A professional soccer match between Turkish club Samsunspor and Spanish club Rayo Vallecano de Madrid scheduled for March 12, 2026, with markets predicting the match outcome (win/draw/loss) based on 90 minutes of regular play plus stoppage time. Multiple prediction platforms have created overlapping markets on this single sporting event.
Polymarket's draw market contains a cancellation clause that resolves to Yes if the match is canceled, while Kalshi provides no explicit cancellation guidance. This creates asymmetric risk for traders betting on draw outcomes across platforms.
Hero Tip:
If you are long the draw on Polymarket and short on Kalshi, a cancellation event would create a profitable arbitrage but also platform risk. Verify Kalshi's cancellation policy directly. For most scenarios (match plays to completion), all platforms resolve consistently based on 90-minute result.
Critical Divergence Points:
Polymarket: Three separate binary markets: Samsunspor Win (resolves No on cancellation), Draw (resolves Yes on cancellation), Rayo Win (resolves No on cancellation). Draw market has unique cancellation logic: 'If the game is canceled entirely, with no make-up game, this market will resolve Yes.' Resolution source is UEFA official statistics or credible consensus within 2 hours of match end.
Kalshi: Single omnibus market covering all three outcomes (Tie, Samsunspor, Vallecano) with no explicit cancellation clause provided. Market resolves Yes for whichever outcome occurs after 90 minutes plus stoppage time. No guidance on postponement or cancellation scenarios.
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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