| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Over 2.5 goals scored | 49% | 48¢ | 49¢ | — | $56 | Trade → |
| Over 3.5 goals scored | 0% | 26¢ | 28¢ | — | $0 | Trade → |
| Over 1.5 goals scored | 0% | 73¢ | 75¢ | — | $0 | Trade → |
| Over 4.5 goals scored | 0% | 12¢ | 13¢ | — | $0 | Trade → |
This market asks which total-goals outcome will occur in the Bristol City at Port Vale match and aggregates public expectations about scoring. It matters because totals markets summarize evolving information (lineups, form, weather) into a single price signal traders can use to express views on how many goals the game will produce.
Bristol City and Port Vale are meeting in a competitive club fixture; whether this is a league match, cup tie, or other competition affects selection and incentives. Recent seasons, each club’s tactical approach and scoring patterns, plus any scheduling congestion or travel, help shape pre-match expectations for total goals.
Market prices for totals reflect the consensus view of participants about which goal-range will occur and will move as new, relevant information arrives (team news, weather, injuries). Traders interpret price changes as updates to collective expectations rather than fixed forecasts.
The official close time for this market is listed on the market page and is currently TBD; markets for match totals commonly close at or shortly before kickoff, so check the Kalshi market page for the definitive close time.
'Totals' refers to the combined number of goals scored by both teams in the match; this market is resolved against predefined ranges or over/under thresholds specified on the event page.
Lineups and late absences matter a lot: the presence or absence of key scorers or central defenders will typically shift expectations for total goals, so markets often move when official lineups are published or when injury/suspension updates arrive.
Head-to-head results can provide context about how the matchup has historically unfolded, but they may be less predictive than recent form, current squad strength, and match context—especially when sample sizes are small or teams have changed personnel or leagues.
In-play events materially change scoring dynamics: red cards, penalties, and significant injuries alter incentives and expected goal rates, and markets typically react quickly; if you trade live, focus on how each event shifts likely scoring pace and the remaining time in the match.