| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Maryland wins by over 45.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Maryland wins by over 21.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Maryland wins by over 27.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Maryland wins by over 15.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Maryland wins by over 33.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Maryland wins by over 39.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Maryland wins by over 30.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Maryland wins by over 42.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Maryland wins by over 24.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Maryland wins by over 18.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Maryland wins by over 36.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks how the point spread will resolve for the Murray St. at Maryland game; spread markets matter because they express the market's view of the expected margin of victory and are used by traders to speculate on which side will cover.
Murray State is typically a mid-major program while Maryland competes in a Power conference; differences in roster depth, style of play, and travel can create meaningful mismatches. College basketball lineups and team strength change over short timeframes, so context such as recent form, injuries, and scheduling often matters more than long-term reputation.
In a spread contract, each outcome corresponds to a range of final margins; market prices reflect collective expectations about which margin range will occur and will move as new information (injuries, lineup changes, tipoff time) arrives.
The listing currently shows 'Closes: TBD'; most spread markets close at or just before the game's official tipoff time or when trading liquidity is sufficient, so check the KALSHI page frequently for the posted close time and any updates.
Those outcomes represent discrete margin-of-victory ranges or specific spread thresholds that partition possible final score differentials; consult the contract description on the platform to see the exact bins (e.g., which margins map to which outcome).
Head-to-head history can be informative but is often less predictive in college basketball because rosters turn over regularly; prioritize recent matchups, common-opponent results, and opponent-adjusted metrics rather than distant historical meetings.
Focus on projected starters, primary scorers and ball-handlers, rebounders who control possession, and depth players who factor into late-game minutes; late changes to expected rotations or availability typically have the biggest impact on the spread.
Zero or very low reported volume indicates limited liquidity; prices can be more volatile and less reliable. If you choose to trade, consider sizing bets conservatively, watch for incoming news that could move the market, and prefer trades executed when liquidity increases.