What will US gas prices be on July 13, 2026?

Prediction market odds reflect real-money bets from traders who profit or lose based on accuracy, creating strong incentives for honest price discovery. Analyst forecasts, by contrast, rely on models and expert judgment but lack direct financial accountability. This market aggregates dispersed information from thousands of participants, often capturing shifts in sentiment faster than traditional surveys. Comparing the implied probability here to published analyst expectations can reveal where the crowd sees upside or downside risk relative to expert consensus.

On Kalshi, this market is priced through a continuous order-book mechanism where buyers and sellers post bids and offers, and trades execute when orders match. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. The price of each contract reflects the crowd's collective belief about the likelihood of the outcome, ranging from near-zero to near-100 cents per share. As new information emerges—supply disruptions, demand shifts, geopolitical events—traders adjust their positions, moving the price in real time and signaling changing expectations.

This market resolves around Jul 13, 2026, at which point the outcome is confirmed against credible public reporting of actual US gas prices for the week. The specific price level or range that determines a win or loss is defined by the market's terms at creation. Once the resolution period closes and verified data is available, the market settles automatically, and traders' profits or losses are finalized based on whether their positions matched the actual result.

Major catalysts for this market include supply shocks (refinery outages, pipeline disruptions), geopolitical tensions affecting crude oil, inventory reports from the Energy Information Administration, and shifts in global demand. Seasonal factors, hurricane activity in the Gulf of Mexico, and unexpected policy announcements can also drive sharp repricing. Traders monitor these signals closely and adjust positions ahead of data releases, so anticipation of any of these events often moves odds before the actual news arrives.