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Data + sources
RAS by Kent Lee Platte·Consensus Big Board (Arif Hasan)·nflverse·PFR·CFBD·All sources & credits·Methodology
Career-value model, live
Privacy·Terms·Press ⌘K to search·Draftanomics2026
  1. Draftanomics/
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  3. 2016 board/
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Side-by-side comparison

Backtest

2 prospects · 2016 draft

Each spoke: percentile within the prospect's own position (DT)
JB
Jonathan Bullard
DT · Florida
22.5 yo · — · —
SD
Sheldon Day
DT · Notre Dame
21.8 yo · 6'1" · 293 lb
Tiebreaker
High confidence
Take Jonathan Bullard over Sheldon Day.

Decisive factor: 42-pick gap on Draftanomics projection. Reinforced by $12M/yr more in projected second-deal AAV.

Headline metrics

The four numbers a GM checks first.

Jonathan Bullard
Predicted pick
#40
range #30–#50
Bust probability
0%
Consensus rank
#32
on 16 boards
Career arc
arrives after the combineThe forecast needs his measurables first.
2nd-deal AAV
$16Mmodel
Sheldon Day
Predicted pick
#82
range #75–#89
Bust probability
0%
Consensus rank
#87
on 11 boards
Career arc
arrives after the combineThe forecast needs his measurables first.
2nd-deal AAV
$4Mmodel

Feature radar

Each axis is the prospect's percentile among prospects at his position (0–100). Bigger shape = stronger across the board.

ProductionAthleticismAgeConsensusPer-play impact (PPA)Breakout ageWorkloadRAS × production
Prospects
  • Jonathan Bullard· EDGE / DL / LB
  • Sheldon Day· EDGE / DL / LB
Axis leaders
  • ProductionJonathan Bullard50
  • AthleticismJonathan Bullard55
  • AgeSheldon Day84
  • ConsensusJonathan Bullard21
  • Per-play impact (PPA)Jonathan Bullard50
  • Breakout ageJonathan Bullard50
  • WorkloadJonathan Bullard50
  • RAS × productionJonathan Bullard100

Comp overlap

Top five historical comps per prospect. Shared comps highlighted.

No shared comps in the top five. Each prospect has a distinct historical profile.
Jonathan Bullard
  • comps arrive after the combineBefore the combine there isn't enough measured data to match him confidently against past players. Comparisons draw on recent NFL careers (2021–2024) and fill in once combine numbers and game-by-game stats land.
Sheldon Day
  • comps arrive after the combineBefore the combine there isn't enough measured data to match him confidently against past players. Comparisons draw on recent NFL careers (2021–2024) and fill in once combine numbers and game-by-game stats land.

Risk and opportunity flags

Top three concerns and top two upside signals from the model.

Jonathan Bullard
Risks
  • No athletic testing
    No Combine drills or Pro Day numbers on file while most of the class has tested — the athletic part of the grade is unmeasured.
Opportunities
No standout upside flags.
Sheldon Day
Risks
No major risks flagged.
Opportunities
  • Mid-major standout
    School SP+ 22.4 (FBS INDEPENDENTS). Strong program among non-Power-5 — the prospect dominated against decent competition.

Career trajectory forecast

Projected share of his team's snaps across the first four NFL seasons. Solid = seasons already played, dashed = the forecast.

0%25%50%75%100%Y1Y2Y3Y4Snap share
Jonathan BullardSheldon Day· solid = actuals, dashed = forecast

Verdict

The model's plain-English read.

Jonathan Bullard

Draftanomics projects Jonathan Bullard (age 22.5 at draft) as a Day 2 pick at #40 (range #30-#50, moderate band). Bust probability sits at 0% — low. No Combine drills or Pro Day numbers on file while most of the class has tested — the athletic part of the grade is unmeasured. The call is a hold at slot: the model's #40 sits within 4 spots of the room's #36 — no market edge to chase, so take him where he sits, and let the 0% bust probability break ties on draft day.

Sheldon Day

Draftanomics projects Sheldon Day (age 21.8 at draft) as a third-round / early Day 3 pick at #82 (range #75-#89, moderate band). Bust probability sits at 0% — low. School SP+ 22.4 (FBS INDEPENDENTS). Strong program among non-Power-5 — the prospect dominated against decent competition. The call is a lean fade: the model sits 12 spots below the room's consensus #70 — don't pay sticker price. The 12-spot markdown rests on thin verified signal rather than a named flaw — the model hasn't seen enough yet to match the room's conviction.