| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Richmond wins by over 8.5 Points | 41% | 36¢ | 41¢ | — | $837 | Trade → |
| Richmond wins by over 5.5 Points | 51% | 47¢ | 51¢ | — | $834 | Trade → |
| Richmond wins by over 11.5 Points | 30% | 29¢ | 30¢ | — | $69 | Trade → |
| Richmond wins by over 20.5 Points | 0% | 3¢ | 9¢ | — | $0 | Trade → |
| Richmond wins by over 19.5 Points | 0% | 3¢ | 11¢ | — | $0 | Trade → |
| Loyola Chicago wins by over 11.5 Points | 0% | 4¢ | 12¢ | — | $0 | Trade → |
| Loyola Chicago wins by over 10.5 Points | 0% | 6¢ | 14¢ | — | $0 | Trade → |
| Loyola Chicago wins by over 4.5 Points | 0% | 18¢ | 25¢ | — | $0 | Trade → |
| Richmond wins by over 1.5 Points | 0% | 59¢ | 66¢ | — | $0 | Trade → |
| Loyola Chicago wins by over 5.5 Points | 0% | 15¢ | 23¢ | — | $0 | Trade → |
| Richmond wins by over 4.5 Points | 0% | 50¢ | 56¢ | — | $0 | Trade → |
| Loyola Chicago wins by over 8.5 Points | 0% | 9¢ | 18¢ | — | $0 | Trade → |
| Richmond wins by over 16.5 Points | 0% | 9¢ | 16¢ | — | $0 | Trade → |
| Loyola Chicago wins by over 2.5 Points | 0% | 25¢ | 31¢ | — | $0 | Trade → |
| Richmond wins by over 13.5 Points | 0% | 17¢ | 25¢ | — | $0 | Trade → |
| Richmond wins by over 14.5 Points | 0% | 14¢ | 22¢ | — | $0 | Trade → |
| Richmond wins by over 7.5 Points | 0% | 39¢ | 45¢ | — | $0 | Trade → |
| Richmond wins by over 10.5 Points | 0% | 27¢ | 33¢ | — | $0 | Trade → |
| Richmond wins by over 17.5 Points | 0% | 7¢ | 15¢ | — | $0 | Trade → |
| Loyola Chicago wins by over 1.5 Points | 0% | 28¢ | 34¢ | — | $0 | Trade → |
| Loyola Chicago wins by over 7.5 Points | 0% | 11¢ | 19¢ | — | $0 | Trade → |
| Richmond wins by over 2.5 Points | 0% | 56¢ | 62¢ | — | $0 | Trade → |
This market asks which point-spread outcome will occur in the college basketball game Loyola Chicago at Richmond; it matters because the spread aggregates bettors' and traders' expectations about the likely margin of victory. Market prices provide a continuously updated signal about how participants view matchup-specific information.
Loyola Chicago and Richmond come from different conferences and styles of play; matchups like this can hinge on tempo, defensive schemes, and familiarity with opponents. Scheduling (conference play vs. non-conference), recent form, and any roster changes or injuries in the days leading up to the game are typical context that shape how the spread develops.
Interpret market prices as the crowd's current consensus about which spread range is most likely to contain the final margin; prices move as new public or private information arrives. Use them alongside your own research (injuries, lineups, matchups) rather than as a standalone forecasting oracle.
Close time is listed as TBD for this market; check the trading platform for a finalized close. Late injuries or lineup news that occur before the market closes typically move prices; information released after close will not change the settled outcome except per the platform’s official late-notice rules.
Each outcome corresponds to a specific spread range or exact margin interval for the final score; the winning outcome is the interval that contains the game's final point differential. Consult the platform’s outcome descriptions to see the precise mapping from final margin to outcome.
Home-court typically lowers the visiting team’s chance of covering the spread by accounting for travel, crowd influence, and familiarity with the facility; quantify that edge by comparing both teams’ home/away splits and how they’ve performed in similar venue contexts.
A starter's absence usually shifts expectations for offensive efficiency and ball-handling, which the market will often price in quickly; the magnitude depends on the player’s role—losing a primary scorer or facilitator typically produces a larger adjustment than losing a reserve.
Head-to-head history is useful when recent matchups are numerous and teams’ rosters/coaching staffs are similar; for infrequent meetings or when personnel have changed, prioritize recent performance, matchup metrics, and common-opponent results over distant past meetings.