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Shock Linwood

#32Shock Linwood

RB·Baylor·2015201420132.4 pts line valueDay 3 (Rds 4–7)

Shock Linwood is a 3-year Explosive Back for Baylor. Shock's 2015 season ranks in the 38th percentile nationally by opponent-adjusted EPA per play across 195 plays — a developing rate for the RB. Shock's production has improved each season, a positive development trajectory.

What projects, and what doesn't · RBs · 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)0.52
    Beats guessing the RB average by 18%. n=4,219 RB seasons
  • EPA per play (efficiency)0.10
    Not projectable — we do not forecast this. n=3,575 RB seasons
  • Total EPA (value)0.41
    Beats guessing the RB average by 9%. n=3,575 RB seasons

Across all positions, usage carries year to year at 0.47 and efficiency at 0.07. So Shock Linwood'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
1329 Rush yards10 Rush TD196 Carries6.8 Yards/carry
Receiving
9 Receptions71 Rec yards1 Rec TD7.9 Yards/rec

Performance Analysis · 2015 · vs RB peers

  • Efficiency38
  • Volume58
  • Explosiveness76
  • Consistency66
  • Receiving21
Player type
Explosive Back

Elite per-carry efficiency — breaks big runs and creates chunk plays at a top rate while in a limited role.

Big-play threatHigh EPA per carryCapitalises on opportunities
Peer percentiles
Opponent-adjusted EPA (WEPA/play)38th %ile · below avg
Game-to-game consistency66th %ile · average
Career trajectory:↑ Rising
Key findings
  • Below-average efficiency vs RB peers — value comes through volume, not per-play impact.
  • Career trajectory is upward — WEPA value has improved season over season.
  • 6 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • Production faded as the season progressed — 0.41 EPA/play decline from first to second half.
  • Peak game: 0.71 EPA/play in Wk 6 vs Kansas (SP+ -21).

Historical Comparables · RB · 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
Saquon BarkleyPenn State0.3403.997.9
Dalvin CookFlorida State0.3404.399.3
Travis EtienneClemson0.4704.7100.1
James FlandersTulsa0.3904.9103.7
Saquon BarkleyPenn State0.4105.298.4

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

Game Log · box score + EPA, week by week

+0.7100.71Wk 1 vs SMU: +0.43 EPA/play1Wk 2 vs Lamar: +0.59 EPA/play2Wk 4 vs Rice: +0.55 EPA/play4Wk 5 vs Texas Tech: +0.60 EPA/play5Wk 6 vs Kansas: +0.71 EPA/play6Wk 7 vs West Virginia: +0.07 EPA/play7Wk 8 vs Iowa State: +0.51 EPA/play8Wk 10 vs Kansas State: +0.31 EPA/play10Wk 11 vs Oklahoma: -0.01 EPA/play11Wk 12 vs Oklahoma State: +0.03 EPA/play12Wk 13 vs TCU: +0.11 EPA/play13Wk 14 vs Texas: -0.45 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+CarRush YdsAvgRush TDRecRec YdsRec TDEPA/play
1@SMUW56-21-17.58759.400.43
2vsLamarW66-31181307.230.59
4vsRiceW70-17-14.6161589.910.55
5vsTexas TechW63-354.52022111.120.60
6@KansasW66-7-21.31313510.4121700.71
7vsWest VirginiaW62-3812.919844.410.07
8vsIowa StateW45-27-0.3271716.311610.51
10@Kansas StateW31-242.613725.5032900.31
11vsOklahomaL34-4422.7211034.90240-0.01
12@Oklahoma StateW45-359.920914.610.03
13@TCUL21-2819.014584.1011500.11
14vsTexasL17-233.77314.40-0.45

Usage & Situational · Pro

Snap-share proxy
Overall
20.2%
Passing plays
2.3%
Rushing plays
31.7%
Standard downs
21.4%
Passing downs
17.0%
EPA by down type
Standard downs
0.30
Passing downs
0.43
Pass / Rush EPA
1.11 / 0.29

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

Career · rolling EPA, game by game

Per-game EPA5-game avg
+0.950−0.7120142015
EPA per play · 2013 — 2015 · 37 games
SeasonTeamLine valueTotal EPA
2013Baylor
1.4
14.3
2014Baylor
3.7
77.2
2015Baylor
2.4
53.1

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.