| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Bologna wins by over 1.5 goals | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Sassuolo wins by over 2.5 goals | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Sassuolo wins by over 1.5 goals | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Bologna wins by over 2.5 goals | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks which spread outcome will occur in the Bologna at Sassuolo match; spreads capture the expected margin between the two teams and matter for traders who want exposure to match competitiveness rather than only the winner.
Bologna and Sassuolo are Italian top-flight clubs whose matches can produce a range of scorelines and margins; spread markets distill those possible margins into discrete outcomes. Historical matchups, current season form, and each club's tactical approach shape expectations for how wide or narrow a result might be.
Market prices on Kalshi for this event represent the trading consensus about which spread outcome will occur and will move as new information arrives (lineups, injuries, weather, in-play events). Use prices as real-time signals of market sentiment, not guarantees of the actual result.
The four outcomes correspond to predefined spread scenarios for this match (different margin buckets or which side covers the spread). The exact wording and payout conditions are listed on the Kalshi market page for this event, so check the market description for precise definitions.
The market shows a TBD close time; on Kalshi similar markets typically close at or shortly before kickoff or when official starting XIs are posted. Monitor the market page and platform notifications for the confirmed close time.
Late changes to starters—especially to key defenders, creators, or goalkeepers—can materially shift expected margins, prompting immediate price movement across the spread outcomes as traders update their assessments.
Focus on the distribution of past margins (how often matches were tight versus one-sided), recent head-to-head trends, and home/away splits rather than isolated scorelines; give greater weight to recent seasons and matches played under similar lineups or tactical setups.
Low volume makes prices more sensitive to individual trades, can widen the effective spread between buy and sell interest, and increases execution risk. If liquidity is limited, small orders may move prices substantially, so consider order size and potential slippage when participating.