| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Over 138.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 141.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 144.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 147.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 150.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 153.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 156.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 159.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 162.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 165.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 168.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks which total-points range the Oklahoma at South Carolina game will fall into. It matters because total-points markets aggregate public and expert views about how offense, defense, tempo, and situational factors will combine on game day.
Oklahoma at South Carolina pairs two college programs with distinct offensive and defensive profiles; the matchup location (South Carolina hosting) and timing will influence game conditions. The market is broken into multiple discrete outcomes (11 bins) that let traders express views on different total-point ranges; the market close is listed as TBD, so timing may be set closer to the game.
Each outcome corresponds to a specific total-points bracket or exact-total bin; market prices reflect the trading community’s consensus about which bracket will occur and update as new information arrives. Treat the market as a dynamic summary of available information—injuries, weather, and lineup announcements commonly move prices before kickoff.
The market close is listed as TBD; platforms typically close total-points markets shortly before kickoff, so monitor the KALSHI page for the official close time as the game approaches.
They represent discrete total-points bins (ranges or exact totals) for the game; each outcome covers a different span of combined points—check the market description on KALSHI for the exact bins and endpoints.
Home-team advantages can affect scoring through crowd influence, travel fatigue, and familiarity with local conditions; assess how each team historically performs at home and on the road and whether travel or venue conditions favor more conservative or aggressive game plans.
Significant injuries—especially to starting quarterbacks, key receivers, or a top defensive playmaker—can materially change scoring expectations; markets often move quickly when official injury reports or depth-chart changes are announced, so monitor those updates in real time.
Direct head-to-head history can be informative but is often limited and context-dependent; more useful are recent-season scoring trends, opponent-adjusted offensive and defensive metrics, and the current-season form of key units when projecting the likely total for this specific matchup.