| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Washington wins by over 2.5 goals | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| New Jersey wins by over 2.5 goals | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| New Jersey wins by over 1.5 goals | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Washington wins by over 1.5 goals | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks which side will cover the point spread in the New Jersey at Washington matchup; it matters because spread markets aggregate expectations about the likely margin of victory and respond quickly to new information.
New Jersey and Washington are NHL franchises with varying recent performance, roster turnover, and injury histories that shape expectations for any given game. Spread markets for their matchup reflect pregame projections about starting goaltenders, special teams, travel and rest, and recent head-to-head results rather than just which team wins.
Market prices in a spread market summarize the crowd’s current view of expected margins; movements in price indicate how traders are updating that view as new information (lineups, injuries, weather, etc.) arrives.
The market close is listed as TBD; spread markets typically stop trading shortly before the scheduled puck drop, so monitor the platform for the official close time and any updates.
The four outcomes are discrete resolution buckets tied to specific spread thresholds for the game; the platform defines the exact thresholds, and each outcome resolves based on the final margin relative to those thresholds.
Starting goalie confirmations, late scratches or lineup changes to top-six forwards and top-four defensemen, injury-report upgrades/downgrades, and any coach statements about deployment or strategy are the biggest drivers.
A goalie change is often one of the largest single pieces of information for a spread market because goalie performance directly influences expected goals-against; assess the replacement’s recent form and sample size when re-evaluating the market.
Use head-to-head trends and recent form as context, but weigh recency, location (home/away splits), and roster continuity; small-sample streaks can be noisy, so combine them with lineup and goalie info rather than treating them as definitive.