| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| James Harden: 8+ | 53% | 32¢ | 53¢ | — | $799 | Trade → |
| Ausar Thompson: 4+ | 42% | 33¢ | 42¢ | — | $228 | Trade → |
| Dennis Schröder: 6+ | 30% | 0¢ | 31¢ | — | $39 | Trade → |
| Dennis Schröder: 5+ | 43% | 28¢ | 42¢ | — | $22 | Trade → |
| Cade Cunningham: 6+ | 95% | 88¢ | 96¢ | — | $8 | Trade → |
| Cade Cunningham: 10+ | 52% | 51¢ | 54¢ | — | $8 | Trade → |
| Ausar Thompson: 6+ | 17% | 0¢ | 17¢ | — | $6 | Trade → |
| Ausar Thompson: 3+ | 3% | 41¢ | 58¢ | — | $3 | Trade → |
| James Harden: 6+ | 0% | 0¢ | 81¢ | — | $0 | Trade → |
| James Harden: 10+ | 0% | 0¢ | 30¢ | — | $0 | Trade → |
| Dennis Schröder: 8+ | 0% | 0¢ | 15¢ | — | $0 | Trade → |
| Tobias Harris: 4+ | 0% | 0¢ | 28¢ | — | $0 | Trade → |
| Dennis Schröder: 2+ | 0% | 0¢ | 96¢ | — | $0 | Trade → |
| Cade Cunningham: 14+ | 0% | 0¢ | 16¢ | — | $0 | Trade → |
| Ausar Thompson: 2+ | 0% | 0¢ | 83¢ | — | $0 | Trade → |
| Tobias Harris: 3+ | 0% | 24¢ | 44¢ | — | $0 | Trade → |
| James Harden: 4+ | 0% | 0¢ | 99¢ | — | $0 | Trade → |
| Dennis Schröder: 4+ | 0% | 0¢ | 61¢ | — | $0 | Trade → |
| Cade Cunningham: 8+ | 0% | 74¢ | 78¢ | — | $0 | Trade → |
| Cade Cunningham: 12+ | 0% | 5¢ | 31¢ | — | $0 | Trade → |
| Tobias Harris: 6+ | 0% | 0¢ | 28¢ | — | $0 | Trade → |
| Tobias Harris: 2+ | 0% | 0¢ | 70¢ | — | $0 | Trade → |
| Tobias Harris: 8+ | 0% | 0¢ | 28¢ | — | $0 | Trade → |
| James Harden: 12+ | 0% | 0¢ | 16¢ | — | $0 | Trade → |
| Ausar Thompson: 8+ | 0% | 0¢ | 18¢ | — | $0 | Trade → |
This market asks traders to predict the distribution of assists in the Detroit at Cleveland game, a measure of playmaking and team offense that can affect fantasy scores and game narratives.
Detroit and Cleveland have contrasting offensive identities that shape assist totals: one team may rely more on isolation scoring while the other emphasizes ball movement and pick‑and‑roll creation. Recent seasons, coaching styles, and rotations (starters vs. bench usage) have produced variable assist rates in this matchup, so outcomes often reflect both season trends and short‑term availability.
Market prices represent the consensus expectation of participants about where the game’s assists will fall; use them as a real‑time signal that integrates public information like injuries, rotations, and pace rather than as definitive predictions.
The event page on the platform lists the specific closing time; markets of this type commonly close before tip‑off or at a platform‑specified time, so check the event details for the exact deadline.
The 25 outcomes are discrete buckets that partition possible assist totals (for example ranges or exact counts); consult the market description on the platform to see how each outcome maps to an assists range or score.
Whether overtime counts depends on the market’s settlement rules; the event description will state if assists from overtime are included, so verify that rule before trading.
Primary playmakers and lead guards drive assist totals — for example the teams’ main ball‑handlers and primary pick‑and‑roll facilitators. Monitor the starting point guard, any designated primary playmaker, and secondary creators who log high usage or minutes to assess impact.
Past head‑to‑head assists can reveal tendencies in this matchup (pace, coaching matchups), but treat small samples cautiously: weigh recent form, roster changes, injury news, and current season playstyle more heavily than isolated past games.