| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Over 147.5 points scored | 53% | 52¢ | 53¢ | — | $562 | Trade → |
| Over 150.5 points scored | 43% | 43¢ | 45¢ | — | $442 | Trade → |
| Over 141.5 points scored | 62% | 64¢ | 67¢ | — | $10 | Trade → |
| Over 138.5 points scored | 75% | 69¢ | 74¢ | — | $6 | Trade → |
| Over 135.5 points scored | 80% | 74¢ | 80¢ | — | $6 | Trade → |
| Over 144.5 points scored | 61% | 56¢ | 61¢ | — | $1 | Trade → |
| Over 159.5 points scored | 0% | 21¢ | 27¢ | — | $0 | Trade → |
| Over 162.5 points scored | 0% | 15¢ | 22¢ | — | $0 | Trade → |
| Over 156.5 points scored | 0% | 27¢ | 32¢ | — | $0 | Trade → |
| Over 153.5 points scored | 0% | 34¢ | 40¢ | — | $0 | Trade → |
| Over 132.5 points scored | 0% | 78¢ | 86¢ | — | $0 | Trade → |
This prediction market asks which total-points range the TCU at Texas Tech game will settle into, giving traders a way to express expectations about the combined score. It matters because totals markets synthesize information about offense, defense, tempo, injuries, and weather into a single traded outcome.
TCU and Texas Tech are programs within the same conference, often producing games where offensive style, pace, and defensive matchups matter a great deal. Historical meetings and season-long scoring trends provide context, but roster changes, coaching adjustments, and week-to-week form drive the likely scoring in this specific matchup. The market’s outcome options (11 discrete buckets) reflect a range of possible combined scores for the game.
Market prices reflect the collective expectations of traders about which total-points bucket is most likely based on available information, and they can move as new information arrives (injuries, weather, lineups). Use prices as a dynamic signal of market sentiment rather than a fixed forecast.
Each outcome corresponds to a specific total-points range for the game (discrete score buckets). The market will settle based on the official combined final score as defined by KALSHI’s event rules; check the event page for the exact bucket boundaries and settlement rules (including whether overtime is counted).
The close time is listed as TBD; the platform will publish an official close time before the event or shortly before kickoff. Markets like this typically close prior to game start, so monitor the event page for the confirmed timestamp.
Late personnel changes alter expected scoring by changing offensive or defensive capability; traders often update positions in response, which moves market prices up to the close. The final settlement, however, depends solely on the actual combined score per platform rules.
Head-to-head history can indicate matchup tendencies (e.g., whether games have been high- or low-scoring), but current-season form, roster composition, and coaching changes are usually more informative for a single-game total.
A sudden change in game script (blowout vs. close game), unusually high turnover differential, extreme weather in Lubbock, or a surprise absence of a key offensive or defensive player can all push the total substantially higher or lower than pregame expectations.