This event group covers three linked prediction markets on the professional Liga Portugal soccer match between Casa Pia AC and FC Arouca scheduled for February 14, 2026. Markets track whether Casa Pia wins, Arouca wins, or the match ends in a draw, all measured within 90 minutes of regular play plus stoppage time.
Kalshi and Polymarket handle match cancellation with no makeup game differently. Polymarket explicitly resolves win markets to No and draw markets to Yes on cancellation; Kalshi provides no cancellation clause and implies all outcomes resolve Yes if the match is played.
Hero Tip:
Monitor cancellation risk closely. On Polymarket, the draw market is protected (resolves Yes on cancellation), but win markets face downside (resolve No). On Kalshi, cancellation handling is unclear—seek platform clarification before trading. Arbitrage opportunity exists if cancellation probability is priced differently across platforms.
Critical Divergence Points:
Polymarket: Three separate binary markets: Casa Pia win (Yes/No), Draw (Yes/No), Arouca win (Yes/No). Win markets resolve No on cancellation with no makeup; draw market resolves Yes on cancellation. Postponement keeps markets open. Key Quote: 'If the game is canceled entirely, with no make-up game, this market will resolve No' (wins) and 'this market will resolve Yes' (draw).
Kalshi: Three outcomes presented as a single event group: all resolve to Yes if the match is played and the respective outcome occurs. No explicit cancellation or postponement clause provided. Key Quote: 'resolves to Yes' for each outcome type.
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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