| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Over 152.5 points scored | 0% | 1¢ | 33¢ | — | $0 | Trade → |
| Over 137.5 points scored | 0% | 29¢ | 69¢ | — | $0 | Trade → |
| Over 131.5 points scored | 0% | 43¢ | 82¢ | — | $0 | Trade → |
| Over 134.5 points scored | 0% | 37¢ | 76¢ | — | $0 | Trade → |
| Over 140.5 points scored | 0% | 22¢ | 62¢ | — | $0 | Trade → |
| Over 158.5 points scored | 0% | 1¢ | 50¢ | — | $0 | Trade → |
| Over 128.5 points scored | 0% | 51¢ | 99¢ | — | $0 | Trade → |
| Over 146.5 points scored | 0% | 8¢ | 47¢ | — | $0 | Trade → |
| Over 143.5 points scored | 0% | 46¢ | 54¢ | — | $0 | Trade → |
| Over 149.5 points scored | 0% | 4¢ | 39¢ | — | $0 | Trade → |
| Over 155.5 points scored | 0% | 1¢ | 27¢ | — | $0 | Trade → |
This market asks which total combined points will occur in the Delaware St. at Morgan St. game; it matters to traders who want to express a view on whether the game will be relatively high- or low-scoring. Totals markets aggregate public information about pace, scoring efficiency, and game context into tradable outcomes.
Delaware State and Morgan State are conference opponents with recurring meetings and familiar coaching matchups; their prior games, roster continuity, and strategic approaches shape expectations for scoring. Venue (Morgan State at home), recent form, and any late roster or injury news are common drivers of how many points the game produces. Because college-team lineups and rotations change frequently, historical averages are useful but should be combined with the latest situational updates.
Market prices on each outcome reflect traders' collective view about which total-point bucket is most likely; comparing prices across outcomes shows the market consensus about relative likelihoods. For execution and settlement details, consult the platform's market page and rulebook.
It refers to the combined points scored by both teams as defined by the market on the platform; check the KALSHI market rules for whether overtime points are included or excluded for settlement.
The market close time is listed as TBD for this event; markets like this typically close at or shortly before scheduled tip-off, but you should check the specific market page on KALSHI for the official close time and any updates.
The 11 outcomes correspond to the discrete total-point levels or ranges offered by the market (for example, specific totals or bucketed ranges); the market description on the event page shows the exact mapping of each outcome to a total-point level or range.
Key team-specific drivers include each team’s recent offensive/defensive form, whether their primary scorers are available, how deep their benches are, and coaching tendencies around tempo and late-game clock management.
Use head-to-head and recent-game data to identify matchup tendencies (e.g., one team consistently slows the game), then adjust for current context such as injuries, rest, and venue; combine that with officiating tendencies and late news to refine your expectation before trading.