This event group covers a professional English Premier League match between Crystal Palace FC (home) and Leeds United FC (away) scheduled for March 15, 2026. Markets span multiple prediction platforms with varying outcome specifications: Kalshi focuses on margin-of-victory thresholds, while Polymarket offers binary win/draw/loss outcomes.
Kalshi uses goal-margin settlement thresholds (1.5 and 2.5 goals) while Polymarket uses simple binary match outcomes (win/draw/loss). These represent different market architectures and cannot be unified into a single resolution logic.
Hero Tip:
Do not assume Polymarket and Kalshi markets will move together. A Leeds win by 1 goal resolves YES on Polymarket but NO on all Kalshi Leeds markets. Track margin thresholds separately from outcome markets. Note cancellation asymmetry: Polymarket draw resolves YES if canceled; win markets resolve NO. Kalshi has no stated cancellation protocol.
Critical Divergence Points:
Kalshi: Four margin-based markets. Resolves YES only if specified team wins by specified goal threshold (1.5 or 2.5 goals). Example: Crystal Palace >1.5 goal win resolves YES only if final score shows Palace winning by 2+ goals. No cancellation clause provided.
Polymarket: Three binary outcome markets: draw (YES if 0-0 or any tied result), Leeds win (YES if Leeds score more goals), Crystal Palace win (YES if Palace score more goals). If canceled with no makeup, draw market resolves YES; win markets resolve NO. Primary source is Premier League official statistics within 2 hours of conclusion.
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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