| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Ziaire Williams: 10+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Ziaire Williams: 15+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Ziaire Williams: 20+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Nic Claxton: 10+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Nic Claxton: 15+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Nic Claxton: 20+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Nic Claxton: 25+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Noah Clowney: 10+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Noah Clowney: 15+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Noah Clowney: 20+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Noah Clowney: 25+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Precious Achiuwa: 10+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Precious Achiuwa: 15+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Precious Achiuwa: 20+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Precious Achiuwa: 25+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| DeMar DeRozan: 15+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| DeMar DeRozan: 20+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| DeMar DeRozan: 25+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| DeMar DeRozan: 30+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks traders to predict which points-range outcome will occur in the Sacramento at Brooklyn game; it matters because total-points markets aggregate expectations about tempo, shooting accuracy, and player availability into tradable prices.
Sacramento and Brooklyn have contrasting offensive profiles and matchup dynamics that influence expected scoring; venue (Brooklyn home court), recent rest, and roster composition all shape the likely pace and efficiency. Historical meetings between these franchises provide context but must be adjusted for offseason moves, injuries, and in-season changes to rotations and coaching strategies.
Market prices indicate the collective view on which scoring-range outcome is most likely and will change as new information (injuries, starting lineups, in-season trends) arrives; use prices to compare implied expectations across outcomes rather than as fixed forecasts.
The 11 outcomes represent discrete scoring-range options or thresholds for the total points scored in the game; consult the event description on KALSHI for the exact range cutoffs and how each outcome is defined.
The event page currently lists the close time as TBD; on many platforms markets close at a predefined pregame cutoff (often just before tipoff) but you should check the KALSHI event page for the confirmed close time and any updates.
Whether overtime counts depends on the market rules displayed on the event page; many total-points markets include overtime unless explicitly excluded, so verify the rule specified for this listing.
Monitor starting lineup confirmations, injury reports for each team’s leading scorers and ball-handlers, minutes-management or rest decisions, and any late scratches—changes to these items materially shift expected scoring and pace.
Past head-to-head games offer useful pattern information about how the teams match up defensively and how scoring tends to distribute, but they must be adjusted for current rosters, injuries, coaching changes, and in-season form rather than used as direct predictors.