This event group covers a single AHL (American Hockey League) matchup between the San Diego Gulls and Texas Stars scheduled for February 27, 2026 at 8:00 PM EST. Both Polymarket and Kalshi are offering prediction markets on the outcome of this game, with resolution based on the final score including overtime and shootouts.
Kalshi's resolution logic contains a logical contradiction: both possible game outcomes (San Diego Gulls win OR Texas Stars win) are mapped to the same resolution state (Yes), making the market fundamentally unresolvable. Polymarket uses standard binary winner-takes-all logic with clear edge-case handling.
Hero Tip:
Polymarket's market is tradeable and clear. Kalshi's market cannot resolve as currently written because exactly one team will win, but both winning conditions claim Yes resolution. Request immediate clarification from Kalshi on whether this is a Yes/No on San Diego Gulls specifically, or if the market description contains an error. Avoid trading Kalshi until resolved.
Critical Divergence Points:
Polymarket:
Binary winner-takes-all. San Diego Gulls win resolves to San Diego Gulls; Texas Stars win resolves to Texas Stars. Postponements keep market open; full cancellations resolve 50-50. Final score includes overtime and shootouts (shootout adds one goal to winner).
Kalshi:
Contradictory dual-Yes mapping. States 'If San Diego Gulls wins...resolves to Yes' AND 'If Texas Stars wins...resolves to Yes.' Since only one team can win, both conditions cannot both occur, creating logical impossibility. No edge-case guidance provided.
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.