This event group covers a single professional AHL (American Hockey League) regular season game between the Colorado Eagles and Calgary Wranglers scheduled for March 27, 2026 at 3:00 PM EDT. The markets resolve based on which team wins the game, including overtime and shootout outcomes.
Kalshi's market structure contains a logical contradiction: both possible game outcomes (either team winning) are mapped to the same resolution value (Yes), rendering the market unresolvable and creating a data integrity failure.
Hero Tip:
Do not trade on Kalshi. The market cannot be settled because both outcomes resolve identically. Use Polymarket exclusively, which correctly maps each outcome to a distinct resolution value and includes proper edge-case handling for postponements and cancellations.
Critical Divergence Points:
Kalshi: Binary market with logical contradiction. Both Calgary Wranglers win and Colorado Eagles win resolve to Yes. This creates an impossible settlement scenario where the market cannot distinguish between outcomes. Key Quote: If Calgary Wranglers wins...resolves to Yes. If Colorado Eagles wins...resolves to Yes.
Polymarket: Categorical market with coherent resolution logic. Colorado Eagles win resolves to Colorado Eagles; Calgary Wranglers win resolves to Calgary Wranglers. Postponements keep market open; cancellations without makeup resolve 50-50. Includes overtime and shootout handling. Key Quote: If Colorado Eagles win, the market will resolve to Colorado Eagles. If Calgary Wranglers win, the market will resolve to Calgary Wranglers.
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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