| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Nicholls St. wins by over 2.5 Points | 48% | 46¢ | 48¢ | — | $18K | Trade → |
| Nicholls St. wins by over 1.5 Points | 52% | 51¢ | 52¢ | — | $6K | Trade → |
| Northwestern St. wins by over 1.5 Points | 43% | 42¢ | 44¢ | — | $462 | Trade → |
| Northwestern St. wins by over 11.5 Points | 12% | 12¢ | 13¢ | — | $389 | Trade → |
| Nicholls St. wins by over 4.5 Points | 42% | 38¢ | 42¢ | — | $275 | Trade → |
| Nicholls St. wins by over 5.5 Points | 34% | 34¢ | 38¢ | — | $123 | Trade → |
| Nicholls St. wins by over 7.5 Points | 32% | 28¢ | 31¢ | — | $94 | Trade → |
| Northwestern St. wins by over 2.5 Points | 38% | 38¢ | 40¢ | — | $26 | Trade → |
| Nicholls St. wins by over 11.5 Points | 0% | 17¢ | 19¢ | — | $0 | Trade → |
| Nicholls St. wins by over 8.5 Points | 0% | 26¢ | 29¢ | — | $0 | Trade → |
| Northwestern St. wins by over 5.5 Points | 0% | 25¢ | 29¢ | — | $0 | Trade → |
| Northwestern St. wins by over 7.5 Points | 0% | 20¢ | 24¢ | — | $0 | Trade → |
| Northwestern St. wins by over 8.5 Points | 0% | 18¢ | 22¢ | — | $0 | Trade → |
| Northwestern St. wins by over 10.5 Points | 0% | 14¢ | 17¢ | — | $0 | Trade → |
| Nicholls St. wins by over 10.5 Points | 0% | 20¢ | 22¢ | — | $0 | Trade → |
| Northwestern St. wins by over 13.5 Points | 0% | 6¢ | 8¢ | — | $0 | Trade → |
| Nicholls St. wins by over 13.5 Points | 0% | 12¢ | 15¢ | — | $0 | Trade → |
| Nicholls St. wins by over 14.5 Points | 0% | 9¢ | 14¢ | — | $0 | Trade → |
| Nicholls St. wins by over 17.5 Points | 0% | 4¢ | 6¢ | — | $0 | Trade → |
| Northwestern St. wins by over 14.5 Points | 0% | 5¢ | 7¢ | — | $0 | Trade → |
| Nicholls St. wins by over 16.5 Points | 0% | 6¢ | 9¢ | — | $0 | Trade → |
| Northwestern St. wins by over 4.5 Points | 0% | 30¢ | 34¢ | — | $0 | Trade → |
| Northwestern St. wins by over 17.5 Points | 0% | 3¢ | 4¢ | — | $0 | Trade → |
This market lets traders take positions on the point-spread outcome for the college football game between Northwestern St. and Nicholls St. Spread markets matter because they focus on margin of victory and respond quickly to game-day information such as injuries, weather, and coaching decisions.
Northwestern St. and Nicholls St. are regional collegiate programs whose matchups often feature familiar coaching staffs and short travel distances, which can compress expected variance compared with long-distance games. Historical context — recent meetings, roster turnover, and conference placement — can all influence how bettors and markets view the matchup going into game week.
Prices in a spread market express the market’s consensus about which margin-range outcome is most supported by traders at a given moment; they update as new information arrives and should be read as dynamic signals rather than fixed predictions.
The market's close time is listed as TBD on the event page; platform close times typically occur before kickoff and may update as the game date is finalized — check the market page for the official and final close time.
Each outcome corresponds to a specific spread outcome or margin-range defined by the market creator (for example, discrete margin buckets); review the outcome labels on the market detail panel to see the exact definitions for this event.
Prioritize confirmed game-day statuses for quarterbacks, offensive line, and key defenders — confirmed absences tend to move spreads materially. Use trusted beat reporters, official team releases, and pregame injury designations rather than unconfirmed rumors.
Yes — home-field effects include crowd noise, familiarity with the playing surface, and travel fatigue. Because both programs are regionally close, the effect may be smaller than long-distance games but can still influence special teams, fourth-down decisions, and tempo.
Head-to-head history and recent form provide context (coaching matchups, scheme advantages, turnover trends), but their predictive value depends on roster continuity and injuries; weigh recent statistical trends like turnover margin and red-zone efficiency while adjusting for player turnover and situational differences.