| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Thomas Harley: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Wyatt Johnston: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Miro Heiskanen: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Mikhail Sergachev: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Miro Heiskanen: 3+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Mavrik Bourque: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Dylan Guenther: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Matt Duchene: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Thomas Harley: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Dylan Guenther: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Clayton Keller: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Mikhail Sergachev: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Mikhail Sergachev: 3+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Jason Robertson: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Matt Duchene: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Jason Robertson: 3+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Clayton Keller: 3+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Wyatt Johnston: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Miro Heiskanen: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Jason Robertson: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Clayton Keller: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Mavrik Bourque: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Nick Schmaltz: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Logan Cooley: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Nick Schmaltz: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks participants to forecast the number of assists associated with the UTA Mammoth at DAL Stars matchup. It matters because assists reflect playmaking, game flow, and situational advantages that bettors and analysts track to price risk and anticipate outcomes.
The market covers a single head-to-head game between two club teams (UTA Mammoth and DAL Stars); its outcomes are split into 25 discrete options that map to different assist totals or ranges. Background context that typically affects these markets includes each team’s recent style of play, any short-term roster changes, and whether the game is home or away—factors that persistently shape assist distributions across similar games.
Prediction market prices represent the crowd’s current view about which discrete assist outcome is most likely and will move as new information arrives (lineups, injuries, game-time conditions). They are signals of consensus expectation, not guarantees; always pair them with up-to-the-minute game information before trading.
Check the market’s rule text on the platform: it will state whether outcomes refer to total assists by one team, combined game assists, or assists by a specific player, and how the 25 discrete outcomes map to numeric totals or ranges.
It means the market is divided into 25 distinct result buckets (individual totals or ranges). Each outcome corresponds to a specific assist total or a range of totals; consult the market page to see the exact mapping and settlement rules.
The event’s close time is listed as TBD—most game-assist markets close at a defined game milestone (for example, opening faceoff/puck drop or game end). Check the market page and the platform’s settlement policy for the precise trigger and any post-game review procedures.
Focus on each team’s primary passers and set-piece playmakers (top distribution players, power-play unit leaders, and the lines most used in offensive situations), plus any players returning from injury or recently promoted to expanded roles.
Late scratches, unexpected injuries, or early penalties can materially change assist expectations by altering who handles playmaking duties or by changing game tempo; markets typically react quickly, so monitor official lineups and live news feeds right up to game start.