Weather Edge Tool
Live NWS forecast vs. Kalshi temperature markets. Warm-bias corrected normal distribution → best play, EV, and Kelly sizing.
FREE · NICHE EDGE
Yes, you can bet on the weather — and win.
What is this?
Kalshi runs markets on weather events — temperature thresholds, snowfall totals, storm frequency. Most people ignore these. That's exactly why they're worth looking at. Thin markets with less sophisticated competition = more mispricings.
If you live in a city and pay attention to weather patterns, you potentially have a local edge over the aggregate market. A NYC resident who watches the NOAA forecast closely might beat the market on NYC snow totals consistently.
Real-World Example
→ Local Knowledge Edge
Kalshi has "NYC gets more than 3 inches of snow in February" at 38¢. You check NOAA's extended 10-day forecast — there's a Nor'easter system forming that the market may not have fully priced.
You buy YES at 38¢. The storm delivers 7 inches. Market settles at 100¢. That's a 2.6x return on a weather call — because nobody else was paying attention to the forecast.
✅Action: Watch NOAA 7-day forecasts and compare to Kalshi weather market prices. Your local knowledge is your edge.
Bottom line: Thin, ignored markets = more inefficiency = more edge for the prepared bettor.
Full guide →Sample Read — Denver, CO
Denver, CO
High > 72°F
NWS is forecasting 76°F in Denver but the Kalshi market is pricing a 42% chance it clears 72°F. Our model puts that at 51%. That's a 9-point edge — buy YES, quarter Kelly.
Live Edge — Today's Best Play
Related Tools
Kalshi Weather Markets — Where the Edge Lives
Kalshi runs daily high-temperature threshold markets across 13 major U.S. cities. Each contract resolves YES if the official NWS observed high for that city clears a specific strike — like “Denver high above 72°F.” The market price is the crowd's implied probability. The question is whether that crowd price is right. We deliberately ignore the narrow bucket (range) markets Kalshi also lists — their windows are too tight, their liquidity is split four ways, and the maximum reachable edge is small. Threshold markets give the cleaner signal.
The model uses a simple but effective approach: take the NWS 24-hour forecast high as the center (μ) and fit a normal distribution with sigma (σ) derived from 30 years of NOAA climate data for that city and month. That gives a clean probability for any temperature threshold — no guesswork, just statistics. When the model probability diverges from the Kalshi price by 5+ percentage points, that's the edge.
Why weather markets are tradable
Temperature forecasts are among the best-validated probabilistic forecasts in the world. NWS day-1 highs are accurate to within 3–4°F roughly 80% of the time. Kalshi's temperature markets, on the other hand, are set by retail traders who often anchor on round numbers and don't correctly account for forecast uncertainty. That's the gap. The model exploits it systematically.
Sizing the trade
The tool outputs quarter Kelly as a default sizing recommendation. Full Kelly is aggressive for any single market — a quarter of that gives you a sustainable bankroll fraction that survives variance without blowing up. Pair the edge signal with the Kelly Criterion Calculator to dial in your exact position size.
What the engine scans
The tool live-computes on every page load. It pulls the latest NWS forecasts for Denver, New York City, Chicago, Los Angeles, Miami, Phoenix, Austin, Atlanta, Philadelphia, Boston, Seattle, Dallas, and San Antonio — matches each city to its active Kalshi threshold markets, runs the normal distribution model, and scores each edge by magnitude × log(volume). The highest-scoring play with edge ≥ 5pp becomes the best play. The Discord alert pipeline runs twice daily (4:15 AM ET and 4:15 PM ET) right after NWS forecast updates and posts qualifying plays to #premium-alerts (≥8pp) and #oracle-picks (≥12pp).
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