| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Portland | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Loyola Marymount | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This prediction market asks which team will win the Portland vs Loyola Marymount matchup and matters because it aggregates public information about team form, injuries, and other game-specific signals into a single trading price.
Portland and Loyola Marymount are NCAA Division I programs whose games are shaped by roster matchups, coaching strategies, and situational factors like home court and travel. Historical head-to-head results give context, but college rosters change yearly, so recent form and current availability are usually more informative.
Market odds convey the crowd’s current assessment of which side is more likely to win based on available information; treat them as a dynamic snapshot that updates as starting lineups, injuries, and other news arrive.
This market offers two outcomes—Portland wins or Loyola Marymount wins—and will be settled according to KALSHI’s official game result and settlement rules; consult the event page for details about overtime inclusion and official score sources.
The market close time is listed as TBD on the event page; typically trading locks shortly before the official game start, so final lineup and injury news released near tip-off can have the biggest impact on prices.
Prioritize confirmed starting lineup releases and official injury reports; availability of primary scorers, shot creators, or defensive anchors materially changes matchup dynamics and should be reflected in how you weigh the market.
If the game is postponed, canceled, or rescheduled, resolution will follow KALSHI’s stated contingency and settlement policies for the event—markets may be voided or held open until a confirmed reschedule; check the exchange’s announcements for the specific outcome handling.
Head-to-head history can highlight recurring matchup tendencies, but because college rosters and coaching staffs evolve, recent season performance, current rotations, and injury status are generally stronger drivers for predicting a single upcoming game.