| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Over 153.5 points scored | 49% | 49¢ | 50¢ | — | $10K | Trade → |
| Over 150.5 points scored | 56% | 55¢ | 57¢ | — | $2K | Trade → |
| Over 156.5 points scored | 46% | 41¢ | 45¢ | — | $2K | Trade → |
| Over 147.5 points scored | 62% | 62¢ | 65¢ | — | $110 | Trade → |
| Over 159.5 points scored | 40% | 34¢ | 38¢ | — | $66 | Trade → |
| Over 144.5 points scored | 69% | 69¢ | 73¢ | — | $37 | Trade → |
| Over 162.5 points scored | 32% | 27¢ | 32¢ | — | $10 | Trade → |
| Over 165.5 points scored | 27% | 20¢ | 26¢ | — | $9 | Trade → |
| Over 168.5 points scored | 0% | 15¢ | 22¢ | — | $0 | Trade → |
| Over 138.5 points scored | 0% | 78¢ | 83¢ | — | $0 | Trade → |
| Over 141.5 points scored | 0% | 74¢ | 79¢ | — | $0 | Trade → |
| Over 171.5 points scored | 0% | 11¢ | 14¢ | — | $0 | Trade → |
| Over 135.5 points scored | 0% | 84¢ | 87¢ | — | $0 | Trade → |
This market lets traders take positions on the total points scored in the North Dakota at St. Thomas game; it matters because totals markets aggregate expectations about pace, offense, and defense into a single tradeable question.
The market sits on the combined scoring output of two collegiate teams whose game-level totals fluctuate with pace, roster availability, and matchup dynamics. Historical meeting patterns, recent form, and situational factors such as rest and travel all shape likely scoring ranges, and those elements are what participants watch as new information arrives.
Market prices reflect what traders collectively expect for the final combined score and will move as news (injuries, starting lineups, weather for outdoor sports, etc.) is released; interpret prices as a real-time consensus, not a fixed forecast.
Markets like this typically close at or shortly before official game start (tip-off/kickoff) or under platform-specific suspension rules; check the event page or platform notifications for the exact closing time since this listing is marked TBD.
Settlement is based on the official final combined score as recorded by the relevant league or official box score; whether overtime is included depends on the platform’s rulebook, so confirm the market’s settlement rules before trading.
Look at both teams’ recent points scored and allowed per possession (efficiency), tempo/possessions per game, turnover rates, and three-point attempt rates — those metrics drive expected total scoring more than single-game point totals.
Late changes can materially alter scoring expectations: loss of a primary scorer or rebounder can reduce total points, while a bench-heavy lineup or free-throw-reliant team can increase variance; traders often reprice the market quickly when such news breaks.
Head-to-head history can provide context (e.g., recurring stylistic mismatches), but recent season-level metrics and current roster status are usually more predictive than distant past meetings; use head-to-head as one input rather than the sole determinant.