This event group covers the AS Monaco FC vs. FC Nantes Ligue 1 soccer match scheduled for February 13, 2026. Three prediction markets track the outcome: whether Nantes wins, whether Monaco 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's draw market and win markets have contradictory cancellation resolution rules. If the game is canceled with no make-up, the draw market resolves Yes while win markets resolve No. Kalshi does not address cancellation scenarios.
Hero Tip:
If the match is canceled or postponed indefinitely, Polymarket traders face a logical contradiction: the draw market Yes and both win market Nos would all resolve simultaneously, violating mutual exclusivity. Kalshi markets lack explicit guidance. Confirm cancellation protocols with each platform and consider hedging across platforms if cancellation risk is material.
Critical Divergence Points:
Polymarket: Three separate binary markets: Nantes win (Yes/No), Monaco win (Yes/No), and Draw (Yes/No). Win markets resolve No on cancellation; draw market resolves Yes on cancellation. Quote: 'If the game is canceled entirely, with no make-up game, this market will resolve to Yes' (draw) vs. 'this market will resolve to No' (win markets).
Kalshi: Three categorical outcomes presented as separate Yes resolutions: Tie wins, Monaco wins, or Nantes wins. No explicit cancellation clause provided. Assumes game completion within 90 minutes plus stoppage time.
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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