| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Patrick Kane: 2+ | 23% | 0¢ | 100¢ | — | $185 | Trade → |
| Dylan Larkin: 2+ | 31% | 0¢ | 100¢ | — | $155 | Trade → |
| Lucas Raymond: 2+ | 40% | 0¢ | 100¢ | — | $78 | Trade → |
| Marco Kasper: 1+ | 36% | 99¢ | 100¢ | — | $72 | Trade → |
| Ryan O'Reilly: 2+ | 33% | 0¢ | 100¢ | — | $72 | Trade → |
| Alex DeBrincat: 1+ | 99% | 99¢ | 100¢ | — | $59 | Trade → |
| Dylan Larkin: 1+ | 65% | 0¢ | 100¢ | — | $58 | Trade → |
| Alex DeBrincat: 2+ | 34% | 0¢ | 100¢ | — | $28 | Trade → |
| Erik Haula: 1+ | 41% | 0¢ | 100¢ | — | $11 | Trade → |
| Moritz Seider: 1+ | 54% | 0¢ | 100¢ | — | $10 | Trade → |
| Roman Josi: 1+ | 99% | 99¢ | 100¢ | — | $1 | Trade → |
| Steven Stamkos: 2+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Steven Stamkos: 3+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Moritz Seider: 2+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Luke Evangelista: 2+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Filip Forsberg: 3+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Filip Forsberg: 2+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Michael Bunting: 2+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Andrew Copp: 2+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Dylan Larkin: 3+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Erik Haula: 2+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Brady Skjei: 2+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Jonathan Marchessault: 2+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Alex DeBrincat: 3+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Roman Josi: 3+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Roman Josi: 2+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Patrick Kane: 3+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Lucas Raymond: 3+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Marco Kasper: 2+ | 0% | 99¢ | 100¢ | — | $0 | Trade → |
| Luke Evangelista: 1+ | 0% | 99¢ | 100¢ | — | $0 | Trade → |
| Filip Forsberg: 1+ | 0% | 99¢ | 100¢ | — | $0 | Trade → |
| Ryan O'Reilly: 3+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Steven Stamkos: 1+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Jonathan Marchessault: 1+ | 0% | 99¢ | 100¢ | — | $0 | Trade → |
| Patrick Kane: 1+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Ryan O'Reilly: 1+ | 0% | 99¢ | 100¢ | — | $0 | Trade → |
| Lucas Raymond: 1+ | 0% | 99¢ | 100¢ | — | $0 | Trade → |
| Andrew Copp: 1+ | 0% | 99¢ | 100¢ | — | $0 | Trade → |
| Michael Bunting: 1+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Brady Skjei: 1+ | 0% | 0¢ | 100¢ | — | $0 | Trade → |
This market lets traders forecast the total combined points (goals) scored in the Detroit Red Wings at Nashville Predators game; it matters because prices aggregate public expectations about scoring and react to new information ahead of puck drop.
Detroit and Nashville have different offensive and defensive tendencies that shape scoring expectations; coaching, roster matchups, and recent form all feed into how many goals the game might produce. The market for this event currently lists 40 possible outcomes and has recorded modest trading volume, which can affect liquidity and price responsiveness. The market closure time is listed as TBD, so participants should monitor updates for lineup and start-time locks.
Market prices represent the collective view of which total-goals outcomes traders expect most; prices move as new information arrives (injuries, starters, rest). Use prices as a continuously updated signal rather than a fixed forecast, and expect rapid changes around lineup and starter announcements.
It measures the total combined goals scored by both teams in the game; individual outcomes correspond to specific totals or ranges as listed on the market page.
Closure is listed as TBD on the event page, but most game total markets lock at puck drop or when starting lineups/goalies are confirmed; watch the market page for the firm lock time and any official notices.
A goalie change can materially alter expected scoring because goalies differ in save tendencies and style; major starter updates typically prompt quick price moves, so reassess market exposure when a change is announced.
Head-to-head trends provide context on matchup tendencies but should be weighed alongside current rosters, injuries, goaltenders, and situational factors like rest; historical patterns lose predictive power when personnel or context changes.
A large number of discrete outcomes spreads liquidity thinly, and relatively low traded volume means individual trades can move prices more; consider using limit orders, checking order book depth, and being cautious about placing large positions relative to market size.