| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Washington wins by over 2.5 goals | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| St. Louis wins by over 1.5 goals | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| St. Louis wins by over 2.5 goals | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Washington wins by over 1.5 goals | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market lets traders bet on the point-spread outcome for the Washington at St. Louis matchup, showing how the market expects the final scoring margin to fall into one of several categories. It matters because the spread encapsulates expectations about relative team strength and game-day factors that affect betting and strategy.
Washington and St. Louis represent two teams whose matchup-level context — roster health, recent form, and where the game is played — will shape market expectations. Historical meetings can offer context but rosters, coaching changes, and short-term trends often matter more for a single-game spread. Because the market closes at a specified time before or during the contest (TBD for this listing), late-breaking information can materially change prices.
Prediction market odds express the consensus view of traders about which spread outcome will occur and update as new information arrives. Use them as a real-time signal of market sentiment, not as an immutable forecast: check underlying game information (injuries, starters, weather) for explanatory context.
The listing shows the close time as TBD; check the market page for the official close time and any updates before placing a trade.
This market divides the possible final scoring margin into four outcome categories; consult the market's outcome labels and description on the platform to see the exact margin ranges or cover/loss thresholds for each outcome.
Late injury reports or starting lineup announcements, major weather updates at the venue, and heavy trading flow or large orders are the items most likely to shift market prices for this spread.
Head-to-head history can provide context on stylistic matchups, but roster changes, coaching, and recent performance usually have greater relevance for a single game's spread; treat historical data as one input among many.
Monitor the official game-day injury and starter reports, final weather and field conditions, any late strategic changes announced by coaches, and the market's price movement to see how new information is being priced in.