| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| VCU wins by over 10.5 Points | 0% | 11¢ | 19¢ | — | $0 | Trade → |
| Dayton wins by over 14.5 Points | 0% | 6¢ | 13¢ | — | $0 | Trade → |
| VCU wins by over 4.5 Points | 0% | 30¢ | 37¢ | — | $0 | Trade → |
| VCU wins by over 13.5 Points | 0% | 5¢ | 14¢ | — | $0 | Trade → |
| Dayton wins by over 8.5 Points | 0% | 22¢ | 28¢ | — | $0 | Trade → |
| VCU wins by over 1.5 Points | 0% | 42¢ | 47¢ | — | $0 | Trade → |
| Dayton wins by over 2.5 Points | 0% | 43¢ | 49¢ | — | $0 | Trade → |
| Dayton wins by over 11.5 Points | 0% | 13¢ | 20¢ | — | $0 | Trade → |
| VCU wins by over 16.5 Points | 0% | 3¢ | 9¢ | — | $0 | Trade → |
| Dayton wins by over 5.5 Points | 0% | 32¢ | 37¢ | — | $0 | Trade → |
| VCU wins by over 7.5 Points | 0% | 19¢ | 26¢ | — | $0 | Trade → |
This market lets traders take positions on the point-spread outcome for the college basketball game VCU at Dayton; it matters because the spread captures collective expectations about which team will cover the margin. Market prices summarize real-time information and sentiment about the game.
VCU and Dayton are conference opponents with different typical styles: VCU has recently been known for aggressive defense and pressure, while Dayton often leverages home-court comfort and structured offensive sets. Both programs have had competitive seasons in recent years, so matchups, recent form, and roster continuity are important context for this game.
In this context, market prices express the consensus view of traders about which side will cover the spread and by how much; prices move as new information (injuries, lineups, travel, news) is incorporated. Treat the market as a dynamic aggregator of relevant game-day information rather than a static prediction.
The market close is listed as TBD; typically spread markets close near the official game start or at a time specified by the exchange. Check the KALSHI platform for the definitive close time and any last-minute changes.
The 11 outcomes correspond to distinct spread results or margin buckets (different ways the game margin can fall relative to the spread). They let traders take positions on a range of possible margins rather than a single binary cover/no-cover outcome.
Monitor official team injury reports, coach press conferences, and verified lineup confirmations. Significant changes to starters or expected minutes (especially primary ball handlers or scorers) tend to move spread markets quickly; adjust positions only after confirming sources.
Primary scorers, the starting point guard (who controls pace and turnovers), and defensive/rebounding anchors usually have the largest impact. Also watch any bench players who have been logging increased minutes or sudden scoring bursts.
Head-to-head history and home performance are useful context but should be weighed alongside current-season form, roster changes, and situational factors (injuries, travel). Recent trends and up-to-date team health often provide stronger signals than older matchups.