| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Colorado wins by over 1.5 goals | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Washington wins by over 1.5 goals | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Washington wins by over 2.5 goals | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Colorado wins by over 2.5 goals | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks how the point spread for the Colorado at Washington matchup will resolve; it matters because the spread summarizes market expectations about which team will outperform the other and by how many points.
Colorado at Washington is a head-to-head sports contest between the two schools’ teams; bettors and analysts use spreads to express and trade views on relative strength rather than just picking a winner. Historical matchups, venue, coaching matchups, and roster changes all provide context that shapes expectations for this particular game.
In a spread market, quoted odds reflect the aggregated view of traders about which side will cover the listed margin; those odds move as news (injuries, lineup changes, weather) and new information arrive.
Resolution follows the platform’s settlement rules—many prediction markets void or cancel markets that do not reach completion within a specified timeframe and return funds, but you should check the KALSHI market page for the exact policy that applies to this event.
Close times are set by the market operator and can vary; often spread markets close at or just before the scheduled start of the game, but confirm the specific close time on the KALSHI event page since this market is marked TBD.
Most spread markets use the official final score, including any overtime periods, for settlement; verify the KALSHI settlement rules on the event page to confirm how this market handles overtime.
Late injury reports can move the spread quickly because they change expected on-field performance; traders typically reassess starting lineups and depth, and the market price will adjust to reflect the new information as it becomes public.
Head-to-head history can highlight tendencies and matchup patterns, but recent form, roster changes, coaching, and situational context (home/away, weather, injuries) are usually more predictive for the upcoming game; use historical results as one input among several.