This event is for the WBB game between Baylor Bears and Duke Blue Devils on March 22 at 4:00 PM 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 to YES for both possible outcomes (Baylor win OR Duke win), creating a logical contradiction that makes the market fundamentally unresolvable. Polymarket correctly resolves to either 'Baylor Bears' or 'Duke Blue Devils' based on the game outcome, with clear tie-breaking and cancellation rules.
Hero Tip:
Do NOT trade on Kalshi — the market rules state it resolves YES if Baylor wins AND YES if Duke wins, meaning every possible outcome triggers YES. This is a data integrity failure. Polymarket is the only tradeable market in this group; it resolves to the actual winner with proper edge-case handling for postponement and cancellation.
Critical Divergence Points:
Kalshi: Outlier: Market contains a logical contradiction. The rules state 'If Baylor wins...then the market resolves to Yes' AND 'If Duke wins...then the market resolves to Yes,' meaning both mutually exclusive outcomes trigger the same YES resolution. This makes the market unresolvable and uninterpretable.
Polymarket: Distinct stance: Market resolves to the actual winner ('Baylor Bears' or 'Duke Blue Devils') based on final score including overtime. Includes proper edge cases: postponement keeps market open until completion, cancellation without makeup resolves 50-50, and result is determined by official final score.
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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