| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Over 135.5 points scored | 49% | 46¢ | 49¢ | — | $131 | Trade → |
| Over 132.5 points scored | 52% | 54¢ | 57¢ | — | $37 | Trade → |
| Over 129.5 points scored | 63% | 58¢ | 65¢ | — | $1 | Trade → |
| Over 141.5 points scored | 0% | 29¢ | 35¢ | — | $0 | Trade → |
| Over 126.5 points scored | 0% | 65¢ | 71¢ | — | $0 | Trade → |
| Over 138.5 points scored | 0% | 36¢ | 42¢ | — | $0 | Trade → |
| Over 123.5 points scored | 0% | 71¢ | 77¢ | — | $0 | Trade → |
| Over 117.5 points scored | 0% | 81¢ | 88¢ | — | $0 | Trade → |
| Over 147.5 points scored | 0% | 16¢ | 24¢ | — | $0 | Trade → |
| Over 120.5 points scored | 0% | 76¢ | 84¢ | — | $0 | Trade → |
| Over 144.5 points scored | 0% | 22¢ | 29¢ | — | $0 | Trade → |
This prediction market asks which total-points outcome will occur in the Drexel at Hofstra basketball game; it matters because total points markets let traders express views on the combined scoring level rather than just the winner. Outcomes reflect how bettors collectively assess offensive pace, defense, and game context for these two teams.
Drexel and Hofstra are college basketball programs with distinct styles that can influence scoring—one team may prioritize a faster pace while the other emphasizes halfcourt sets and defense. Historical meetings, recent form, roster availability, and venue (home/away) all shape expectations; markets update as information such as injuries, lineups, and coaching adjustments becomes available. This particular market is hosted on KALSHI and will settle according to the platform's stated resolution rules.
Prediction market prices reflect the aggregate market view of which total-points range (or exact total bracket) is most likely given current information; they are not fixed predictions and will move as new data arrives or traders revise beliefs. Interpret prices qualitatively to understand market consensus about whether the game will be higher- or lower-scoring than typical.
The market close time is set by the platform and commonly coincides with the scheduled game start or slightly before tip-off; because this listing shows TBD, expect the close time to be posted once the game time is finalized and subject to KALSHI's market rules.
The winning outcome is the bracket or option that contains the combined final score of Drexel and Hofstra as measured at game end; resolution follows the market’s specific wording on whether the total is counted at the final whistle, and whether overtime is included or excluded per KALSHI's stated rules.
Whether overtime counts depends on the market's resolution conditions; some markets include all points scored through any overtime periods while others specify 'regulation only'—check the market's settlement text on KALSHI for the definitive rule.
Late injuries and lineup changes can shift expected scoring by altering pace, offensive roles, and defensive matchups; monitor official injury reports, coach announcements, and pregame rotations, since traders typically adjust market prices quickly when such news emerges.
Look at recent head-to-head games for scoring trends, each team’s season-long offensive and defensive efficiency metrics, how both teams perform at home versus on the road, and any structural changes (new coach, transfers) since prior meetings that could affect scoring.