Highest temperature in Minneapolis on May 29, 2026?

Prediction market odds on Kalshi reflect real-money trader consensus and often incorporate meteorological forecasts, historical weather patterns, and seasonal climate data. Unlike traditional analyst forecasts, which rely on models and expert judgment, prediction markets aggregate distributed information through price discovery. Comparing Kalshi implied probabilities to National Weather Service outlooks or climate models can reveal whether traders are pricing in more optimistic or pessimistic temperature scenarios than official forecasters expect for Minneapolis on that date.

On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. On Kalshi, the highest temperature outcome for Minneapolis on May 29, 2026, is priced as binary or range-based contracts reflecting trader expectations. Each contract price represents the implied probability that the actual high temperature will fall within a specified range. Traders buy contracts they believe are underpriced and sell those they view as overpriced, with prices converging toward the true probability as new information arrives. Volume and liquidity on Kalshi determine how easily traders can enter or exit positions.

The market resolves on May 30, 2026, after the highest temperature for Minneapolis on May 29, 2026, has been recorded and verified. Resolution is determined by official temperature data from a designated meteorological source, ensuring an objective and auditable outcome. Traders' positions settle based on whether the actual high temperature matches the outcome they backed, with payouts distributed accordingly to winners and losers.

Several factors could shift odds for Minneapolis's May 29 high temperature. Major weather pattern changes, such as shifts in jet stream positioning or the development of high-pressure systems, would move markets significantly. Updated seasonal forecasts, El Niño or La Niña conditions, and historical temperature anomalies for late May in Minnesota all influence trader expectations. As the event date approaches, short-range weather models become more reliable, typically causing sharper price movements. Real-time atmospheric data and any unusual climate events in the weeks prior will drive trading activity.