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Shane Tucker

#1Shane Tucker

WR·Middle Tennessee·201520140.0 pts line valueDay 2 (Rds 2–3)

Shane Tucker is a 2-year Possession Receiver WR for Middle Tennessee. Shane's 2015 season ranks in the 0th percentile nationally by opponent-adjusted EPA per play across 143 plays — a developing 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 Shane Tucker'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.

2015 Production

Rushing
413 Rush yards2 Rush TD127 Carries3.3 Yards/carry
Receiving
16 Receptions133 Rec yards1 Rec TD8.3 Yards/rec

Performance Analysis · 2015 · vs WR peers

  • Efficiency0
  • Volume56
  • Explosiveness9
  • Consistency62
  • Pass-Down100
Player type
Possession Receiver WR

Chain-mover who earns targets through reliability. High volume, short-to-intermediate routes, consistent floor every week.

High target shareChain moverReliable floor
Peer percentiles
Opponent-adjusted EPA (WEPA/play)0th %ile · below avg
Game-to-game consistency62th %ile · average
Key findings
  • Below-average efficiency vs WR peers — value comes through volume, not per-play impact.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • Strong second-half surge — EPA/play improved 0.18 from the first to second half of the season.

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
Shai WertsGeorgia Southern0.1500.024.2
De'Michael HarrisSouthern Miss0.1300.715.2
Hyleck FosterMarshall0.1800.518.2
Davis BrysonKennesaw State0.2000.019.4
D.J. FosterArizona State0.2001.034.8

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

Game Log · box score + EPA, week by week

+0.5700.57Wk 1 vs Jackson State: +0.22 EPA/play1Wk 2 vs Alabama: -0.56 EPA/play2Wk 3 vs Charlotte: -0.30 EPA/play3Wk 5 vs Vanderbilt: -0.57 EPA/play5Wk 8 vs Louisiana Tech: -0.24 EPA/play8Wk 10 vs Marshall: +0.05 EPA/play10Wk 11 vs Florida Atlantic: -0.08 EPA/play11Wk 12 vs North Texas: +0.01 EPA/play12Wk 13 vs UTSA: -0.10 EPA/play13Wk 1 vs Western Michigan: -0.42 EPA/play1
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsJackson StateW70-1424522.51330.22
2@AlabamaL10-3729.0-0.56
3vsCharlotteW73-14-21.7-0.30
5vsVanderbiltL13-17-1.64164.006-0.57
8@Louisiana TechL16-458.3-0.24
10vsMarshallW27-243.52168.0080.05
11@Florida AtlanticW24-17-9.812020.0020-0.08
12vsNorth TexasW41-7-25.022412.00120.01
13@UTSAW42-7-17.7252.509-0.10
1vsWestern MichiganL31-454.9372.307-0.42

Usage & Situational · Pro

Snap-share proxy
Overall
19.6%
Passing plays
7.1%
Rushing plays
32.8%
Standard downs
22.5%
Passing downs
12.0%
EPA by down type
Standard downs
-0.26
Passing downs
0.20
Pass / Rush EPA
-0.10 / -0.21

Usage = share of team plays (CFBD has no true snap counts).

Career · rolling EPA, game by game

Per-game EPA5-game avg
+1.510−0.762015
EPA per play · 2014 — 2015 · 21 games
SeasonTeamLine valueTotal EPA
2014Middle Tennessee
1.6
31.0
2015Middle Tennessee
0.0
4.5

Chart shows per-game EPA (bars) and rolling 5-game average (line). Season breaks marked with dashed lines. Line value = est. points over replacement per game.

EPA = expected points added (opponent-adjusted). NIL estimates are model-based ranges, not reported deals. Data: CollegeFootballData. Not betting advice.