Highest temperature in Manila on July 3?

Prediction market odds often diverge from traditional weather analyst forecasts because they incorporate real-time trader behavior, risk appetite, and information flow rather than relying solely on meteorological models. While meteorologists publish deterministic or probabilistic forecasts based on atmospheric data, this market aggregates the distributed knowledge of traders who may factor in additional signals—historical patterns, seasonal trends, or late-breaking weather updates. Comparing the implied probability from current odds to published forecasts can reveal where market participants see value or disagreement with consensus predictions.

On Polymarket, traders set the odds through an automated market maker that adjusts prices based on buy and sell volume. On Polymarket, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Each share represents a claim on a specific outcome—for instance, whether the highest temperature will be 27°C or below. The current odds reflect the latest trades and available liquidity; as more traders buy or sell, the price moves to balance supply and demand. This continuous repricing ensures the market price converges toward the true probability as new information arrives.

This market resolves around Jul 3, 2026, once July 3 has passed and the day's highest temperature in Manila can be verified. The outcome is confirmed against credible public sources that record the official peak temperature for that date. Traders holding shares in the winning outcome receive their payout, while losing positions expire worthless. Resolution typically occurs within hours or a day after the event, depending on data availability and platform processing.

Several factors could shift odds before resolution. Updated weather forecasts from meteorological agencies may indicate changing atmospheric conditions or seasonal patterns affecting Manila's temperature on July 3. Major weather systems—monsoons, tropical storms, or heat waves—could be flagged by forecasters weeks in advance, prompting traders to reassess probabilities. Real-time data closer to the event date, such as observed temperatures in the days leading up to July 3, often triggers sharp repricing. Additionally, historical temperature records and anomalies for that date may influence trader positioning as the market approaches settlement.