This event group covers a single AHL (American Hockey League) regular season game between the Manitoba Moose and Grand Rapids Griffins scheduled for February 25, 2026 at 7:00 PM EST. Both Polymarket and Kalshi have created prediction markets on the outcome of this game, with resolution tied to the final score including overtime and shootout results.
Kalshi market contains a logical contradiction where both possible game outcomes (Manitoba Moose win and Grand Rapids Griffins win) are stated to resolve to Yes, making the market fundamentally unresolvable. Polymarket provides coherent, mutually exclusive resolution logic.
Hero Tip:
Do not trade on Kalshi until the platform corrects the resolution criteria. The Polymarket market is the only one with valid, resolvable logic. If you hold Kalshi positions, request clarification or consider exiting.
Critical Divergence Points:
Polymarket:
Clear binary outcome structure with three distinct resolution paths: Manitoba Moose win resolves to Manitoba Moose, Grand Rapids Griffins win resolves to Grand Rapids Griffins, and cancellation without makeup resolves 50-50. Key Quote: 'If Manitoba Moose win, the market will resolve to Manitoba Moose. If Grand Rapids Griffins win, the market will resolve to Grand Rapids Griffins.'
Kalshi:
Logically contradictory binary market where both possible outcomes map to Yes. Key Quote: 'If Manitoba Moose wins...then the market resolves to Yes' AND 'If Grand Rapids Griffins wins...then the market resolves to Yes.' This creates an impossible resolution state.
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.