Weather Edge Gaussian Probability Model

This bot exploits overpriced NO sides of temperature markets on Polymarket. It gathers live METAR observations and Open-Meteo forecasts to estimate the probability distribution of daily high temperatures at specific locations. It uses a Gaussian probability model to calculate the fair probability of the temperature staying below the market's threshold. The bot enters a NO position when the market price exceeds the model's calculated probability by a margin. Exit is at expiration when the outcome is determined. The repo has 5 stars and is actively updated, suggesting some community interest. Implementation is in Python and runs as a paper-trading bot. The edge comes from more accurate weather probability modeling than the market prices in. Risks include forecast errors, extreme weather events, and location-specific microclimates not captured by the model.