This event group covers a professional Czech Extraliga (ELH) ice hockey match between HC Sparta Praha and HC Pardubice scheduled for April 8, 2026 at 11:45 AM EDT. Both Kalshi and Polymarket are offering prediction markets on the outcome of this single game, with resolution determined by the final score including overtime and shootouts.
Kalshi market contains a logical contradiction where both possible game outcomes (Pardubice win and Sparta Praha win) are mapped to the same resolution (Yes), making the market fundamentally unresolvable. Polymarket provides coherent categorical resolution with proper edge case handling.
Hero Tip:
Treat Polymarket as the reliable resolution source. Kalshi's market appears to have a structural error in its resolution logic that must be corrected before trading. Request clarification from Kalshi before committing capital.
Critical Divergence Points:
Kalshi:
Binary Yes/No market with contradictory logic mapping. Both outcomes (HC Pardubice wins OR HC Sparta Praha wins) resolve to Yes, leaving no path to No resolution. Quote: 'If HC Pardubice wins...resolves to Yes' AND 'If HC Sparta Praha wins...resolves to Yes'.
Polymarket:
Categorical winner-based resolution with mutually exclusive outcomes. Sparta Prague win resolves to 'Sparta Prague', Dynamo Pardubice win resolves to 'Dynamo Pardubice'. Includes explicit edge case handling: postponements keep market open, full cancellations resolve 50-50. Quote: 'If Sparta Prague win, the market will resolve to Sparta Prague. If Dynamo Pardubice win, the market will resolve to Dynamo Pardubice.'
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.