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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/
  2. 2017 board/
  3. Taco Charlton
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Taco Charlton
2017 NFL Draft prospect

Taco Charlton

EDGE·Michigan·Big Ten
age 22.5 · 6'6" · 277 lb

On the live board, bust risk sits at 3% and the realistic range is No. 8 to No. 138.

34rank#34$3.3MCompShane Ray
Big Ten→ DAL's 2017 class
Print sheet
Backtest: model vs. reality

The model graded Taco Charlton at pick #34; he was actually picked #28 by DAL. 1 NFL season in, he's hung on the fringe of the rotation (grading 6.0 of 20 per season). The 4-tier model has him as a likely starter.

Taco CharltonEDGEDraftanomics #34
Print
Dossier
OverviewScouting reportWhy this gradeConsensusProductionRisk1Team fit5Will he be there?Comps5Film & notes

Overview

Headline grade, verdict, and the one-line scout take

Draftanomics Rank
High conviction
#34EDGE·Michigan

We had him No. 34 on draft night, and the league mostly agreed — DAL took him at No. 28. The seasons since are the scoreboard.

Scouting report

The written report — drafted from the fact sheet, every number traceable, honest about what we can't see yet

Why this grade

Which signals drove the grade up or down — in plain English

Consensus

The analyst room, accuracy-weighted, plus where Draftanomics disagrees with it

Production

Measurables, traits, and college play quality

Risk1

Bust probability, injury history, character flags, pre-mortem

Team fit5

How well this prospect fits each of the 32 team schemes

Will he be there?

Probability he's still on the board at each of your picks

Comps5

Historical players this prospect resembles

Film & notes

Clips, scout notes, voice memos, written reports

Draftanomics's take

Draftanomics had Taco Charlton at #34 on draft night — a Day 2 grade — and DAL took him at No. 28. The model's case leans on broad top-100 board coverage and scout consensus. Bust risk projects at 3%, below the position median — the model has a tight grade. The room had him #21 pre-draft; our board sat 13 spots lower.

Written from the live model's numbers — projected to round 2, and it updates whenever the model does. See methodology for what drives the take.

Draftanomics Pick?
#34
Day 2range #8–#138 · volatile
Bust Probability?
3%
0.09× EDGE / DL / LB class avg (27%)
safer than class avg
Model trust: MODERATE
Actual NFL Pick?
#28
DAL · Rd 1
Year 1 Outcome?
6.0
99% snap share
Career outlook

Career outlook

How this is built →
5-year career arc
Elite
10%[10–11]
Bust
18%[16–19]
Starter
49%[48–50]
Role
23%[22–24]

Read the two ends and skim the middle: the model has a real track record telling stars and busts apart, but “solid starter vs. rotation guy” is close to a coin flip from public data — that's why those two bars are grayed. For his odds of outright busting, the Bust-risk panel next door is the number to trust.

The bracketed ranges show how far each number could reasonably move — they come from how 23–57 similar players in past drafts actually turned out.

Projected second contract
$3.4M($0M–$12.8M)/yr model
Role player / rotation contract
Bust risk
3%
from a model with a graded track record at this positionsecond opinion: 1 of 5 closest historical comps busted (20%)
Public-board consensus

27 public boards track this prospect. Per-board breakdown loads with the live board.

Pin a team in your account to see how this prospect fits your roster + cap.
Scout note
Private to this device — saved to your browser, never sent to a server.
Empty notes are auto-deleted.
Verdict
Aligned
Gap (actual − predicted)
-6

Film

Highlight reels indexed from YouTube. Loads only when you press play.

Working in his favor: how many boards rank him top-100, scout consensus, and how many boards rank him top-50. Nothing in the profile pulled the grade down.

Scout consensus
+0.05
Positional consistency
-0.03
Age
+0.02

Model read

Model grade
0.69 of 1
Confidence?
99%
Predicted round
2

The grade is the 0-to-1 score the board sorts by — it only means something next to the rest of this class, which is why the rank above it is the number to quote.

Pulling the boards…
Mock-draft consensus
Pulling the mocks…
4-tier outlook?
Starter
Model expects a solid starter career
Model trust: MODERATE
Elite
10%
Starter
49%
Role
23%
Bust
18%

Outcome shares from the 4-tier model. The Bust share here is a different model than the headline bust probability — for bust risk, use that number.

Career trajectory + forecast

Solid points = actual NFL snap share per season. Dashed extension = forecast for upcoming years.

0%25%50%75%100%Y1Y2Y3Y4
Actual Forecast (comp-based)
Risk dashboard

Risk profile is clean

Risk score12· CLEAN

Everything that could go wrong with Taco Charlton, gathered in one place — the most serious flags listed first.

  • Predicted-pick range#8–138 · 130-pick spread
    The model's own projections scatter widely for this prospect — the landing spot is genuinely uncertain.
  • Bust probability3%
    Low bust risk by the model's read.
  • Age22.5 yrs
    Within the typical EDGE draft-age band (~23.5).
  • Public-board coverage27 sources
    Plenty of public boards have a read — the grade is well corroborated.

Case for / case against

Named, concrete signals — every flag cites numbers, comp players, or schedule context.

Reasons to fade
No risk flags raised.
Reasons to buy
Strong comp group
high
4 of 4 closest comps with NFL outcomes became Starters or Franchise players: Shane Ray, Leonard Williams, Danielle Hunter (+1 more). The historical neighborhood overwhelmingly produced NFL contributors.
Scheme context
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Teams likely to draft

Based on each team's roster depth at EDGE / DL / LB, age, and recent capital invested.

NE#1 fit
Need at positionComfortableQuality starters10Roster spots short0Recent picks spent hereLittle
KC#2 fit
Need at positionComfortableQuality starters8Roster spots short0Recent picks spent hereLittle
NO#3 fit
Need at positionComfortableQuality starters9Roster spots short0Recent picks spent hereLittle
TB#4 fit
Need at positionComfortableQuality starters10Roster spots short0Recent picks spent hereLittle
SF#5 fit
Need at positionComfortableQuality starters9Roster spots short0Recent picks spent hereLittle

Historical comps

Side-by-side with top comps →

Closest historical matches among prior EDGE / DL / LB prospects who were drafted, by overall statistical profile. A smaller distance means a closer match.

PlayerPosYearPickSnap trajectoryCareer arcDistance
Shane RayEDGE2015#23
↑4 pts
Franchise1.44
Geneo GrissomEDGE2015#97
↓16 pts
Contributor1.58
Leonard WilliamsEDGE2015#6
→0 pts
Franchise2.06
Danielle HunterEDGE2015#88
↑8 pts
Franchise2.38
Owamagbe OdighizuwaEDGE2015#74
↓22 pts
Starter2.64
Scout reports
Paste in any scouting report you trust; Draftanomics pulls out the concrete claims so you can weigh them against the model on the same page.
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