| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| San Jose St. | 4% | 3¢ | 4¢ | — | $26K | Trade → |
| Colorado St. | 97% | 96¢ | 97¢ | — | $5K | Trade → |
This market trades the outcome of the college football game Colorado St. at San Jose St., letting participants express expectations about which team will win. It matters because market prices aggregate public information and react to news such as injuries, lineup changes, and weather; the market has two outcomes and shows $30,874 in total volume traded.
Both programs are Mountain West Conference members, so this game can affect conference standings and bowl positioning; recent seasons, recruiting cycles, and any coaching changes provide useful context for assessing matchup strength. Historical head-to-head results and turnover in key positions (especially quarterback play) shape preseason expectations. Midseason factors such as momentum, injuries, and schedule difficulty can shift the balance quickly.
Prediction market prices summarize collective expectations about the game outcome and will update as new public information arrives; treat them as a dynamic indicator rather than a static forecast. Large price moves often coincide with official injury reports, lineup announcements, or late-breaking news close to kickoff.
This market lists two mutually exclusive outcomes corresponding to which team wins the official game result; contracts resolve based on the game's final official score as recorded by the sanctioning authorities and the platform's rules.
The event page currently shows the close time as TBD; on KALSHI, markets for single-game outcomes typically close at or shortly before official kickoff, but you should confirm the exact closing time on the platform or in any event notices.
Prioritize official injury reports, coach press conferences, and final depth charts—losing a starter, especially at quarterback or on the defensive line, can materially change expected outcomes and often triggers significant market adjustments.
Home-field factors include crowd support, travel fatigue, and familiarity with the playing surface; Colorado State’s home altitude is a factor when opponents travel to Fort Collins, but when CSU travels to San Jose the altitude advantage is neutralized—consider recent travel patterns and rest when assessing impact.
Useful metrics include recent head-to-head trends, offensive/defensive efficiency, turnover margin, third-down and red-zone conversion rates, special teams performance, injury histories, and situational splits (home vs. away, rest days, and strength of recent opponents).