Kent State Golden Flashes vs. Massachusetts Minutemen (W)
Volume:
$3,222
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 Kent State Golden Flashes and Massachusetts Minutemen scheduled for February 25, 2026 at 6:00 PM ET. The markets resolve based on which team wins the game, with provisions for postponement, cancellation, and overtime.
Kalshi market contains a logical contradiction where both possible game outcomes (UMass win and Kent St. win) are mapped to the same resolution state (Yes), leaving no valid path to a No resolution. This makes the market unresolvable and indicates a data integrity failure.
Hero Tip:
Do not trade Kalshi until the resolution logic is corrected. The market as written cannot resolve to No under any game outcome. Contact Kalshi support to confirm whether the intended structure was Yes for UMass / No for Kent St., or if this is a template error. Polymarket's binary structure is clear and resolvable.
Critical Divergence Points:
Polymarket: Binary winner-take-all market with clear resolution paths. Kent State win resolves to Kent State Golden Flashes, UMass win resolves to Massachusetts Minutemen. Cancellation without makeup resolves 50-50. Postponement keeps market open until completion. Resolution based on final score including overtime.
Kalshi: Yes/No market with critical logical flaw. Both UMass win and Kent St. win are mapped to Yes resolution. No resolution path exists for No outcome. This creates an unresolvable market structure.
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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