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NASA has been collecting global temperature data since 1880.Someone just turned 146 years of it into a Polymarket edge machine.$531,472 total net profite.19,267 predictions placed.The tool? 30 lines of Python. Linear regression. A normal distribution. Public data anyone can download for free.Here's the exact logic:The market trades temperature anomaly buckets - six slots, each 0.05°C wide. Most traders guess. This wallet calculates.> Step 1. Pull NASA GISTEMP April column. 146 data points going
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> NASA publishes the temperature anomaly every month> Polymarket trades it across six buckets> between them sits a problem linear regression solves cleanly> Mac Mini. Claude Code. 30 lines of Python.> μ = model prediction. σ = residuals.> P(bucket) = Φ((b-μ)/σ) - Φ((a-μ)/σ)> model says 56%. market trades at 48%.> EV = 0.56 - 0.48 = +0.08 per share.> edge isn't in the regression. it's in who sees fresh data first.
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I built a 30-line Python weather bot for PolymarketMost guess April 26 temps - I don’t> NASA GISTEMP data since 1880> Filter April column> Post-1970 linear regression (y = m·x + b)> μ prediction residuals → σ> Normal CDF> exact probability for every bucket (1.15-1.19, 1.20-1.24 etc.)Then ENSO correction on top so La Nina doesn’t destroy the forecastMarket prices one bucket at 48%Model says 56%. Instant +EV.This is the baseline. Real edge starts here.Bookmark this thread and save it
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