosiveness68
  • Consistency73
  • 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 consistency73th %ile · average
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.
  • Strong second-half surge — EPA/play improved 0.20 from the first to second half of the season.
  • Peak game: 1.18 EPA/play in Wk 11 vs SMU (SP+ 13).

NIL Market Tier· 2025

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
Keytaon ThompsonMississippi State0.4601.232.2
Savion WilliamsTCU0.4501.125.2
DeAndre HughesAir Force0.4701.328.2
Quadree HendersonPittsburgh0.5301.633.4
Javion PoseyFlorida Atlantic0.4501.423.8

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

Game Log · box score + EPA, week by week

+1.1801.18Wk 1 vs Fordham: +0.81 EPA/play1Wk 2 vs Michigan State: -0.10 EPA/play2Wk 3 vs Stanford: +0.95 EPA/play3Wk 5 vs California: +0.06 EPA/play5Wk 6 vs Pittsburgh: +0.23 EPA/play6Wk 8 vs UConn: +0.63 EPA/play8Wk 9 vs Louisville: +0.47 EPA/play9Wk 10 vs Notre Dame: +0.56 EPA/play10Wk 11 vs SMU: +1.18 EPA/play11Wk 12 vs Georgia Tech: +1.04 EPA/play12Wk 14 vs Syracuse: -0.28 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsFordhamW66-1022311.51170.81
2@Michigan StateL40-42-3.423216.0118-0.10
3@StanfordL20-30-11.8714120.10460.95
5vsCaliforniaL24-28-3.245413.50260.06
6@PittsburghL7-488.423517.50240.23
8vsUConnL23-385.135217.31390.63
9@LouisvilleL24-3812.445313.30170.47
10vsNotre DameL10-2524.422814.01250.56
11vsSMUL13-4513.468614.30251.18
12vsGeorgia TechL34-369.3514228.41571.04
14@SyracuseW34-12-13.122713.5021-0.28

Usage & Situational · Pro

Snap-share proxy
Overall
8.8%
Passing plays
15.0%
Rushing plays
0.3%
Standard downs
7.8%
Passing downs
11.1%
EPA by down type
Standard downs
0.38
Passing downs
0.77
Pass / Rush EPA
0.54 / -0.76

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.