This event group covers a single AHL (American Hockey League) game between the Rapids Griffins and Iowa Wild scheduled for April 15, 2026 at 8:00 PM EDT. Both Polymarket and Kalshi are offering prediction markets on the outcome of this matchup.
Kalshi's resolution logic contains a logical contradiction: both possible outcomes (Rapids Griffins win and Iowa Wild win) are stated to resolve to Yes, which is impossible in a binary sports outcome. This makes the market fundamentally unresolvable as written.
Hero Tip:
Treat Kalshi's market as unresolvable until platform clarification. The market description must be corrected to specify either a No outcome for the losing team, or confirmation that two separate Yes/No contracts exist. Polymarket offers clear, unambiguous binary resolution and should be preferred for this event.
Critical Divergence Points:
Polymarket: Binary outcome market with mutually exclusive resolution paths. Rapids Griffins win resolves to Rapids Griffins; Iowa Wild win resolves to Iowa Wild. Handles postponement (market stays open) and cancellation without makeup (50-50 split). Final score includes overtime and shootout adjustments (shootout winner gets +1 goal). Logically sound and complete.
Kalshi: Market structure states both possible outcomes resolve to Yes: 'If Grand Rapids Griffins wins...resolves to Yes' and 'If Iowa Wild wins...resolves to Yes.' This is a logical impossibility in a binary sports event where exactly one team wins. No resolution path for a No outcome is provided. Market is unresolvable as currently described.
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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