This event group covers a professional Argentina Primera Division soccer match between CA Tucumán and CA Aldosivi scheduled for March 11, 2026. Markets track the outcome within 90 minutes of regular play plus stoppage time across two platforms (Polymarket and Kalshi), with separate binary contracts for each team's win and draw outcomes.
Cancellation scenario handling differs between platforms. Polymarket's draw market resolves YES on cancellation; Kalshi's three-outcome structure does not explicitly address cancellation and likely defaults all outcomes to NO, creating a payout mismatch.
Hero Tip:
Avoid holding both Polymarket draw and Kalshi tie contracts simultaneously if cancellation risk is material. Confirm Kalshi's cancellation protocol directly before the event date. For normal match completion (win/loss/draw), both platforms are aligned.
Critical Divergence Points:
Polymarket: Three separate binary markets: Tucuman Win (YES if Tucuman wins, NO otherwise), Aldosivi Win (YES if Aldosivi wins, NO otherwise), Draw (YES if draw, NO otherwise). Cancellation with no make-up resolves Tucuman and Aldosivi markets to NO, but Draw market resolves to YES. Quote: 'If the game is canceled entirely, with no make-up game, this market will resolve Yes.'
Kalshi: Three mutually exclusive outcome markets: Tucuman Win, Tie, Aldosivi Win. Each resolves YES only if that outcome occurs after 90 minutes plus stoppage time. No explicit cancellation clause provided; standard resolution would resolve all three to NO on cancellation, contradicting Polymarket's draw-to-YES rule.
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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