| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Over 126.5 points scored | 63% | 57¢ | 60¢ | — | $1K | Trade → |
| Over 129.5 points scored | 54% | 54¢ | 56¢ | — | $1K | Trade → |
| Over 132.5 points scored | 47% | 44¢ | 47¢ | — | $649 | Trade → |
| Over 135.5 points scored | 39% | 34¢ | 39¢ | — | $24 | Trade → |
| Over 117.5 points scored | 0% | 75¢ | 82¢ | — | $0 | Trade → |
| Over 123.5 points scored | 0% | 64¢ | 69¢ | — | $0 | Trade → |
| Over 120.5 points scored | 0% | 70¢ | 76¢ | — | $0 | Trade → |
| Over 138.5 points scored | 0% | 27¢ | 34¢ | — | $0 | Trade → |
| Over 144.5 points scored | 0% | 15¢ | 22¢ | — | $0 | Trade → |
| Over 141.5 points scored | 0% | 21¢ | 27¢ | — | $0 | Trade → |
| Over 114.5 points scored | 0% | 81¢ | 88¢ | — | $0 | Trade → |
This market asks how many total points will be scored in the Marist at Quinnipiac college basketball game by offering multiple total-point thresholds as tradable outcomes. It matters because it aggregates real-money expectations about how high- or low-scoring the game will be, which is useful for bettors and analysts tracking scoring risk.
Marist and Quinnipiac are NCAA Division I programs whose matchups are decided by factors like pace, shooting accuracy, and defensive schemes rather than external events. Historical head-to-head trends, season-long offensive and defensive performance, and recent form all provide context for likely scoring levels; those datasets are what traders use to form expectations for this market. The market currently lists 11 distinct total-point outcomes and the official close time is listed as TBD on the exchange.
Market prices on this platform reflect the consensus expectation of traders about which total-point threshold will be exceeded; prices move as new information (injuries, lineups, tip time) arrives and as traders update their beliefs. Treat prices as an evolving signal of collective expectation, not a fixed prediction.
The close time is listed as TBD on the exchange; many venue-based markets close at or shortly before scheduled tip-off, but always check the Kalshi market page for the exact closing timestamp or any platform announcements.
Home-court can affect scoring through crowd energy, familiarity with the rim and sightlines, and reduced travel fatigue; historically, some teams score better at home while opponents may play more cautiously, so evaluate each team's home/away scoring splits for this matchup.
Look at both teams' recent points per game, offensive and defensive efficiency, pace (possessions per game), turnover rates, three-point attempt and make rates, and free-throw rates — these together indicate expected combined scoring.
Late injuries or lineup news that remove high-usage scorers or key defenders can meaningfully shift expectations; markets tend to react quickly to confirmed reports, as losing a primary scorer typically lowers expected totals while losing a defensive anchor may raise them.
The 11 outcomes correspond to different total-point thresholds or ranges for this game; choose an outcome by comparing the market-implied expectation (prices), recent team scoring trends, and the liquidity/volume on each outcome — note the market has recorded $3,264 in total volume traded so far, which indicates current activity but not final resolution.