| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| CJ McCollum: 30+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Onyeka Okongwu: 15+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Onyeka Okongwu: 25+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Jonathan Kuminga: 15+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Onyeka Okongwu: 10+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Dyson Daniels: 10+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Jonathan Kuminga: 20+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Onyeka Okongwu: 20+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Jalen Johnson: 35+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Nickeil Alexander-Walker: 25+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Dyson Daniels: 20+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Dyson Daniels: 15+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Draymond Green: 15+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| CJ McCollum: 25+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Draymond Green: 10+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| CJ McCollum: 15+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| CJ McCollum: 20+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Nickeil Alexander-Walker: 20+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Nickeil Alexander-Walker: 15+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Jonathan Kuminga: 10+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Jonathan Kuminga: 25+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Jalen Johnson: 30+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Jalen Johnson: 20+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Jalen Johnson: 25+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Nickeil Alexander-Walker: 30+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Draymond Green: 20+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market offers bets on the combined points outcome for the NBA game Golden State at Atlanta. It matters because it aggregates market expectations about scoring given team styles, injuries, and game context.
Golden State typically features heavy perimeter shooting and high-volume ball-handling that can produce quick scoring bursts; Atlanta often plays at an up-tempo pace that creates transition opportunities and higher possession counts. Totals markets for this matchup reflect the interaction of those styles plus matchup-specific defense, personnel, and coaching adjustments.
Market prices here represent collective expectations for the game's combined point total across the available outcome buckets; movement in prices signals how new information (injuries, lineup news, rest, etc.) shifts those expectations.
The event page lists the close time as TBD; traders should watch for the official close announcement from the platform—markets typically stop accepting trades shortly before game tip-off or at the published close.
The 22 outcomes correspond to discrete point-total buckets or specific ranges for the combined game score; the winning outcome is determined by which bucket contains the official final combined score at settlement.
Late absences for high-usage scorers or primary playmakers tend to reduce expected totals, while unexpected returns or depth additions can increase them; markets often react quickly, so traders monitor official injury reports and coaching minutes guidance.
Home court can influence pace, travel fatigue, and shooting efficiency—factors the market prices in. For this matchup, Atlanta’s home tempo and arena conditions are part of the assessment that moves odds as new data arrive.
Settlement follows the platform’s official rules and the game’s official reported final score; if the platform treats postponed or canceled games as void, trades may be refunded, so check KALSHI’s settlement and force-majeure policies for exact handling.