TOTAL VOLUME:
$134.1b
24H VOL:
$113,466,932
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,423,222,590
402,751
Markets across
30,217
events
MATCHED EVENTS:
2,632
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
Closed: Jun 7, 2:00 AM EST
Kalshi
The daytime high temperature in Minneapolis on June 6, 2026, will be recorded by the National Weather Service.
On Kalshi, the highest temperature in Minneapolis on June 6, 2026, is priced through binary or range-based outcome contracts. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Traders buy and sell shares corresponding to different temperature thresholds, with prices reflecting the implied probability of each outcome. As new information emerges—such as seasonal forecasts or atmospheric patterns—traders adjust their positions, moving prices up or down. The market price at any moment represents the collective belief of active traders about which temperature range is most likely to occur on that specific day.
The market resolves on Jun 7, 2026, after the highest temperature in Minneapolis on June 6, 2026, has been recorded and verified. The outcome is determined by the actual peak temperature reached that day in Minneapolis, as measured by official weather data sources. Once the day concludes and the final high temperature is confirmed, the market settles according to which outcome bracket or contract specification the actual temperature falls into, and traders' positions are paid out accordingly.
Several factors could shift market odds for Minneapolis's high temperature on June 6, 2026. Seasonal climate patterns and long-range weather forecasts released closer to the date will influence trader expectations significantly. Major atmospheric systems—such as heat waves, cold fronts, or unusual jet-stream positioning—could alter the probability of extreme temperatures. Additionally, historical temperature records for that date and broader climate trends may prompt traders to adjust positions. As June 6 approaches, short-range meteorological models will become more precise, likely triggering sharp market movements as traders react to refined forecasts.