Medallion Engine

The name refers to a method, not a track record. The quantitative style this engine imitates has a few defining habits, and all of them are visible in the code:

Many weak signals, not one strong opinion. No single factor here has meaningful predictive power alone. Fifteen of them, standardized and combined, do. Look at the weight chart — nothing dominates, and that is the design working.

Fit the weights, do not assert them. Every weight above came from ridge regression on this season's actual results. Ridge rather than plain least squares because football factors are badly collinear — target share, air-yards share and route rate all measure the same latent thing.

Trade the difference, not the level. The output that matters is edge, not projection. Everyone knows the best player is the best player; that is priced in.

Never look ahead. Training windows end strictly before the target week. It is trivially easy to build a model with a 0.9 R² by leaking one same-week statistic, and equally easy to lose money with it.

Where the market baseline comes from. There is no free consensus-projection feed, so “the market” is reconstructed from Sleeper's search rank — a genuine crowd artifact built from what millions of managers actually look up — and mapped onto the model's own positional scoring curve so that points are compared to points. A consequence worth knowing: when the crowd and the model rank a player identically, his edge is exactly 0.0. That is not a missing value. It means the two disagree about nothing, which is the correct answer for most of the top of the board.

What is not claimed: any resemblance in returns. This is a fantasy football projection system. The honest expectation is a small, persistent edge over consensus — visible on the Backtest Desk, where it is measured against a dumb three-game average that is much harder to beat than most people assume.