| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Dallas wins by over 1.5 goals | 34% | 33¢ | 34¢ | — | $13K | Trade → |
| Calgary wins by over 1.5 goals | 26% | 24¢ | 26¢ | — | $1K | Trade → |
| Dallas wins by over 2.5 goals | 22% | 20¢ | 22¢ | — | $649 | Trade → |
| Calgary wins by over 2.5 goals | 14% | 14¢ | 17¢ | — | $17 | Trade → |
This market asks which spread outcome will occur in the Dallas Stars at Calgary Flames game, focusing on the margin of victory rather than just the winner. It matters because spread outcomes capture expectations about relative team strength, goaltending, and game conditions.
Dallas and Calgary are NHL clubs with differing styles; historical matchups, roster construction, and recent form all shape expectations for goal margins. Game-specific variables such as starting goaltenders, injuries, travel and schedule (back-to-backs) can materially shift the likely spread. Market activity and trading volume reflect how participants incorporate that information into pricing.
Market odds express the collective judgment about which spread outcome is most likely and update as new information arrives (lineup news, injuries, game-day conditions). Treat prices as real-time signals that change with developments rather than fixed forecasts.
Each outcome corresponds to a specific range of goal-margin results (which side covers the preset spread or specific goal-differential buckets). Consult the market page for the exact definitions of the four outcome buckets used in this event.
Late scratches—especially to a starting goalie or top-line forward—typically trigger rapid price movement as traders reassess the expected goal margin; markets often react quickly once official roster moves are announced.
TBD means the platform has not announced a firm close time; in practice, spread markets typically close shortly before puck drop or when lineups are locked. Monitor the market page for the official closing update from the operator.
Key items include the confirmed starting goalies, recent goals-for and goals-against trends, special teams rates, rest/travel status, and any head-to-head or situational splits (home/road, back-to-back). Advanced metrics like expected goals can help assess underlying performance.
Historical head-to-head data can highlight matchup tendencies (e.g., which team typically controls tempo or exploits the other's weaknesses), but weigh that against current-season form, roster health, and goaltending—short-term trends and game-specific factors often matter more than long-ago results.