Kent State Golden Flashes vs. Miami (OH) RedHawks (W)
Volume:
$31,744
Markets
Outcome
Chance %
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Liquidity
Volume
24h
7d
Open Interest
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Description
This event group covers the outcome of a women's college basketball game between Kent State Golden Flashes and Miami (OH) RedHawks scheduled for March 4, 2026 at 6:00 PM ET. Markets across Kalshi and Polymarket are predicting which team will win this matchup.
Kalshi's market contains a logical contradiction where both possible game outcomes (Kent State win and Miami (OH) win) are mapped to the same resolution (Yes), making the market fundamentally unresolvable and meaningless.
Hero Tip:
This is a critical data integrity failure on Kalshi's platform. Do not trade this market on Kalshi. Use Polymarket exclusively, which has proper binary resolution logic: Kent State win resolves to Kent State Golden Flashes, Miami (OH) win resolves to Miami (OH) RedHawks.
Critical Divergence Points:
Kalshi: Logical contradiction: both Kent St. win and Miami (OH) win resolve to Yes. This makes every possible game outcome resolve identically, rendering the market unresolvable. Key Quote: If Kent St. wins...resolves to Yes. If Miami (OH) wins...resolves to Yes.
Polymarket: Standard binary outcome market with coherent logic: Kent State win resolves to Kent State Golden Flashes, Miami (OH) win resolves to Miami (OH) RedHawks. Includes explicit handling for postponements (market stays open) and cancellations (50-50 split). Key Quote: If Kent State wins, market resolves to Kent State Golden Flashes. If Miami (OH) wins, market resolves to Miami (OH) RedHawks.
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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