A men's college basketball game between the Omaha Mavericks and South Dakota Coyotes scheduled for March 6, 2026 at 7:00 PM ET. Markets cover moneyline outcomes, point spreads at -2.5 and -3.5, and total points over/under at 149.5, 150.5, and 151.5.
Kalshi moneyline market contains a logical contradiction: both Omaha win and South Dakota win resolve to Yes, leaving no valid No outcome. This is a data integrity failure that makes the market fundamentally unresolvable.
Hero Tip:
Do not trade the Kalshi moneyline. Use Polymarket moneyline instead, which correctly resolves to either Omaha Mavericks or South Dakota Coyotes. All spread and total markets across both platforms are logically consistent and resolvable.
Critical Divergence Points:
Kalshi: Moneyline market has contradictory resolution logic: If Omaha wins = Yes, If South Dakota wins = Yes. No valid No outcome exists. Quote: 'If Omaha wins the Omaha at South Dakota men's college basketball game originally scheduled for Mar 6, 2026, then the market resolves to Yes. If South Dakota wins the Omaha at South Dakota men's college basketball game originally scheduled for Mar 6, 2026, then the market resolves to Yes.'
Polymarket: Moneyline market has correct binary resolution: If Omaha wins = Omaha Mavericks, If South Dakota wins = South Dakota Coyotes. Spread and total markets also follow standard resolution logic with 50-50 cancellation clause. Quote: 'If the Omaha Mavericks win, the market will resolve to Omaha Mavericks. If the South Dakota Coyotes win, the market will resolve to South Dakota Coyotes.'
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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