| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Oklahoma wins by over 1.5 Points | 76% | 70¢ | 76¢ | — | $3K | Trade → |
| Oklahoma wins by over 7.5 Points | 53% | 52¢ | 53¢ | — | $2K | Trade → |
| Oklahoma wins by over 8.5 Points | 49% | 47¢ | 49¢ | — | $250 | Trade → |
| Oklahoma wins by over 5.5 Points | 60% | 59¢ | 60¢ | — | $215 | Trade → |
| Oklahoma wins by over 4.5 Points | 64% | 60¢ | 64¢ | — | $112 | Trade → |
| Oklahoma wins by over 2.5 Points | 71% | 67¢ | 71¢ | — | $2 | Trade → |
| Oklahoma wins by over 23.5 Points | 0% | 3¢ | 9¢ | — | $0 | Trade → |
| Oklahoma wins by over 22.5 Points | 0% | 4¢ | 11¢ | — | $0 | Trade → |
| Oklahoma wins by over 20.5 Points | 0% | 7¢ | 14¢ | — | $0 | Trade → |
| Oklahoma wins by over 16.5 Points | 0% | 16¢ | 23¢ | — | $0 | Trade → |
| South Carolina wins by over 2.5 Points | 0% | 17¢ | 25¢ | — | $0 | Trade → |
| Oklahoma wins by over 13.5 Points | 0% | 26¢ | 31¢ | — | $0 | Trade → |
| South Carolina wins by over 8.5 Points | 0% | 4¢ | 11¢ | — | $0 | Trade → |
| Oklahoma wins by over 11.5 Points | 0% | 34¢ | 36¢ | — | $0 | Trade → |
| Oklahoma wins by over 19.5 Points | 0% | 9¢ | 15¢ | — | $0 | Trade → |
| Oklahoma wins by over 17.5 Points | 0% | 13¢ | 21¢ | — | $0 | Trade → |
| Oklahoma wins by over 14.5 Points | 0% | 23¢ | 28¢ | — | $0 | Trade → |
| South Carolina wins by over 7.5 Points | 0% | 6¢ | 13¢ | — | $0 | Trade → |
| South Carolina wins by over 1.5 Points | 0% | 20¢ | 26¢ | — | $0 | Trade → |
| South Carolina wins by over 4.5 Points | 0% | 12¢ | 19¢ | — | $0 | Trade → |
| Oklahoma wins by over 10.5 Points | 0% | 37¢ | 41¢ | — | $0 | Trade → |
| South Carolina wins by over 5.5 Points | 0% | 10¢ | 17¢ | — | $0 | Trade → |
This market lets traders buy and sell outcomes tied to the point spread for the college football game South Carolina at Oklahoma. It matters because the spread market aggregates public information about expected margin and responds quickly to news that affects the likely game result.
Oklahoma and South Carolina come from different conferences and often present contrasting styles of play; matchups between teams like these hinge on tempo, quarterback play, and how each defense matches up with the opponent’s strengths. Historical matchup details, recent season trends, and coaching decisions shape expectations, and any late roster changes or injuries can materially alter the outlook for this specific game.
Market prices on the spread reflect collective expectations about how many points one team will win or lose by and update as participants incorporate new information. Use prices as a real-time signal that moves with injury reports, lineup news, weather forecasts, and other game-specific developments.
The event listing currently shows a close time of TBD; typically spread markets close at or just before kickoff, but you should monitor the KALSHI listing for the final settlement time and any updates.
Those outcomes correspond to discrete spread intervals or specific point-margin buckets offered by the contract, so each outcome pays if the final margin falls inside that outcome’s defined range; consult the market’s outcome descriptions on KALSHI to see the exact ranges.
A confirmed injury to a starting quarterback is high-impact news that typically shifts expectations for scoring and margin; markets usually react quickly as traders reprice based on the backup’s history, offensive continuity, and coaching adjustments.
Home-field factors—crowd noise, travel fatigue for the visitor, and familiarity with the stadium—are built into lines by bookmakers and reflected in market prices; their actual influence depends on team travel distance, recent home/road performance, and matchup-specific variables.
Settlement procedures depend on KALSHI’s contract rules and any official adjustments announced by the platform; in many prediction markets, postponed or canceled events are voided or settled per predefined policies, so check the market’s terms and KALSHI’s announcements for event-specific handling.