| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| UCLA wins the 1H by over 9.5 points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| UCLA wins the 1H by over 6.5 points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| UConn wins the 1H by over 9.5 points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| UCLA wins the 1H by over 3.5 points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| UConn wins the 1H by over 12.5 points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| UConn wins the 1H by over 18.5 points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| UConn wins the 1H by over 6.5 points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| UCLA wins the 1H by over 12.5 points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| UConn wins the 1H by over 3.5 points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| UConn wins the 1H by over 15.5 points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks how the point spread will fall for the first half of the UCLA vs UConn game — effectively betting on which team covers the margin during the first 20 minutes. First-half markets matter for traders who want exposure to early-game dynamics without the noise of late-game comebacks.
UCLA and UConn are major college basketball programs with distinct styles, personnel, and coaching approaches; their matchups draw attention because early-game matchups and tempo can swing the first half margin. The market lists 10 discrete outcomes and currently shows a closing time of TBD on the trading platform, so participants should monitor updates as line releases, injuries, and official starting lineups become available. Historical program success is a background factor, but specific first-half expectations depend on current-season rosters and matchup details.
Market prices reflect collective expectations about the first-half spread and will move as new information arrives (injuries, starters, matchup reports, in-game events). Interpreting odds here means tracking how the market rebalances in response to these inputs rather than treating any single quote as final.
The event listing shows the market closes as TBD; check the KALSHI event page or market feed for the official close time and any updates from the market creator.
The 10 outcomes correspond to discrete first-half spread ranges or specific margin bins defined by the market creator; the platform will label each outcome so traders can see which margin interval each outcome covers.
Starters set matchups and minute distributions for the first half — a strong starter or a late scratch can materially change expected scoring and defensive matchups, so update your assessment when official lineups are released near tipoff.
Yes — markets update as new information arrives, so key in-game events (early injuries, momentum swings, foul trouble, or an unexpectedly fast/slow pace) will typically move prices during live trading windows.
Head-to-head history and recent first-half splits can provide context, but prioritize recent season data, opponent-adjusted performance, and matchup-specific indicators (e.g., how each team defends the perimeter) because college rosters change frequently and small samples can be misleading.