| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Josh Hart: 15+ | 34% | 0¢ | 34¢ | — | $138 | Trade → |
| Karl-Anthony Towns: 20+ | 44% | 0¢ | 44¢ | — | $88 | Trade → |
| Karl-Anthony Towns: 15+ | 74% | 0¢ | 74¢ | — | $46 | Trade → |
| Jalen Brunson: 25+ | 51% | 42¢ | 51¢ | — | $39 | Trade → |
| Mikal Bridges: 20+ | 25% | 0¢ | 25¢ | — | $38 | Trade → |
| Chet Holmgren: 20+ | 43% | 0¢ | 43¢ | — | $20 | Trade → |
| Chet Holmgren: 15+ | 72% | 0¢ | 72¢ | — | $13 | Trade → |
| Josh Hart: 20+ | 16% | 0¢ | 16¢ | — | $11 | Trade → |
| Mikal Bridges: 15+ | 50% | 0¢ | 50¢ | — | $9 | Trade → |
| Jalen Brunson: 20+ | 89% | 0¢ | 80¢ | — | $2 | Trade → |
| Karl-Anthony Towns: 30+ | 0% | 0¢ | 11¢ | — | $0 | Trade → |
| Jalen Brunson: 15+ | 0% | 0¢ | 89¢ | — | $0 | Trade → |
| Mikal Bridges: 25+ | 0% | 0¢ | 12¢ | — | $0 | Trade → |
| Karl-Anthony Towns: 25+ | 0% | 0¢ | 22¢ | — | $0 | Trade → |
| Chet Holmgren: 10+ | 0% | 0¢ | 97¢ | — | $0 | Trade → |
| Luguentz Dort: 20+ | 0% | 0¢ | 10¢ | — | $0 | Trade → |
| Luguentz Dort: 10+ | 0% | 0¢ | 49¢ | — | $0 | Trade → |
| Jalen Brunson: 35+ | 0% | 0¢ | 19¢ | — | $0 | Trade → |
| OG Anunoby: 15+ | 0% | 44¢ | 54¢ | — | $0 | Trade → |
| Chet Holmgren: 25+ | 0% | 0¢ | 22¢ | — | $0 | Trade → |
| Luguentz Dort: 15+ | 0% | 0¢ | 20¢ | — | $0 | Trade → |
| Josh Hart: 10+ | 0% | 0¢ | 67¢ | — | $0 | Trade → |
| OG Anunoby: 10+ | 0% | 0¢ | 89¢ | — | $0 | Trade → |
| OG Anunoby: 25+ | 0% | 0¢ | 16¢ | — | $0 | Trade → |
| OG Anunoby: 20+ | 0% | 0¢ | 32¢ | — | $0 | Trade → |
| Jalen Brunson: 30+ | 0% | 0¢ | 34¢ | — | $0 | Trade → |
| Mikal Bridges: 10+ | 0% | 0¢ | 83¢ | — | $0 | Trade → |
This market asks how many points will be scored in the Oklahoma City at New York game and lets traders express views on scoring outcomes. It matters because scoring expectations drive in-play strategy, hedging, and market pricing for related bets.
Oklahoma City and New York typically present contrasting styles: one team may play faster with higher possession counts while the other emphasizes defense and half-court sets. Short-term factors like injuries, recent form, and rotations can shift expected scoring from historical baselines. The market's 27 outcomes indicate a fairly granular set of possible point totals or ranges.
Market prices reflect collective expectations about which point outcomes are more or less likely; lower-priced outcomes indicate stronger market preference while higher-priced ones indicate less market interest. Read outcome labels and recent trade activity to see where traders are concentrating exposure.
Check the event's outcome labels on the KALSHI page: 'Points' can mean combined total points for both teams or an individual team’s point total depending on this specific market. The outcome descriptions will indicate whether each option is a discrete total or a range.
Because the close time is listed as TBD, monitor the event page and any KALSHI notifications; trading windows for points markets typically close at or shortly before official game start unless otherwise specified, but the platform will publish the final cutoff once set.
The market is most sensitive to availability and projected minutes of each team’s leading scorers and primary playmakers, plus any high-usage bench scorers. Late scratches, load management decisions, or a change in starting lineup can materially shift expected totals.
Those 27 outcomes likely represent a set of discrete totals or score-range buckets for this game; read each outcome label to see the exact point interval or total. A larger number of outcomes gives more granularity, so compare trade sizes across outcomes to gauge market concentration.
Home-court can influence pace and shooting comfort, while Oklahoma City traveling east to New York can introduce fatigue and schedule disruption. Expect visiting teams to sometimes play more conservatively early, and consider local arena pace and referee tendencies as part of scoring expectations.