Average draft position is the closest thing fantasy football has to a betting line — it is the market’s price for every player, expressed in draft slots instead of dollars. And like any market, it is not efficient everywhere. Some stretches of the draft systematically cost more than the expected production they return, and others hand you a starter at a discount. The difference between those stretches is what our draft kit calls a value tier, and it is the single most useful way to draft against the market rather than with it. This post lays out the four value tiers our projection model sees in the 2026 draft, and links to the live rankings board so you can see the current names and numbers in each one.
Before the tiers, the framing: projected points come from the same player_feature_store stack that powers the live rankings — the numbers are not invented for this article. ADP is the market’s current average slot. A value tier is simply a band of the draft where the projection-versus-ADP relationship is consistent. Where the model outranks the market, you are in a value zone. Where the market outranks the model, you are in an overprice zone. The foundational version of this framework lives in our cornerstone ADP value tiers post; this is the preseason-updated read.
Round 1–2: the elite tier is efficient, mostly
The very top of the draft is the most carefully studied stretch in fantasy, and the model tends to agree with ADP within half a tier on the top group. Getting the elite names right is structural value — securing two top-12 finishers is more valuable than chasing a mid-draft sleeper. The rare mismatch here is about player type, not talent: the model at the margin prefers pass-catching backs and target-hog receivers over touch-volume backs in uncertain committees. If you are picking late in round one, the highest expected-points names the model has slightly ahead of their ADP are where the quiet top-tier edge sits — visible on the live board when you sort by model rank.
Rounds 3–5: the overprice zone
This is the most inefficient stretch of the draft — the Zone 2 where name-brand and last-season memory inflate price above projection. Round 3 and 4 RBs and "second WR on a great offense" types routinely go a round ahead of where their projected points belong. Our cornerstone post shows the hit-rate math here is rough on consensus: many of these picks do not return a top-24 finish. The live board is where you spot the overprices before draft night — every name whose model rank sits a full tier below his ADP is a fade candidate, exactly as the model vs consensus guide describes.
The scatter shows where production actually clusters relative to targets in our stored history — the relationship the market approximates with a name and a round. The players the market consistently overprice are the ones whose big-name production was a peak, not a baseline.
Rounds 6–10: tier breaks beat single names
The middle rounds are where construction beats evaluation. Which exact player you draft at pick 75 matters less than whether you have organized your build around the structural needs of your league — PPR, TE premium, superflex. Inside a value tier, the six-to-eight players are near-interchangeable, so the right move is to take the top of whatever tier you are in and let the draft come to you. This is also the cleanest place to deploy the "second-bite TE" or late-round streaming-QB strategies, both covered in our TE premium and QB streaming posts.
The worst mistake in this band is reaching through an entire tier to chase one name. If a player is the clear top of his tier, one pick early is fine; if he is priced a round ahead of the tier, a comparable projection will be there next round. Drafting the tier, not the story, is what separates a good middle round from a bad one.
Rounds 11+: the discount zone
The final band is where the model produces its most consistent above-ADP value, because it is where the market gets bored and starts drafting on vibes. The recurring cheap-pick archetypes — year-2 receivers with rising target share, backup RBs with a path to a vacated role, rushing-floor streamable QBs — are the exact sleepers developed in our sleepers by model post. The hit rate on any single late pick is low, but the cost is so cheap that one hit pays for several misses. Historically, a meaningful share of late-round picks finish top-24 at their position — and those are the picks that win leagues.
The bar chart shows the ceiling side of this zone: the players who have the single-week pop to win a week. The model’s discount-zone sleepers are the cheap names with this kind of ceiling and a capped floor — a combination you can only identify when you compare projection to price side by side.
How to draft the tiers, not just read them
Reading value tiers is only the first step; using them is the whole game. Three habits make the framework operational:
- Draft in the value zones, not against them. When the model and the market disagree, side with the projection where the gap is a full tier or more. That is real edge, not noise.
- Respect your scoring format. PPR changes the tier shape more than anything else. The live board respects your chosen format, and the draft kit emits a format-specific cheat sheet.
- Let the draft come to you in the stacks. Inside a tier the players are interchangeable; across a tier they are not. Reach within, never through.
The cleanest way to put this into practice on draft night is the draft kit cheat sheet — it sorts the projection stack into tiers and gives you a PPR, half-PPR, and standard tab, so the value zones are visible in the format you actually play. Pair it with the live rankings for the current board and the RB1 hit-rate backtest for the early-round risk, and you will consistently outdraft rooms that are pricing on reputation instead of projection.
Value tiers are decision support, not a guarantee. Re-check the live board and your league scoring before you pick.
DFS projected ROI vs ownership %
Projected GPP ROI multiplier vs projected ownership across simulated lineups. Sub-10% leverage plays compound when they hit; chalk plays cap your upside even when the projection is dead-on.
Prop OVER hit rate vs line distance from median
Empirical hit rate of OVER bets as the prop line moves away from the player projection median, measured in standard deviations. A line set 1sd below the median hits ~84% of the time — but books price the juice to match.
