| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Hofstra wins by over 2.5 Points | 49% | 49¢ | 50¢ | — | $32K | Trade → |
| Hofstra wins by over 5.5 Points | 40% | 37¢ | 40¢ | — | $25K | Trade → |
| William & Mary wins by over 10.5 Points | 13% | 10¢ | 15¢ | — | $771 | Trade → |
| William & Mary wins by over 1.5 Points | 41% | 40¢ | 41¢ | — | $691 | Trade → |
| William & Mary wins by over 13.5 Points | 6% | 6¢ | 9¢ | — | $539 | Trade → |
| Hofstra wins by over 8.5 Points | 26% | 25¢ | 29¢ | — | $308 | Trade → |
| William & Mary wins by over 19.5 Points | 2% | 1¢ | 3¢ | — | $250 | Trade → |
| William & Mary wins by over 4.5 Points | 31% | 27¢ | 31¢ | — | $206 | Trade → |
| Hofstra wins by over 11.5 Points | 23% | 17¢ | 22¢ | — | $12 | Trade → |
| William & Mary wins by over 7.5 Points | 3% | 18¢ | 23¢ | — | $3 | Trade → |
| William & Mary wins by over 16.5 Points | 0% | 3¢ | 4¢ | — | $0 | Trade → |
This market lets traders express views on the point-spread outcome for the William & Mary at Hofstra matchup — essentially which margin range the final score will fall into. It matters because spread markets aggregate information about team strength, injuries, and other game-day factors into tradable prices.
William & Mary and Hofstra are collegiate programs whose matchups are influenced by conference alignment, roster turnover typical of college sports, and home-court dynamics when the game is played at Hofstra. Historical head-to-head results, recent seasons, and coaching styles provide context, but game-to-game variability (injuries, lineup changes, and short-term form) often drives spread movements.
Market prices in a spread market reflect the collective expectations of traders about the likely margin of victory; as new information arrives (injuries, lineup updates, betting flow), those prices adjust. Use prices as a real-time summary of market sentiment rather than fixed predictions.
The market close is listed as TBD and will typically be set relative to the official game start time per the platform’s rules; settlement occurs based on the official final score from the recognized sporting authority, with platform-specific cutoff times for trading before kickoff.
The 11 outcomes partition possible final-margin results into discrete buckets (including outcomes for each side covering, and possibly exact-margin or push scenarios); each outcome corresponds to a specific range or result against the posted spread rather than a single win/loss result.
Late availability news is highly market-sensitive: confirmation of a key starter missing or returning can quickly reprice outcomes since it changes expected margin; traders typically wait for official injury reports and starting-lineup announcements before placing larger bets.
Volume provides a sense of liquidity and how much capital has been committed; higher traded volume generally means tighter pricing and easier entry/exit, while lower volume can lead to wider spreads between buy and sell prices and greater sensitivity to single large trades.
Pushes or exact-margin outcomes depend on how the market’s outcome buckets are defined; some markets include a specific outcome for exact-margin results, while others treat pushes per platform rules (which may result in refunds or a designated settlement outcome), so check the event rules for the exact settlement policy.