How the blend works

Two independent views of the same week, and why combining them beats trusting either alone.

The problem with trusting one source

DFS pick'em sites like Underdog and PrizePicks publish a projected fantasy-point total for every player, every week. Sportsbooks and real-money prediction markets like Kalshi publish betting lines and contract prices (passing/rushing/receiving yardage props, anytime-touchdown odds, game totals) that imply their own view of how a player will perform. Both are independently pretty good at this. They also don't always agree.

When two differently-built systems (one a projections desk, one a real market where people bet real money) land on similar numbers, that agreement is a stronger signal than either alone. When they disagree, that disagreement is informative too: it usually means real uncertainty (a banged-up offensive line, a tough matchup one side is pricing in that the other missed) rather than one side being simply wrong. This site blends the two into a single expected-points number.

Two inputs

DFS Projections

Underdog, PrizePicks, and Betr Picks projections, already scored in fantasy points and averaged together.

Sportsbook & Market Odds

Real player-prop lines and odds from US sportsbooks (via The Odds API) and real-money prediction-market contracts (Kalshi), converted into an expected fantasy-point total using the market's own implied probabilities.

How they become one number

1

DFS Projection

Average the projected points across every DFS source that's posted a number for that player this week.

2

Sportsbook Projection

Convert each betting market into points, using your league's scoring rate (half-PPR by default: 0.04 pts/passing yard, 0.1 pts/rushing or receiving yard, 0.5 pts/reception). A yardage or reception line becomes an expected-value estimate from the market's own quoted probabilities at every threshold a book offers, not just the single headline number. Touchdown odds are converted from betting odds into an implied probability and multiplied by the points a touchdown is worth. Kalshi's real-money prediction-market contracts price the same questions directly as a probability and are pooled in alongside the sportsbooks, not shown as a separate number. Game total and spread are shown for context (blowout risk, game script) rather than folded directly into the estimate.

3

Blended score

Average the DFS Projection and Sportsbook Projection. If only one side has data for a player, that side is used on its own rather than showing nothing.

A real example

This week's highest Half PPR blended score belongs to Josh Allen (QB · BUF). Here's how that number was built:

23.48 DFS projection
25.63 Sportsbook projection
24.55 Blended

See the full per-market breakdown →

This is v1

The blend above is a straightforward, transparent starting point: a plain average, not a fitted model, deliberately simple so every number on this site can be traced back to a real market or a real projection you can click through and check. Refining the weighting between DFS and sportsbook sources using real results, and eventually rebuilding a start/sit call against real league rosters, are explicit next steps, not one-time decisions.