| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Kansas St. | 7% | 6¢ | 7¢ | — | $4K | Trade → |
| Kansas | 94% | 93¢ | 94¢ | — | $735 | Trade → |
This market trades the outcome of the Kansas St. at Kansas game—essentially which team wins the matchup. It matters because rivalry games can affect conference standings, postseason positioning, and short-term team momentum.
Kansas and Kansas State meet regularly across major college sports in a long-running in-state rivalry; both programs have distinct styles, coaching approaches, and fan intensity that influence single-game results. Recent form, injuries, and where the game is played (home vs. away) typically matter more than long-ago results, though historical matchup patterns can highlight matchup advantages.
Market prices summarize the beliefs of traders about which outcome is more likely and update as new information arrives; use prices to compare your own view with the market and to decide whether new information (injuries, lineups, weather) changes the expected outcome.
The listing shows the close as TBD; final close timing is set by the platform and often tied to the official game start—check the specific contract page or platform notifications for the definitive close time.
This is a two-outcome (binary) market corresponding to which team wins the game—one outcome for a Kansas State win and one for a Kansas win. Confirm the exact outcome labels on the contract page before trading.
Settlement normally follows the official final result as reported by the sport’s governing body, which typically includes overtime results; verify the contract terms on the platform to confirm how overtime is handled.
Monitor official injury reports and starting lineup announcements, any late scratches, travel or weather advisories (for outdoor games), and last-minute coaching statements—those items commonly move prices in the hours before kickoff or tip-off.
Head-to-head history provides context about long-term rivalry patterns, but prioritize recent performance, current rosters, venue, and matchup-specific stats—distant historical trends are less predictive of a single game.