| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| James Harden: 1+ | 0% | 40¢ | 92¢ | — | $0 | Trade → |
| James Harden: 2+ | 0% | 3¢ | 55¢ | — | $0 | Trade → |
| Cade Cunningham: 3+ | 0% | 0¢ | 48¢ | — | $0 | Trade → |
| Tobias Harris: 2+ | 0% | 0¢ | 42¢ | — | $0 | Trade → |
| Ausar Thompson: 2+ | 0% | 0¢ | 99¢ | — | $0 | Trade → |
| Cade Cunningham: 2+ | 0% | 20¢ | 54¢ | — | $0 | Trade → |
| Ausar Thompson: 3+ | 0% | 0¢ | 98¢ | — | $0 | Trade → |
| Evan Mobley: 1+ | 0% | 0¢ | 99¢ | — | $0 | Trade → |
| Evan Mobley: 2+ | 0% | 0¢ | 98¢ | — | $0 | Trade → |
| Cade Cunningham: 1+ | 0% | 54¢ | 98¢ | — | $0 | Trade → |
| Dennis Schröder: 2+ | 0% | 0¢ | 98¢ | — | $0 | Trade → |
| Dennis Schröder: 1+ | 0% | 0¢ | 99¢ | — | $0 | Trade → |
| Ausar Thompson: 4+ | 0% | 0¢ | 97¢ | — | $0 | Trade → |
| Tobias Harris: 1+ | 0% | 0¢ | 99¢ | — | $0 | Trade → |
| James Harden: 3+ | 0% | 0¢ | 37¢ | — | $0 | Trade → |
| Dennis Schröder: 3+ | 0% | 0¢ | 97¢ | — | $0 | Trade → |
| Tobias Harris: 3+ | 0% | 0¢ | 97¢ | — | $0 | Trade → |
| Evan Mobley: 3+ | 0% | 0¢ | 97¢ | — | $0 | Trade → |
This market lets traders take positions on the number of steals recorded in the Detroit at Cleveland game. It matters because steals are a high-leverage event that signal defensive disruption and can shift momentum and in-game outcomes.
Detroit and Cleveland bring different defensive philosophies and personnel that affect turnover creation; coaching, rotations, and recent roster moves can change how aggressively each team presses or gambles for steals. Head-to-head history and recent form provide context, but single-game variance is high—matchups, minutes and game pace often drive actual results.
Market prices aggregate participant expectations about which steal-count outcome will occur; treat them as a real-time signal to combine with your own scouting and information about injuries, lineups, and game conditions.
The event page lists the close as TBD; on most platforms markets close at or just before the official game start or at a platform-specified time. Check the market page or platform notifications for the exact close time before trading.
Each outcome corresponds to a specific discrete steal total or a defined range for this matchup (for example, exact counts or buckets). Consult the market’s outcome list on the platform to see whether outcomes are team-specific (Detroit or Cleveland) or represent the combined game total.
Whether overtime counts depends on the contract terms specified by the platform. Because the event page marks close as TBD, read the market rules or the official contract description to confirm whether official stats include overtime.
Players who defend the ball, play heavy minutes, or specialize in on-ball pressure and passing-lane reads will drive the steals count. Monitor starters, primary perimeter defenders, any defensive specialists off the bench, and recent minutes trends to assess who will create or concede steals.
Use head-to-head and recent-season trends to establish context, but weight them alongside current-season form, lineup changes, injuries, and game pace projections. Because steals are volatile, place more emphasis on recent matchup-specific information (who is playing, minutes, matchup advantages) than long-term averages.