This event group covers the women's college basketball game between Indiana State Sycamores and Belmont Bruins scheduled for February 28, 2026 at 5:00 PM ET. Markets on both Polymarket and Kalshi are betting on the winner of this single game.
Kalshi market contains a logical contradiction where both possible game outcomes (Belmont win and Indiana State win) are stated to resolve to the same result (Yes), making the market fundamentally unresolvable and creating data integrity failure.
Hero Tip:
Treat Polymarket as the authoritative source for this event. Kalshi's market structure is broken and should not be used for settlement until corrected by the platform. The contradiction suggests a copy-paste error or template malfunction on Kalshi's side.
Critical Divergence Points:
Polymarket: Clean binary logic: Indiana State win resolves to 'Indiana State Sycamores', Belmont win resolves to 'Belmont Bruins'. Postponement extends market; cancellation without makeup splits 50-50. Key Quote: 'If the Indiana State Sycamores win, the market will resolve to Indiana State Sycamores. If the Belmont Bruins win, the market will resolve to Belmont Bruins.'
Kalshi: Defective binary structure: Both outcomes map to Yes. 'If Belmont wins...resolves to Yes' and 'If Indiana St. wins...resolves to Yes'. This is logically impossible for a binary market. Key Quote: 'If Belmont wins...then the market resolves to Yes. If Indiana St. wins...then the market resolves to Yes.'
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.
Follow the signals, not the noise
Get insights on market conviction, notable shifts, and what the data is quietly signaling.