| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| UNLV wins by over 2.5 Points | 58% | 52¢ | 58¢ | — | $194 | Trade → |
| Wyoming wins by over 4.5 Points | 26% | 24¢ | 29¢ | — | $189 | Trade → |
| UNLV wins by over 10.5 Points | 29% | 23¢ | 29¢ | — | $164 | Trade → |
| UNLV wins by over 7.5 Points | 38% | 33¢ | 38¢ | — | $126 | Trade → |
| UNLV wins by over 4.5 Points | 49% | 45¢ | 49¢ | — | $117 | Trade → |
| UNLV wins by over 1.5 Points | 0% | 55¢ | 61¢ | — | $0 | Trade → |
| UNLV wins by over 19.5 Points | 0% | 3¢ | 11¢ | — | $0 | Trade → |
| UNLV wins by over 16.5 Points | 0% | 8¢ | 15¢ | — | $0 | Trade → |
| UNLV wins by over 5.5 Points | 0% | 40¢ | 45¢ | — | $0 | Trade → |
| Wyoming wins by over 5.5 Points | 0% | 20¢ | 25¢ | — | $0 | Trade → |
| Wyoming wins by over 2.5 Points | 0% | 30¢ | 35¢ | — | $0 | Trade → |
| Wyoming wins by over 1.5 Points | 0% | 33¢ | 39¢ | — | $0 | Trade → |
| Wyoming wins by over 8.5 Points | 0% | 12¢ | 19¢ | — | $0 | Trade → |
| UNLV wins by over 8.5 Points | 0% | 30¢ | 35¢ | — | $0 | Trade → |
| UNLV wins by over 17.5 Points | 0% | 6¢ | 13¢ | — | $0 | Trade → |
| UNLV wins by over 14.5 Points | 0% | 12¢ | 19¢ | — | $0 | Trade → |
| Wyoming wins by over 10.5 Points | 0% | 7¢ | 15¢ | — | $0 | Trade → |
| UNLV wins by over 13.5 Points | 0% | 14¢ | 21¢ | — | $0 | Trade → |
| Wyoming wins by over 14.5 Points | 0% | 3¢ | 9¢ | — | $0 | Trade → |
| Wyoming wins by over 11.5 Points | 0% | 5¢ | 14¢ | — | $0 | Trade → |
| UNLV wins by over 11.5 Points | 0% | 19¢ | 25¢ | — | $0 | Trade → |
| Wyoming wins by over 13.5 Points | 0% | 3¢ | 10¢ | — | $0 | Trade → |
| Wyoming wins by over 7.5 Points | 0% | 14¢ | 22¢ | — | $0 | Trade → |
This market lets traders buy and sell outcomes tied to the point spread for the Wyoming at UNLV matchup; it matters because the spread encodes market expectations about the margin of victory and key game dynamics.
Wyoming and UNLV are intercollegiate opponents with regular meetings as Mountain West Conference members, so historical matchups, travel patterns, and conference stakes often affect expectations. Contextual factors such as recent team form, injuries, and coaching matchups typically shape pregame markets for this pairing.
Market prices aggregate the collective view of traders about the spread and how many points one team will win by; movements in price reflect new information or shifts in participant sentiment rather than guarantees about the final result.
The listing shows the close time as TBD; in practice, KALSHI markets of this type typically close shortly before the game starts, so monitor the market page for the official close time.
Those outcomes correspond to discrete spread ranges or point-margin scenarios offered in the market, allowing traders to take positions on narrow bands of the possible final margin rather than a single binary outcome.
Total volume indicates historical trading activity and gives a sense of liquidity: lower volume can mean wider spreads, less ability to move large positions without price impact, and greater sensitivity to new bets or news.
Late roster changes (starters scratched), coaching decisions (e.g., play-callers unavailable), injury updates, unexpected weather or travel disruptions, and concentrated large bets can all produce rapid shifts in the spread.
Home advantage typically favors UNLV via familiarity with the venue, local crowd support, and reduced travel; traders factor these effects into the market along with any matchup-specific advantages each team has.