Lowest temperature in Minneapolis on Jul 7, 2026?

Prediction market odds reflect real-money incentives for accuracy, often incorporating meteorological models and historical temperature patterns faster than traditional analyst consensus. While weather forecasters publish seasonal outlooks and daily predictions, this market aggregates trader beliefs into a single probability, which can diverge from any single analyst's point estimate. The continuous pricing mechanism means odds adjust dynamically as new data emerges, potentially offering a more responsive signal than static forecasts released on a fixed schedule.

On Kalshi, this market is priced through a continuous order-book mechanism where traders buy and sell shares corresponding to different temperature ranges or outcomes. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Prices move in real time as supply and demand shift, with the bid-ask spread reflecting uncertainty around the lowest temperature on that date. Traders profit by correctly predicting the outcome, creating strong incentives to incorporate all available weather data and historical patterns into their positions.

This market resolves around Jul 8, 2026, once July 7, 2026 has passed and the lowest temperature for that day can be verified from credible public sources. The outcome is determined by the actual recorded low temperature in Minneapolis on that date, confirmed through official meteorological records. All open positions settle based on which outcome bracket or range the verified temperature falls into.

Major weather pattern shifts, seasonal climate anomalies, and updated long-range forecasts can significantly move odds in this market. El Niño or La Niña conditions, polar vortex disruptions, and historical temperature records for early July all serve as key signals traders monitor. As the event date approaches, medium-range forecasts become increasingly reliable, typically causing sharper price movements. Additionally, any unusual atmospheric patterns or climate news could prompt rapid repricing as traders update their probability estimates.