Oakland Golden Grizzlies vs. Robert Morris Colonials
Volume:
$993,201
Markets
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
A men's college basketball game between Oakland Golden Grizzlies and Robert Morris Colonials scheduled for February 15, 2026 at 2:00 PM ET. Markets cover moneyline (winner), spread (-1.5 Robert Morris), and total points (Over/Under 156.5 and 155.5).
Unified Resolution Criteria (Consistent across platforms)
Both platforms resolve based on identical game outcome (final score including overtime) with consistent edge case handling for postponements and cancellations.
Primary resolution logic:
NCAA.com official final game score
Core resolution logic:
Moneyline: Market resolves to the team with the higher final score
Spread (-1.5 Robert Morris): Resolves to Robert Morris if they win by 2+ points, otherwise Oakland
Over/Under 156.5: Resolves Over if combined score is 157+, Under if 156 or less
Over/Under 155.5: Resolves Over if combined score is 156+, Under if 155 or less
All resolutions include overtime scoring in final totals
Edge cases & Clarifications:
Game Postponement: Markets remain open and unresolved until the game is completed on a future date
Game Cancellation (No Makeup): All markets resolve 50-50 (split pool equally between Yes and No outcomes)
Overtime Periods: All scoring in overtime counts toward final score and total points markets
Timing:
Resolution occurs immediately after final game conclusion on February 15, 2026, or on the rescheduled date if postponed
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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