| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Over 145.5 points scored | 53% | 51¢ | 53¢ | — | $159 | Trade → |
| Over 148.5 points scored | 44% | 44¢ | 46¢ | — | $29 | Trade → |
| Over 136.5 points scored | 0% | 64¢ | 84¢ | — | $0 | Trade → |
| Over 163.5 points scored | 0% | 2¢ | 97¢ | — | $0 | Trade → |
| Over 142.5 points scored | 0% | 52¢ | 75¢ | — | $0 | Trade → |
| Over 160.5 points scored | 0% | 2¢ | 77¢ | — | $0 | Trade → |
| Over 151.5 points scored | 0% | 30¢ | 50¢ | — | $0 | Trade → |
| Over 154.5 points scored | 0% | 22¢ | 45¢ | — | $0 | Trade → |
| Over 133.5 points scored | 0% | 9¢ | 98¢ | — | $0 | Trade → |
| Over 139.5 points scored | 0% | 57¢ | 81¢ | — | $0 | Trade → |
| Over 157.5 points scored | 0% | 16¢ | 40¢ | — | $0 | Trade → |
This market asks how many combined points Gardner-Webb and USC Upstate will score in their matchup; it matters to traders who want to express views on the scoring environment and tempo of this specific game.
Both programs are NCAA Division I teams and mid-major matchups like this often show wide scoring variation depending on pace, personnel and coaching strategy. Season trends, recent form and any roster changes or injuries leading into the game provide the most relevant background for this market.
Market prices represent the crowd’s consensus about the likely total and will move as new information arrives. Treat prices as dynamic indicators of market sentiment rather than fixed predictions.
Trading generally closes at the official game start time shown on the platform; because this event lists the close time as TBD, monitor the KALSHI event page for the announced settlement cutoff and any updates.
The winner is determined by the combined final score as recorded in the official box score for the contest. Check the market’s specific rules for whether overtime points are included in settlement.
Late starting lineup announcements, injuries or suspensions to key scorers, announced rest decisions, or an unexpected venue/time change are the most common drivers of rapid price moves.
Compare both teams’ recent scoring and pace over a meaningful sample (several games), examine offensive/defensive efficiency per possession, and review three-point and free-throw tendencies; prioritize current-season and matchup-specific data over older history.
Head-to-head history can offer context, but it is typically less predictive than current rosters, recent form, and style-of-play metrics; use head-to-head as one input alongside up-to-date performance and availability information.