Marquette Golden Eagles vs. Villanova Wildcats (W)
Volume:
$65,428
Markets
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
This event group covers the women's college basketball matchup between Marquette Golden Eagles and Villanova Wildcats scheduled for February 22, 2026 at 3:30 PM ET. Markets across platforms are betting on which team will win the game, with resolution based on the final score including overtime.
Kalshi market contains a logical contradiction where both possible outcomes (Villanova win and Marquette win) are mapped to the same resolution state (Yes), making the market fundamentally unresolvable and creating a data integrity failure.
Hero Tip:
Do not trade the Kalshi version of this market. The resolution rules are logically broken and cannot properly settle. Polymarket is the only platform with valid binary resolution logic for this event. Contact Kalshi support to report the contradiction before February 22, 2026.
Critical Divergence Points:
Polymarket: Clear binary winner-take-all logic. Resolves to team name of winner based on final score including overtime. Postponements keep market open; cancellations resolve 50-50. Quote: 'The result will be determined based on the final score including any overtime periods.'
Kalshi: Contradictory resolution logic: states both 'If Villanova wins...resolves to Yes' and 'If Marquette wins...resolves to Yes', mapping both possible outcomes to identical resolution. This creates logical impossibility for settlement.
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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