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Shock Linwood

#32Shock Linwood

RB·Baylor·2015201420133.7 pts line valueDay 2 (Rds 2–3)

Shock Linwood is a 3-year Explosive Back for Baylor. Shock's 2014 season ranks in the 28th percentile nationally by opponent-adjusted EPA per play across 240 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.

2014 Production

Rushing
1252 Rush yards16 Rush TD251 Carries5.0 Yards/carry
Receiving
7 Receptions90 Rec yards0 Rec TD12.9 Yards/rec

Performance Analysis · 2014 · vs RB peers

  • Efficiency28
  • Volume64
  • Explosiveness40
  • Consistency68
  • Receiving14
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)28th %ile · below avg
Game-to-game consistency68th %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.
  • 4 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 — 0.14 EPA/play decline from first to second half.
  • Peak game: 0.82 EPA/play in Wk 5 vs Iowa State (SP+ -8).

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
James FlandersTulsa0.3904.9103.7
Hassan HaskinsMichigan0.3804.8106.4
Royce FreemanOregon0.3605.199.0

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

Game Log · box score + EPA, week by week

+0.8200.82Wk 1 vs SMU: +0.25 EPA/play1Wk 2 vs Northwestern State: +0.48 EPA/play2Wk 3 vs Buffalo: +0.17 EPA/play3Wk 5 vs Iowa State: +0.82 EPA/play5Wk 6 vs Texas: +0.41 EPA/play6Wk 7 vs TCU: +0.02 EPA/play7Wk 8 vs West Virginia: -0.16 EPA/play8Wk 10 vs Kansas: +0.40 EPA/play10Wk 11 vs Oklahoma: +0.31 EPA/play11Wk 13 vs Oklahoma State: +0.19 EPA/play13Wk 14 vs Texas Tech: +0.16 EPA/play14Wk 15 vs Kansas State: +0.46 EPA/play15Wk 1 vs Michigan State: -0.22 EPA/play1
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+CarRush YdsAvgRush TDRecRec YdsRec TDEPA/play
1vsSMUW45-0-21.216895.610.25
2vsNorthwestern StateW70-611333.0125300.48
3@BuffaloW63-21-7.720974.821400.17
5@Iowa StateW49-28-7.915825.530.82
6@TexasW28-79.0281485.310.41
7vsTCUW61-5823.3291786.100.02
8@West VirginiaL27-418.421693.31-0.16
10vsKansasW60-14-9.814815.810.40
11@OklahomaW48-1419.223873.820.31
13vsOklahoma StateW49-288.6211135.411400.19
14vsTexas TechW48-464.9241586.6221500.16
15vsKansas StateW38-2716.318915.110.46
1vsMichigan StateL41-4224.111262.401140-0.22

Usage & Situational · Pro

Snap-share proxy
Overall
22.4%
Passing plays
1.7%
Rushing plays
41.6%
Standard downs
25.2%
Passing downs
15.3%
EPA by down type
Standard downs
0.18
Passing downs
0.40
Pass / Rush EPA
0.68 / 0.21

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.