This event group covers a women's college basketball game between Albany Great Danes and New Hampshire Wildcats scheduled for February 28, 2026 at 1:00 PM ET. Markets on Polymarket and Kalshi are tracking the outcome of this matchup, with resolution based on the final score including overtime.
Kalshi market contains a logical contradiction where both possible game outcomes (Albany win and New Hampshire win) are stated to resolve to Yes, making the market fundamentally unresolvable. This is a data integrity failure that prevents proper settlement.
Hero Tip:
Do not trade the Kalshi market in its current form. The resolution logic is broken—both outcomes cannot resolve to the same result in a binary market. Wait for Kalshi to correct the market description or contact support for clarification on intended resolution. Polymarket's binary structure is logically sound and should be your reference market.
Critical Divergence Points:
Polymarket: Clean binary outcome: Albany win resolves to 'Albany Great Danes', New Hampshire win resolves to 'New Hampshire Wildcats'. Includes edge case handling for postponement (market remains open) and cancellation (50-50 split). Resolution based on final score including overtime.
Kalshi: Critical logical error: states 'If University at Albany wins...resolves to Yes' AND 'If New Hampshire wins...resolves to Yes'. Both outcomes cannot resolve to the same result in a Yes/No market, making settlement impossible.
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.