This market resolves based on the outcome of a DEL (Deutsche Eishockey Liga) regular season game between Eisbaeren Berlin and Koelner Haie scheduled for April 17, 2026. The winner is determined by the final score including overtime and shootout periods, with the market resolving to the winning team's name. In the event of postponement, the market remains open until completion; if canceled with no makeup game, it resolves 50-50.
Kalshi market contains a logical contradiction: both outcomes (Eisbären Berlin wins OR Kolner Haie wins) are specified to resolve to Yes, making the market fundamentally unresolvable and creating a data integrity failure.
Hero Tip:
Do not trade the Kalshi market. The resolution logic is contradictory—it states both a win by Eisbären Berlin and a win by Kolner Haie resolve to Yes, which is logically impossible. Polymarket's binary structure (one team wins, market resolves to that team's name) is the only coherent framework. Seek clarification from Kalshi before placing any bets.
Critical Divergence Points:
Polymarket: Binary match outcome market. Resolves to 'Eisbaeren Berlin' if Eisbaeren Berlin wins, or 'Koelner Haie' if Koelner Haie wins. Includes postponement (market remains open) and cancellation (50-50 split) clauses. Shootout goals are counted toward final score.
Kalshi: Contradictory resolution logic: states 'If Eisbären Berlin wins...then the market resolves to Yes' AND 'If Kolner Haie wins...then the market resolves to Yes.' Both mutually exclusive outcomes cannot both resolve to Yes in a binary market.
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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