| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Over 66.5 1H points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 69.5 1H points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 87.5 1H points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 75.5 1H points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 72.5 1H points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 81.5 1H points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 78.5 1H points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 84.5 1H points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 90.5 1H points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks which discrete total number of points will be scored in the first half of the Miami (OH) vs SMU game. It matters because first-half totals isolate early-game dynamics and let traders express views on pace, opening game plans, and initial scoring risk.
Miami (OH) and SMU come from different conferences and often present contrasting styles: one program may favor a ground-based, methodical approach while the other emphasizes tempo and passing. Historical matchups and season-long scoring trends can differ substantially by team and opponent quality, so first-half scoring can vary from full-game expectations. Venue and matchup context (conference vs non-conference, neutral site, etc.) also shape how coaches start games.
Market prices on KALSHI for each outcome reflect the collective expectations of traders about the first-half point total and update as new information arrives. Use those prices as a real-time summary of how the market is valuing different discrete first-half totals, recognizing they can move quickly pregame with news or betting flow.
The event page shows the official close time (listed as TBD here); in practice, first-half total markets usually stop accepting new trades at or just before kickoff or when the first half begins, so monitor the market page for the exact cutoff.
KALSHI has split the possible first-half totals into nine discrete outcomes (individual totals or buckets); each outcome corresponds to one specific range or total displayed on the market page, and traders buy into the outcome they expect the first-half score to fall into.
Compare each team's recent first-half points per game, pace metrics (possessions per half), and opponent-adjusted scoring; give extra weight to similar opponent types and home/away splits, and account for small-sample variability when drawing conclusions.
A confirmed QB change typically alters expected play-calling, tempo, and scoring confidence for the opening half; markets often move quickly on such news as traders update expectations for possessions, efficiency, and the likelihood of scoring drives early.
Yes—if the game is outdoors, wind, heavy rain, or cold can reduce passing efficiency and special teams performance, lowering first-half scoring; if the game is indoors or in stable conditions, weather is not a factor and focus should be on matchup and tempo instead.