| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Shai Gilgeous-Alexander: 30+ | 60% | 59¢ | 60¢ | — | $8K | Trade → |
| Nikola Jokić: 20+ | 82% | 75¢ | 81¢ | — | $6K | Trade → |
| Nikola Jokić: 25+ | 60% | 59¢ | 60¢ | — | $5K | Trade → |
| Nikola Jokić: 30+ | 37% | 36¢ | 37¢ | — | $4K | Trade → |
| Shai Gilgeous-Alexander: 35+ | 37% | 36¢ | 37¢ | — | $3K | Trade → |
| Luguentz Dort: 15+ | 21% | 19¢ | 21¢ | — | $2K | Trade → |
| Christian Braun: 15+ | 34% | 30¢ | 33¢ | — | $2K | Trade → |
| Luguentz Dort: 10+ | 52% | 50¢ | 52¢ | — | $2K | Trade → |
| Christian Braun: 20+ | 14% | 8¢ | 12¢ | — | $2K | Trade → |
| Nikola Jokić: 35+ | 20% | 19¢ | 20¢ | — | $2K | Trade → |
| Shai Gilgeous-Alexander: 45+ | 8% | 4¢ | 7¢ | — | $1K | Trade → |
| Aaron Gordon: 20+ | 18% | 17¢ | 18¢ | — | $1K | Trade → |
| Aaron Gordon: 15+ | 40% | 38¢ | 40¢ | — | $980 | Trade → |
| Cameron Johnson: 10+ | 50% | 49¢ | 50¢ | — | $628 | Trade → |
| Christian Braun: 10+ | 67% | 63¢ | 67¢ | — | $415 | Trade → |
| Shai Gilgeous-Alexander: 40+ | 19% | 17¢ | 18¢ | — | $401 | Trade → |
| Aaron Gordon: 10+ | 73% | 68¢ | 71¢ | — | $351 | Trade → |
| Luguentz Dort: 20+ | 1% | 2¢ | 5¢ | — | $260 | Trade → |
| Cameron Johnson: 25+ | 4% | 1¢ | 3¢ | — | $244 | Trade → |
| Cameron Johnson: 15+ | 22% | 9¢ | 22¢ | — | $110 | Trade → |
| Aaron Gordon: 25+ | 8% | 5¢ | 8¢ | — | $1 | Trade → |
| Cameron Johnson: 20+ | 7% | 1¢ | 7¢ | — | $1 | Trade → |
This market asks how the scoring outcome will fall in the Denver at Oklahoma City game and matters to traders who want to express views on game scoring, hedge other positions, or trade on late information such as injuries or starting lineups.
Denver and Oklahoma City have distinct styles that typically influence total scoring: Denver has recently been associated with high-usage star scoring and the effects of altitude at home, while Oklahoma City has emphasized pace and transition opportunities. Market structure (22 discrete outcomes) lets participants price a wide range of possible point totals or ranges and update positions as lineup news, injuries, and matchup information arrive.
Market prices reflect the consensus view of traders about which point-range outcome will occur and will move as new information comes in; interpret movements as shifts in market expectations rather than fixed forecasts, and consult the market’s outcome labels and resolution rules on KALSHI for exact definitions.
The market close time is listed as TBD on the event page; final outcome is determined after the official game is completed and KALSHI applies its stated resolution rules using the designated official data source. Check the market page for any updates to the close time and the platform’s resolution policy.
Outcome labels on the market page define whether each option covers combined totals, one team’s point ranges, or exact totals; because formats vary by market, consult the market's outcome descriptions on KALSHI to see which point metric (game total, team total, or range bins) is being traded.
KALSHI resolves markets using the official statistical provider specified on the market page (typically the league box score or another designated official source); check the event’s rules section for the exact provider and procedures for ties or scoring corrections.
Watch injury updates and confirmed scratches, announced starting lineups, coach comments about rotations, and any late trade or illness news — these items directly change expected scoring and often cause rapid price movement in the hours or minutes before tip-off.
Use historical head-to-head and venue splits as context for tendencies (for example, how each team has performed offensively and defensively at home versus away), but combine that with current-season form, roster availability, and schedule context because historical averages may not reflect the specific conditions of this matchup.