2026 Busts: Early Picks Our Model Fades

What the fade selector does

Every fade on this page starts from one gap: how far below current ADP our model ranks a player. Say the market takes someone at pick 40 and our board has him 80th overall. That's a 40-spot reach, and it qualifies for this list. We flag anyone our model ranks 15 or more spots later than his ADP, inside the top 60 picks.

Past pick 60, the gap stops mattering. Replacement-level players swap places every week of August, and calling that swap a fade is noise wearing a headline. Both cutoffs, the 15-spot gap and pick 60 itself, are v1 judgment calls, not backtested constants — the same disclosure standard the values list holds itself to. If we retune either number, this page says so.

The rank side of that gap comes from the same board as the rest of the site: value over positional baseline rather than raw projected points, built by the three-step pipeline on the methodology page. That distinction matters more here than anywhere else on the site. A fade is a claim that the model is right and the market is wrong, and you should know exactly what the model means before you spend a mid-round pick believing it.

Here's this run's full reach list, recomputed against live ADP on every visit:

The two populations

Two very different situations land a player on that list, and the table above can't tell them apart. Call the first population type-A. These are the honest fades: established players with two full, stable seasons behind them, the case the model reads best. When one of those players still prices below ADP, the market is paying for a name more than a role, and the gap should change how you draft him.

Terry McLaurin is the worked example of the check, not a claim about today's list: a veteran receiver the market pays partly on name recognition. Before you file him as type A, open his player page from the card and count his 2025 games; a short last season moves him to the second population, however long his career. He is also a wide receiver, the one position our backtest lost to a simpler baseline, so run check three twice there. The number is on the methodology page.

When a card passes that check, that's the fade worth respecting on draft day, the rare case where the model's read and years of tape agree against the market.

Call the second population type-B. These are the model's blind spots. Here's the mechanism.

Our per-game rates come from a player's last two seasons, weighted toward the more recent one. That's the same pipeline the methodology page walks step by step. A separate games-played prior, built from recent availability, turns those per-game rates into a season total. A player whose most recent season was thin on games gets hit twice by that design: once in his per-game rate, again in the games prior that stretches or shrinks it into a full year.

Joe Burrow is the clearest worked example of the type, not a claim about today's list. Our board prices him off a thin 2025 sample and the games prior that season creates, with no way to update either one. Rashee Rice and Malik Nabers fit the type for the same reason: a thin 2025 the model still weights heavily, through the games prior if not the rate, whatever the reason behind it.

Read that number as a blind spot, not advice. Our rank reflects a thin sample and nothing else; it has no separate view on where he stands right now. If you have that view, it's worth more than our rank, because the board has no input that could change its mind.

Omarion Hampton shows a related but different blind spot. He has a single NFL season on record, and the model weighs it by its games, pulling it toward a bottom-quartile rate for the position harder the fewer games it holds, the rule the methodology page lays out. The market can price a depth-chart promotion or an expanded role the model has no input for. That gap is the model being honest about what it doesn't know, not a verdict on Hampton himself.

How to tell which is which

You don't need our internal notes to sort a fade list into its two piles. Three checks do most of the work.

First, check whether last season ended early for him or his role just changed. An early end means the model is weighting a thin sample; a changed role means it is still pricing the smaller role he had. Either way, the market's read outweighs ours right now.

Second, count his 2025 games on his player page. A short 2025 hits his projection twice: that season's rate is pulled harder toward a bottom-quartile rate for the position, or, under four games, dropped in favor of 2024 when that season qualifies, and the games prior still weights 2025 at 70% (85% for receivers), so the model projects most of that missed time again.

Third, ask whether his last two seasons were both full and stable. Those two seasons are all the model reads, so two full ones are its best case, and a fade that survives it deserves real weight.

The methodology page names the rookie rule as a real limitation and shows how short seasons are discounted. This section is that same limitation, aimed at one list. Sorting the two piles is the edge this page exists to hand you.

Using fades at the table

A fade only pays off if you act on it at the table, not just in your notes app.

Don't pay ADP for a type-A row. When two full, stable seasons and the model agree that a player is priced on reputation, let someone else spend that pick. Take the discount waiting at this run's ADP values instead, or the next name on the full rankings. Those reputation fades are the cleanest edge on this list.

Type-B rows need the opposite discipline. If a name is on this list only because of a thin, shortened, or rookie-adjacent 2025, the market's price is doing better work right now than ours is. Draft him at ADP if you'd have wanted him anyway, and don't let our rank talk you out of a player you already trust. Expect our board to keep looking wrong on those names until the season settles them.

That gap closes in the weekly numbers, which come from a game-level model reading each week's actual scoring since Week 1. On the draft side, pair this list with the draft strategy guide or how to win your league guide for how one overpriced pick fits into the rest of your draft.