This event group covers a professional Czech Extraliga hockey match between HC Energie Karlovy Vary and HC Ocelari Trinec scheduled for April 8, 2026 at 12:30 PM EDT. Markets resolve based on the final game outcome, with provisions for postponements, cancellations, and shootout handling.
Kalshi market contains a logical contradiction: both possible game outcomes (Karlovy Vary win and Trinec win) are mapped to the same resolution state (Yes), making the market unresolvable. Polymarket uses a proper binary structure with mutually exclusive outcomes.
Hero Tip:
Kalshi's market is broken and should not be traded. The platform must clarify whether the market should resolve Yes only for Karlovy Vary, only for Trinec, or use a different structure entirely. Polymarket's market is logically sound and can be traded with confidence.
Critical Divergence Points:
Polymarket: Binary outcome market with mutually exclusive resolution paths. Resolves to 'Karlovy Vary' if Karlovy Vary wins; resolves to 'Trinec' if Trinec wins. Postponements keep market open; cancellations resolve 50-50. Shootout goals are counted in final score. Quote: 'If Karlovy Vary win, the market will resolve to Karlovy Vary. If Trinec win, the market will resolve to Trinec.'
Kalshi: Logically contradictory structure. Market states it resolves to Yes if Karlovy Vary wins AND also resolves to Yes if Trinec wins, creating an impossible resolution scenario. Quote: 'If HC Energie Karlovy Vary wins...then the market resolves to Yes. If HC Ocelari Trinec 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.
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