TOTAL VOLUME:
$134b
24H VOL:
$107,351,958
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,416,970,024
400,720
Markets across
30,097
events
MATCHED EVENTS:
2,633
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
Closed: Jun 3, 2:00 AM EST
Kalshi
This event concerns the maximum temperature recorded in Minneapolis on June 2, 2026, as documented by the National Weather Service. The outcome will be determined by which temperature range the day's high falls within.
On Kalshi, the highest temperature in Minneapolis on June 2 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 or sell shares corresponding to specific temperature brackets, with prices reflecting the collective probability assigned to each outcome. As the event date approaches and weather models update, prices adjust to reflect new information. The market price of each outcome directly implies its probability; higher prices mean traders view that temperature range as more likely to occur.
The market resolves on Jun 3, 2026, after the highest temperature in Minneapolis on June 2, 2026, has been recorded and verified. Resolution is determined by official temperature data from a designated weather station or source. Once the actual high temperature is confirmed, the outcome corresponding to that reading is marked correct, and traders holding winning shares receive their payout. The exact resolution criteria and data source are specified in the market terms.
Several factors can shift odds for Minneapolis's June 2 high temperature. Updated seasonal climate forecasts and long-range weather models may signal warmer or cooler patterns. Real-time atmospheric conditions, jet stream positioning, and high-pressure or low-pressure systems developing in the weeks before June 2 will influence trader expectations. Historical temperature records and anomalies for early June in Minneapolis provide context. As the date approaches, short-range forecasts become more precise, typically causing sharper price moves. Unusual weather events or climate patterns elsewhere may also affect regional conditions.