| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Columbia wins by over 19.5 Points | 3% | 1¢ | 6¢ | — | $50 | Trade → |
| Columbia wins by over 4.5 Points | 0% | 18¢ | 26¢ | — | $0 | Trade → |
| Columbia wins by over 13.5 Points | 0% | 3¢ | 10¢ | — | $0 | Trade → |
| Harvard wins by over 5.5 Points | 0% | 44¢ | 47¢ | — | $0 | Trade → |
| Harvard wins by over 11.5 Points | 0% | 20¢ | 27¢ | — | $0 | Trade → |
| Harvard wins by over 2.5 Points | 0% | 56¢ | 57¢ | — | $0 | Trade → |
| Harvard wins by over 8.5 Points | 0% | 30¢ | 36¢ | — | $0 | Trade → |
| Columbia wins by over 1.5 Points | 0% | 29¢ | 34¢ | — | $0 | Trade → |
| Columbia wins by over 7.5 Points | 0% | 11¢ | 19¢ | — | $0 | Trade → |
| Columbia wins by over 10.5 Points | 0% | 5¢ | 13¢ | — | $0 | Trade → |
| Columbia wins by over 16.5 Points | 0% | 3¢ | 7¢ | — | $0 | Trade → |
This market lets traders take positions on the point-spread outcome for Columbia at Harvard, showing collective expectations about the margin of victory. Spread markets matter because they focus on relative team performance rather than just who wins, which can reveal nuanced sentiment about matchups and conditions.
Columbia and Harvard are Ivy League opponents; Harvard has frequently been the pregame favorite in recent Ivy competition due to recruiting depth and program continuity, while Columbia has produced occasional upsets and competitive performances. Home-field/court dynamics at Harvard and short Ivy League schedules make single-game swings common, so lines can move quickly on new information like injuries or coaching announcements.
Market prices aggregate participants' views about which spread-bin or margin interval is most likely to occur; price movements reflect new information and trading flow rather than a single predictive model. Use prices as a real-time summary of market expectations, while remembering they can shift rapidly as game-day news appears.
The market close time is listed as TBD; the market will typically close either just before game start or at a platform-defined deadline — monitor the market page for the official close time.
The 11 outcomes are discrete spread bins or margin ranges (for example, Harvard wins by X or more, Columbia wins by Y or more, and intermediate ranges); each outcome corresponds to a specific margin interval rather than a simple win/loss result.
Late news about starters, injuries, or suspensions tends to move prices quickly as traders re-evaluate expected margins; significant absences for a primary scorer or defender typically shift the market more than role-player changes.
Low volume means prices can be volatile and more easily swayed by individual trades; treat current prices as less robust than markets with heavier liquidity and watch for rapid swings after new information.
Resolution follows the platform’s rules (this market cites KALSHI); in many cases a postponed game that is eventually played will allow the market to settle on the official game result, while outright cancellations can lead to voiding and refunds — check KALSHI’s official settlement policy for specifics.