| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Loyola Marymount wins by over 5.5 Points | 51% | 48¢ | 51¢ | — | $174 | Trade → |
| San Diego wins by over 7.5 Points | 0% | 9¢ | 16¢ | — | $0 | Trade → |
| San Diego wins by over 10.5 Points | 0% | 4¢ | 12¢ | — | $0 | Trade → |
| Loyola Marymount wins by over 2.5 Points | 0% | 59¢ | 65¢ | — | $0 | Trade → |
| Loyola Marymount wins by over 8.5 Points | 0% | 36¢ | 42¢ | — | $0 | Trade → |
| Loyola Marymount wins by over 14.5 Points | 0% | 15¢ | 22¢ | — | $0 | Trade → |
| Loyola Marymount wins by over 11.5 Points | 0% | 25¢ | 31¢ | — | $0 | Trade → |
| San Diego wins by over 4.5 Points | 0% | 14¢ | 22¢ | — | $0 | Trade → |
| San Diego wins by over 1.5 Points | 0% | 24¢ | 31¢ | — | $0 | Trade → |
| Loyola Marymount wins by over 20.5 Points | 0% | 3¢ | 11¢ | — | $0 | Trade → |
| Loyola Marymount wins by over 17.5 Points | 0% | 7¢ | 15¢ | — | $0 | Trade → |
This market lets traders take positions on the point spread for the college basketball game San Diego at Loyola Marymount; it matters because the spread encodes the market consensus about which team is expected to win and by how many points.
San Diego (USD) and Loyola Marymount (LMU) are regular opponents within the same regional competition context, and matchups between them often hinge on tempo, perimeter shooting, and rebounding. Season-long trends, recent form, injuries, and where the game is played are common drivers of how these teams perform against the spread. Because college rosters change more rapidly than pro teams, short-term roster news can materially alter expectations.
Each listed outcome corresponds to a particular spread range; market prices reflect the crowd’s collective view and update as new information arrives. Treat prices as a dynamic signal of market sentiment rather than a fixed prediction.
The market’s close time is determined by the platform and may be listed on the market page; if the close is listed as TBD, monitor the market page for updates and expect trading to stop shortly before game start or at the announced close.
Each outcome represents a specific point-spread range for the final margin of the San Diego at Loyola Marymount game; settlement is based on the official final score relative to the spread range chosen.
Settlement follows the platform’s contingency rules: if the game is canceled and not rescheduled within the platform’s timeframe, trades are typically voided and funds returned; if rescheduled, the market may remain open until the game is played—check the platform’s official rules for details.
Rapid moves usually reflect new information such as injury reports, lineup confirmations, or large trades; in low-liquidity markets, even small news or a single large trade can trigger outsized price swings, so distinguish between information-driven moves and liquidity noise.
Head-to-head and recent results provide context but should be weighed with factors like location, roster continuity, injuries, and sample size; single-game anomalies are common in college basketball, so combine historical data with current-season metrics and situational information.