| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Orlando over 113.5 points scored | 1% | 1¢ | 72¢ | — | $1 | Trade → |
| Orlando over 101.5 points scored | 0% | 32¢ | 99¢ | — | $0 | Trade → |
| Minnesota over 105.5 points scored | 0% | 48¢ | 99¢ | — | $0 | Trade → |
| Orlando over 104.5 points scored | 0% | 24¢ | 99¢ | — | $0 | Trade → |
| Minnesota over 108.5 points scored | 0% | 32¢ | 99¢ | — | $0 | Trade → |
| Orlando over 110.5 points scored | 0% | 6¢ | 81¢ | — | $0 | Trade → |
| Orlando over 98.5 points scored | 0% | 48¢ | 99¢ | — | $0 | Trade → |
| Orlando over 107.5 points scored | 0% | 16¢ | 90¢ | — | $0 | Trade → |
| Minnesota over 111.5 points scored | 0% | 24¢ | 99¢ | — | $0 | Trade → |
| Orlando over 119.5 points scored | 0% | 0¢ | 50¢ | — | $0 | Trade → |
| Minnesota over 126.5 points scored | 0% | 0¢ | 50¢ | — | $0 | Trade → |
| Orlando over 122.5 points scored | 0% | 0¢ | 46¢ | — | $0 | Trade → |
| Orlando over 116.5 points scored | 0% | 0¢ | 54¢ | — | $0 | Trade → |
| Minnesota over 117.5 points scored | 0% | 6¢ | 81¢ | — | $0 | Trade → |
| Minnesota over 129.5 points scored | 0% | 0¢ | 46¢ | — | $0 | Trade → |
| Minnesota over 114.5 points scored | 0% | 16¢ | 91¢ | — | $0 | Trade → |
| Minnesota over 123.5 points scored | 0% | 0¢ | 54¢ | — | $0 | Trade → |
| Minnesota over 120.5 points scored | 0% | 1¢ | 73¢ | — | $0 | Trade → |
This market asks how many points the Orlando and Minnesota teams will score in their matchup and lets traders express views on each team’s expected offensive output. It matters because team totals isolate scoring risk separate from game winner or point spread markets.
Orlando and Minnesota bring different offensive and defensive profiles that can influence scoring: one team may emphasize transition and three-point shooting while the other plays inside-out or controls tempo. Recent form, roster changes, and where the game is played all provide useful historical context, but single-game totals are often driven by short-term factors like injuries and rest. Head-to-head history can inform expectations but should be weighted against current-season trends and lineup availability.
Market prices reflect the collective view on whether each team’s scoring will fall into specific total ranges or cross posted lines; price movement signals new information entering the market (injuries, rotations, rest, betting flow). Use prices as a dynamic indicator, and always check the event rules to understand how outcomes are defined and settled.
The closing time is listed on the market page; if it is shown as TBD, the platform will set a closing time prior to the game—check the market interface for updates and final close notifications.
Those outcomes correspond to the distinct scoring ranges or named total options available for one or both teams on this market; view the market’s outcome list to see the exact labels and how each range is defined.
Player absences change scoring projections by altering usage and minutes distribution; markets typically adjust quickly to public reports, so monitor injury reports and official team announcements for the most impactful information.
Head-to-head history can highlight matchup tendencies, but prioritize recent season data, current rotations, and context (home/away, rest, injuries) because rosters and styles evolve and single-game totals are sensitive to short-term changes.
Settlement rules vary by platform and by market; consult the event’s settlement rules on KALSHI to see whether totals include overtime or are limited to regulation, and contact platform support if the rule is unclear.