This event group covers a professional Ligue 1 soccer match between Olympique Lyonnais and Paris FC scheduled for March 8, 2026. Markets are offered across Polymarket and Kalshi, with separate binary outcomes for Lyon win, Paris win, and draw results.
Polymarket's draw market contains a cancellation clause that resolves YES if the game is canceled with no makeup, while Kalshi's three-outcome market structure does not explicitly address cancellation scenarios, creating potential misalignment in edge-case settlement.
Hero Tip:
Traders holding positions across both platforms should request explicit cancellation guidance from Kalshi before March 8, 2026. If a cancellation occurs, Polymarket's draw market will clearly resolve YES, but Kalshi's resolution path is undefined. Consider hedging or clarifying with platform support to avoid settlement ambiguity.
Critical Divergence Points:
Polymarket:
Three separate binary markets: Lyon win (resolves YES if Lyon wins in 90+stoppage), Draw (resolves YES if draw OR if game canceled with no makeup), Paris win (resolves YES if Paris wins in 90+stoppage). Primary source is official Ligue 1 statistics within 2 hours, fallback to credible reporting consensus. Quote: 'If the game is canceled entirely, with no make-up game, this market will resolve Yes.'
Kalshi:
Single three-outcome market: each outcome (Paris wins, Lyon wins, Tie) resolves YES based on the match result after 90 minutes plus stoppage time. No explicit cancellation clause stated. Quote: 'If Paris wins... If Lyon wins... If Tie wins... then the market resolves to Yes.'
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.