This event group covers a Swiss National League (SNHL) ice hockey match between Rapperswil-Jona Lakers and Geneve-Servette scheduled for February 24, 2026. Markets on Polymarket and Kalshi both predict the winner of this professional hockey game, with resolution based on the final score including overtime and shootouts.
Kalshi market contains a logical contradiction: both possible game outcomes (Lakers win and Servette win) are stated to resolve to Yes, which is impossible in a binary Yes/No market. This makes the Kalshi market fundamentally unresolvable as written.
Hero Tip:
Avoid trading the Kalshi market until the resolution logic is clarified by Kalshi support. The contradiction suggests either a drafting error (second condition should resolve to No) or the market is actually a Yes/No on Lakers only. Polymarket's winner-take-all structure is logically sound and should be your primary reference.
Critical Divergence Points:
Polymarket: Winner-take-all binary with explicit edge-case handling. Resolves to team name of winner. Postponements keep market open; cancellations resolve 50-50. Key quote: 'If Rapperswil-Jona Lakers win, the market will resolve to Rapperswil-Jona Lakers. If Geneve-Servette win, the market will resolve to Geneve-Servette.'
Kalshi: Logically contradictory Yes/No structure. Both Lakers win and Servette win are stated to resolve to Yes. Key quote: 'If SC Rapperswil-Jona Lakers wins...then the market resolves to Yes. If Genève Servette wins...then the market resolves to Yes.' This creates an unresolvable scenario.
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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