| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Over 142.5 points scored | 54% | 53¢ | 54¢ | — | $4K | Trade → |
| Over 145.5 points scored | 45% | 43¢ | 45¢ | — | $792 | Trade → |
| Over 139.5 points scored | 62% | 59¢ | 62¢ | — | $345 | Trade → |
| Over 127.5 points scored | 87% | 85¢ | 87¢ | — | $147 | Trade → |
| Over 136.5 points scored | 68% | 66¢ | 68¢ | — | $22 | Trade → |
| Over 133.5 points scored | 74% | 73¢ | 75¢ | — | $10 | Trade → |
| Over 148.5 points scored | 36% | 35¢ | 40¢ | — | $8 | Trade → |
| Over 130.5 points scored | 81% | 76¢ | 81¢ | — | $7 | Trade → |
| Over 154.5 points scored | 33% | 22¢ | 25¢ | — | $1 | Trade → |
| Over 151.5 points scored | 0% | 29¢ | 33¢ | — | $0 | Trade → |
| Over 157.5 points scored | 0% | 17¢ | 22¢ | — | $0 | Trade → |
This market asks how many combined points will be scored in the Idaho at Montana St. game; traders buy and sell discrete total-point outcomes to express expectations about game scoring. It matters because total-point markets aggregate public and expert information about pace, offense/defense matchup, weather, and other game-day factors.
Idaho and Montana State are NCAA college football programs whose recent schedules, roster turnover, and coaching approaches shape how they score and prevent scoring. Historical head-to-head results, season-long trends (offensive tempo, red-zone efficiency, turnover rates), and situational factors such as injuries or travel are the primary contextual elements that persist across markets. Because college rosters change year to year, recent-season and game-specific information typically matter more than distant history.
Market prices for each outcome represent the crowd-implied view about which total-point bracket is most likely, and they move as new information arrives (injury reports, weather forecasts, lineup changes). Use prices as a real-time summary of market sentiment, not as a deterministic prediction.
A TBD close means the platform has not yet set the final cut-off; the market will typically close before kickoff. Check the KALSHI event page and any official updates for the announced close time; trades after the close will not be accepted.
The 11 outcomes divide the possible combined-game scores into discrete buckets or point totals that will be resolved based on the final combined score. Consult the outcome labels on the market page to see the exact brackets and how the market defines each outcome.
Resolution rules vary by platform and by market. Verify the specific event rules on KALSHI—some markets count overtime points toward totals, others specify regulation only—so confirmation from the event description or rulebook is necessary.
Treat head-to-head history as informative but context-dependent: compare opponent quality, coaching changes, and roster continuity. Prioritize recent-season stats (offensive yards per play, scoring per drive, red-zone efficiency) and adjust for differences in schedule strength and any recent personnel changes.
Home-field factors (crowd noise, travel fatigue for the visiting team) can influence tempo and special teams. Local weather—wind, cold, or precipitation—can suppress passing efficiency and kicking, often lowering scoring, so check the forecast as game day approaches and incorporate likely conditions into your view.