Highest temperature in Moscow on July 7?

Prediction market odds and traditional meteorological forecasts serve complementary roles. Weather analysts rely on atmospheric models, historical data, and satellite imagery to project temperature ranges, while this market aggregates the real-time beliefs of traders who have financial incentive to price outcomes accurately. Market odds often incorporate analyst consensus but can diverge when traders identify model uncertainty or expect unusual conditions. Comparing the implied probability from this market to published forecasts from national weather services reveals where the crowd sees edge or disagreement, making both sources valuable for understanding expected outcomes on July 7.

On Polymarket, traders set prices through an automated market maker that adjusts odds based on buy and sell pressure. On Polymarket, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Each temperature outcome is represented as a separate contract, and the price of each reflects its implied probability—higher prices mean the market views that outcome as more likely. Liquidity pools allow traders to enter and exit positions continuously, and the spread between bid and ask prices tightens as volume increases. Real-time price discovery means odds shift instantly when new weather data or model updates reach the market.

This market resolves around Jul 7, 2026, once July 7 has passed and the highest temperature recorded in Moscow that day is confirmed. The outcome is verified against credible public sources to determine which temperature band or specific value was reached. Traders holding contracts matching the verified result receive their payout, while other positions expire worthless. The resolution process typically completes within hours or a day after the event, allowing quick settlement and payoff distribution to winning participants.

Weather model updates are the primary driver of price movement in this market. Major shifts in seasonal forecasts, atmospheric pressure systems, or unexpected climate patterns can trigger rapid repricing as traders adjust their bets. Real-time meteorological alerts, changes to long-range forecasts from major weather agencies, and historical temperature anomalies for early July all influence trader sentiment. As the event date approaches, intraday forecasts become more precise, typically narrowing the range of expected outcomes and concentrating liquidity around the most probable temperature band. Breaking news about unusual weather events or heat waves in the region can also spark sudden volatility.