This event is for the WBB game between Troy Trojans and Kansas Jayhawks on March 19 at 12:00 AM ET.
If the game is postponed, this market will remain open until the game has been completed.
If the game is canceled entirely, with no make-up game, this market will resolve 50-50.
Kalshi resolves YES for both possible outcomes (Troy wins OR Kansas wins), creating a logical contradiction that makes the market fundamentally unresolvable. Polymarket correctly resolves to a single winner (Troy Trojans or Kansas Jayhawks) based on game outcome, which is the standard sports betting logic.
Hero Tip:
Do NOT trade on Kalshi — the market rules state it resolves YES regardless of whether Troy or Kansas wins, meaning there is no NO outcome possible. This is a data integrity failure. Trade only on Polymarket, which has proper binary resolution (Troy Trojans vs. Kansas Jayhawks).
Critical Divergence Points:
Kalshi: Outlier: Resolves YES if Troy wins AND ALSO YES if Kansas wins, violating binary market logic. Key quote: 'If Troy wins the Troy at Kansas women's college basketball game originally scheduled for Mar 19, 2026, then the market resolves to Yes. If Kansas wins the Troy at Kansas women's college basketball game originally scheduled for Mar 19, 2026, then the market resolves to Yes.'
Polymarket: Aligned with standard sports betting: Resolves to exactly one outcome — either Troy Trojans or Kansas Jayhawks — based on final game score. Key quote: 'If the Troy Trojans win, the market will resolve to Troy Trojans. If the Kansas Jayhawks win, the market will resolve to Kansas Jayhawks.'
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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