This event group covers a Swiss National League (SNHL) ice hockey match between HC Ajoie and Genève-Servette scheduled for March 7, 2026. Markets on both Polymarket and Kalshi are betting on the outcome of this professional hockey game, with resolution based on the final score including overtime and shootouts.
Kalshi's resolution criteria contains a logical contradiction: both possible game outcomes (Genève Servette win and HC Ajoie win) are mapped to the same resolution (Yes), leaving no valid path to a No resolution. This makes the market fundamentally unresolvable as written.
Hero Tip:
Do not trade on Kalshi until the platform clarifies the intended resolution logic. The current wording suggests a data entry error. Polymarket's market is logically sound and safe to trade. Request explicit confirmation from Kalshi on whether this should be a binary win/loss market or a Yes/No on a specific team.
Critical Divergence Points:
Polymarket: Binary outcome market with clear logic: Ajoie win resolves to Ajoie, Geneve-Servette win resolves to Geneve-Servette. Includes well-defined edge cases for postponement (market stays open) and cancellation without makeup (50-50 split). Key Quote: 'If the game is canceled entirely, with no make-up game, this market will resolve 50-50.'
Kalshi: Logically contradictory resolution criteria. Both 'Genève Servette wins' and 'HC Ajoie wins' are stated to resolve to Yes. No condition is specified for a No resolution. Key Quote: 'If Genève Servette wins... resolves to Yes. If HC Ajoie wins... 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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