This event group covers a professional Argentina Primera Division soccer match between CSyD Defensa y Justicia and CA Vélez Sarsfield scheduled for February 13, 2026. Markets on Kalshi and Polymarket assess the outcome (win/loss/draw) based on the result after 90 minutes of regular play plus stoppage time, excluding extra time or penalties.
Cancellation and no-makeup-game scenarios are handled differently across platforms. Kalshi's structure treats all outcomes uniformly as Yes-resolving events, while Polymarket differentiates: draw markets resolve Yes on cancellation without makeup, but win/loss markets resolve No.
Hero Tip:
Monitor AFA official announcements for postponement or cancellation. If a game is canceled without a makeup, Polymarket draw bettors win while win bettors lose, but Kalshi's unified Yes-resolution creates ambiguity. Clarify with platform support which outcome Kalshi will actually settle if no makeup occurs.
Critical Divergence Points:
Kalshi: All three outcome markets (Velez win, Defensa win, Tie) are structured to resolve Yes. The platform does not explicitly address cancellation or postponement scenarios. Quote: 'If Tie wins...then the market resolves to Yes' (and similarly for both win outcomes).
Polymarket: Three separate markets with asymmetric cancellation logic: Defensa win and Velez win markets resolve No if canceled with no makeup; draw market resolves Yes if canceled with no makeup. Quote: 'If the game is canceled entirely, with no make-up game, this market will resolve Yes' (draw) vs 'this market will resolve No' (win markets).
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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