Oakland Golden Grizzlies vs. Cleveland State Vikings (W)
Volume:
$1,762
Markets
Outcome
Chance %
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Liquidity
Volume
24h
7d
Open Interest
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Description
This event group covers a Women's College Basketball (WBB) matchup between Oakland Golden Grizzlies and Cleveland State Vikings scheduled for February 28, 2026 at 2:00 PM ET. Markets across Polymarket and Kalshi are pricing the outcome of this single game, with resolution tied to the final score including overtime.
Kalshi's resolution logic contains a logical contradiction: both Oakland win and Cleveland State win are stated to resolve to Yes, making the market fundamentally unresolvable. Polymarket uses standard binary winner-take-all logic with clear edge case handling.
Hero Tip:
This is a critical data integrity failure on Kalshi. Do not trade this market on Kalshi until the platform clarifies the resolution logic. The contradiction makes it impossible to determine the correct settlement outcome. Polymarket's logic is sound and resolvable; concentrate trading activity there.
Critical Divergence Points:
Polymarket: Binary winner-take-all structure. Oakland win resolves to Oakland Golden Grizzlies; Cleveland State win resolves to Cleveland State Vikings. Postponement keeps market open until completion; cancellation without makeup resolves 50-50. Resolution based on final score including overtime.
Kalshi: Logical contradiction in resolution rules. Both Oakland win and Cleveland State win are stated to resolve to Yes, creating an impossible settlement scenario where two mutually exclusive outcomes cannot be distinguished.
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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