Robert Morris Colonials vs. Oakland Golden Grizzlies (W)
Volume:
$18,159
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 Robert Morris Colonials and Oakland Golden Grizzlies scheduled for February 21, 2026 at 2:00 PM ET. Markets on both Polymarket and Kalshi are betting on the outcome of this single game, with resolution based on the final score including overtime.
Kalshi market contains a logical contradiction that makes it unresolvable. Both possible game outcomes (Oakland win or Robert Morris win) are mapped to the same resolution state (Yes), leaving no condition for a No resolution. This is a data integrity failure that renders the market uninvestable.
Hero Tip:
Do not trade on Kalshi. The market cannot resolve to No under any realistic game scenario. Polymarket is the only viable venue for this event, offering clear binary resolution with proper edge-case handling for postponements and cancellations.
Critical Divergence Points:
Polymarket: Binary outcome market with two mutually exclusive resolutions: Robert Morris Colonials or Oakland Golden Grizzlies. Includes contingency logic for postponement (market remains open) and cancellation with no makeup (50-50 split). Resolution based on final score including overtime.
Kalshi: Yes/No market that maps both possible game outcomes to Yes: Oakland win resolves Yes, Robert Morris win resolves Yes. No condition is defined for a No resolution, creating a logical impossibility where the market cannot fail to resolve Yes.
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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