This event group covers the women's college basketball game between George Mason Patriots and Duquesne Dukes scheduled for February 28, 2026 at 2:00 PM ET. Both Polymarket and Kalshi are offering prediction markets on the outcome of this single game, with resolution based on the final score including overtime.
Kalshi market contains a logical contradiction where both possible game outcomes are stated to resolve to Yes, making the market fundamentally unresolvable. Polymarket correctly structures this as a binary outcome market.
Hero Tip:
This is a critical data integrity failure on Kalshi's platform. The market cannot function as described because only one team can win. Assume Kalshi intended a standard Yes/No structure (Duquesne Yes / George Mason No, or vice versa) but the description was duplicated in error. Verify with Kalshi support before trading. Polymarket's market is resolvable and should be treated as the reliable source.
Critical Divergence Points:
Polymarket: Binary outcome market with mutually exclusive resolution paths. George Mason win resolves to George Mason Patriots; Duquesne win resolves to Duquesne Dukes. Includes postponement (market stays open) and cancellation (50-50 split) provisions. Resolution based on final score including overtime.
Kalshi: Market description states both outcomes resolve to Yes: 'If Duquesne wins...resolves to Yes' AND 'If George Mason wins...resolves to Yes.' This is logically impossible for a single game outcome and indicates a platform error or template malfunction.
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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