This event group covers the professional English Premier League soccer match between Sunderland AFC and Fulham FC scheduled for February 22, 2026. Three related markets track the outcome: whether Sunderland wins, whether Fulham wins, and whether the match ends in a draw. All markets resolve based on the result after 90 minutes of regular play plus stoppage time, excluding extra time or penalties.
Polymarket specifies outcome-dependent cancellation logic (draw resolves Yes, wins resolve No), while Kalshi does not explicitly address cancellation, creating potential settlement ambiguity if the match is canceled without a makeup.
Hero Tip:
Verify with both platforms their cancellation protocol before the event date. If Kalshi defaults to No for all outcomes on cancellation, the draw market on Polymarket carries hidden upside risk. If Kalshi matches Polymarket's draw-Yes rule, no action needed.
Critical Divergence Points:
Polymarket: Three separate markets with outcome-specific cancellation rules. Sunderland win and Fulham win both resolve No if canceled; draw resolves Yes if canceled. All markets remain open if postponed. Key Quote: 'If the game is canceled entirely, with no make-up game, this market will resolve [No for wins / Yes for draw].'
Kalshi: Three markets bundled as a single event group where each outcome (Sunderland win, Fulham win, draw) resolves Yes if that outcome occurs after 90 minutes plus stoppage time. Cancellation protocol not stated. Key Quote: 'resolves to Yes' for each outcome type, with no explicit cancellation clause.
Our PredictionHero Resolution Divergence Alerts (RDA) are there to help users identify potential differences across platforms. They do not replace or supersede the official rules and description of any prediction market. Users are solely responsible for reviewing and understanding the applicable rules and resolution criteria before placing any trade or bet. If you notice a potential inconsistency, discrepancy, or error in an alert, please report it to our team so we can review and improve the accuracy of our data.
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