Kalshi F1 Points Model Trader

This is a template.
The default signal uses static points standings and driver ratings to Monte Carlo simulate the remaining season -- remix it with live F1 API data, qualifying pace analysis, or weather-adjusted race models.
The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

F1 Drivers Championship markets on Kalshi price each driver's chance of winning the title. This skill runs Monte Carlo simulations using current points standings and driver skill ratings to compute fair win probabilities, then trades when the market diverges from the model.

Key advantages:

• Points standings are public -- no proprietary data needed
• Monte Carlo captures non-linear dynamics -- points gaps, remaining races, and driver variance
• Driver ratings provide edge -- market often misprices mid-field drivers

Signal Logic

Points-Based Monte Carlo Model