| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Fordham wins by over 2.5 Points | 49% | 46¢ | 49¢ | — | $11 | Trade → |
| La Salle wins by over 4.5 Points | 27% | 27¢ | 33¢ | — | $1 | Trade → |
| La Salle wins by over 13.5 Points | 0% | 5¢ | 12¢ | — | $0 | Trade → |
| Fordham wins by over 5.5 Points | 0% | 35¢ | 41¢ | — | $0 | Trade → |
| Fordham wins by over 14.5 Points | 0% | 10¢ | 16¢ | — | $0 | Trade → |
| Fordham wins by over 17.5 Points | 0% | 5¢ | 12¢ | — | $0 | Trade → |
| La Salle wins by over 7.5 Points | 0% | 17¢ | 24¢ | — | $0 | Trade → |
| La Salle wins by over 1.5 Points | 0% | 38¢ | 43¢ | — | $0 | Trade → |
| Fordham wins by over 8.5 Points | 0% | 24¢ | 30¢ | — | $0 | Trade → |
| Fordham wins by over 11.5 Points | 0% | 16¢ | 23¢ | — | $0 | Trade → |
| La Salle wins by over 10.5 Points | 0% | 10¢ | 17¢ | — | $0 | Trade → |
This market asks how the point spread will resolve for the college basketball game Fordham at La Salle; it matters to traders and bettors who want to express views on the expected margin of victory. Spread markets summarize collective expectations about game competitiveness and key matchup advantages.
Fordham and La Salle are conference opponents, so this matchup is shaped by familiar scouting, recent conference form, and typical travel/home-court dynamics. Historical results between the two programs provide context, but season-to-date trends, roster availability, and coaching adjustments are often more predictive for any single game. The listed market currently shows 11 discrete spread outcomes and a total traded volume of $12; the market close time is TBD on the KALSHI platform.
In a spread market each outcome corresponds to a particular margin scenario; market prices reflect the crowd's consensus about which margins are most likely given available information. Prices can move as new data (injuries, starting lineups, weather for travel, or breaking news) arrives and should be read as shifting signals, not guarantees.
The market close time is listed as TBD; on KALSHI, spread markets commonly close before game tipoff or at a posted cutoff — check the KALSHI market page for updates and any announced closing time.
They represent discrete margin scenarios for how the final score differential resolves (different spread ranges or exact margins depending on the market design); each outcome corresponds to a particular band of final margins rather than a single continuous number.
Announcements about starting-lineup changes, injuries to primary scorers, point guards, or key rebounders, and any suspension or availability news typically have the biggest impact because they alter expected scoring and defensive matchups.
Head-to-head history is useful for matchup tendencies (e.g., which team controls pace or exploits mismatches), but place more weight on current-season form, roster changes, and situational context because those most directly affect a single game’s spread.
Monitor official team injury reports and press releases, pregame starter announcements, reputable sports beat reporters and local outlets, coach interviews, and the KALSHI order book and trade history for line movement; these sources typically surface the news that drives market adjustments.