This event group covers a men's college basketball game between St. Bonaventure Bonnies and George Mason Patriots scheduled for February 28, 2026 at 2:00 PM ET. Markets include moneyline (winner), over/under totals at two thresholds (145.5 and 146.5), and a point spread (-4.5 favoring George Mason).
Kalshi's binary market contains a logical contradiction where both possible game outcomes (St. Bonaventure win and George Mason win) are stated to resolve to Yes, making the market fundamentally unresolvable. Polymarket's markets are internally consistent but operate on a different platform with different resolution mechanics.
Hero Tip:
Avoid trading the Kalshi market until the platform corrects the resolution logic. For Polymarket, all four markets (moneyline, two over/unders, and spread) are logically sound and cross-consistent. Use the final official NCAA score including any overtime periods as the settlement source.
Critical Divergence Points:
Polymarket: Four distinct markets with clear binary outcomes. Moneyline: winner takes all. Over/Under 145.5: Over if combined score >= 146, Under if < 146. Over/Under 146.5: Over if combined score >= 147, Under if < 147. Spread: George Mason wins if they win by 5+ points, otherwise St. Bonaventure wins. All use final score including overtime. Postponement keeps markets open; cancellation with no makeup resolves 50-50.
Kalshi: Binary market states: 'If St. Bonaventure wins...resolves to Yes' AND 'If George Mason wins...resolves to Yes.' Both outcomes map to Yes, creating a logical impossibility. No resolution path exists for a No outcome.
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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