This event group covers a men's college basketball game between Murray State Racers and Bradley Braves scheduled for March 1, 2026 at 2:00 PM ET. Markets include moneyline (winner), over/under total points (158.5), and point spread (Bradley -4.5) across Polymarket and Kalshi platforms.
Kalshi's moneyline market contains a logical contradiction: both Murray State win and Bradley win are stated to resolve to Yes, making the market fundamentally unresolvable and creating a data integrity failure. Polymarket markets are logically consistent.
Hero Tip:
Avoid the Kalshi moneyline until the contradiction is resolved. The market cannot function as written. Polymarket's moneyline, over/under, and spread markets are all logically sound and can be safely traded.
Critical Divergence Points:
Polymarket: Three distinct markets with clear binary logic. Moneyline: resolves to winner name. Over/Under 158.5: resolves Over if combined score >= 159, Under if < 159. Spread Bradley -4.5: resolves Bradley if win by 5+, otherwise Murray State. All handle postponement (stay open) and cancellation (50-50 split) consistently. Key Quote: "The result will be determined based on the final score including any overtime periods."
Kalshi: Moneyline market contains logical contradiction. States both outcomes resolve to Yes: "If Murray St. wins...then the market resolves to Yes" AND "If Bradley wins...then the market resolves to Yes." This violates binary resolution logic and makes outcome determination impossible. Key Quote: Both Murray State and Bradley outcomes explicitly map to Yes resolution.
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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