Delaware Fightin' Blue Hens vs. Florida International Golden Panthers (W)
Volume:
$490,540
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 the University of Delaware Fightin' Blue Hens and Florida International University Golden Panthers scheduled for February 19, 2026. The markets resolve based on which team wins the game, with provisions for postponement or cancellation.
Kalshi's resolution criteria contains a logical contradiction: both Delaware winning and Florida International winning are stated to resolve to Yes, which is impossible in a binary market structure. This makes the market fundamentally unresolvable as written.
Hero Tip:
Treat Kalshi's second clause as a likely documentation error. The intended logic is almost certainly Delaware win = Yes, FIU win = No (standard binary). Contact Kalshi support for clarification before trading. Polymarket's winner-take-all structure is logically sound and resolvable.
Critical Divergence Points:
Polymarket: Clear binary winner-take-all resolution. Delaware victory resolves to Delaware team name, FIU victory resolves to FIU team name. Postponement keeps market open; cancellation without makeup resolves 50-50. Includes overtime in final score.
Kalshi: Stated resolution contains logical contradiction: both Delaware win and FIU win are said to resolve to Yes. In a binary Yes/No market, only one outcome can resolve Yes. As written, the market cannot be resolved without violating binary logic.
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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