Bethune-Cookman Wildcats vs. Florida A&M Rattlers (W)
Volume:
$351,960
Markets
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
This event group covers a women's college basketball game between Bethune-Cookman Wildcats and Florida A&M Rattlers scheduled for March 5, 2026 at 5:00 PM ET. Markets on both Polymarket and Kalshi are betting on the winner of this matchup, with resolution based on the final score including overtime.
Kalshi market contains a logical contradiction: both possible game outcomes (Florida A&M win and Bethune-Cookman win) are specified to resolve to Yes, leaving no valid No resolution path. This makes the market fundamentally unresolvable as a binary contract.
Hero Tip:
Trade only on Polymarket for this event. Polymarket uses standard winner-take-all binary logic with clear resolution paths for both outcomes plus edge cases. Kalshi's market structure is broken and should not be relied upon until the platform issues a corrected specification.
Critical Divergence Points:
Polymarket: Standard binary winner-take-all structure. Bethune-Cookman win resolves to Bethune-Cookman Wildcats; Florida A&M win resolves to Florida A&M Rattlers. Postponement keeps market open; cancellation without makeup resolves 50-50. Resolution based on final score including overtime.
Kalshi: Logically incoherent specification. Both outcomes (Florida A&M win and Bethune-Cookman win) are mapped to Yes resolution, with no specified No outcome. This violates binary market structure and creates an unresolvable state.
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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