A men's college basketball game between Utah State Aggies and San Diego State Aztecs scheduled for February 25, 2026 at 11:00 PM ET. Multiple prediction markets track the moneyline winner, point spread, and total points scored in this single sporting event.
Kalshi moneyline market contains a logical contradiction where both possible game outcomes (San Diego St. wins or Utah St. wins) are specified to resolve to Yes, with no defined resolution path for either outcome resolving to No. This makes the market fundamentally unresolvable. Polymarket markets are logically sound and consistent.
Hero Tip:
Disregard the Kalshi moneyline market due to its logical impossibility. Treat Polymarket as the authoritative source for all three market types: moneyline winner, point spread (-1.5 San Diego State), and over/under total (146.5). All Polymarket markets share unified postponement (market stays open) and cancellation (50-50 split) rules.
Critical Divergence Points:
Kalshi:
Moneyline market states both 'If San Diego St. wins... resolves to Yes' and 'If Utah St. wins... resolves to Yes' with no alternative outcome specified. This creates a logical contradiction where no game result can produce a No resolution. No postponement or cancellation guidance provided.
Polymarket:
Moneyline resolves to 'Utah State Aggies' if Utah State wins or 'San Diego State Aztecs' if San Diego State wins, based on final score including overtime. Postponement keeps market open until completion. Cancellation without makeup resolves 50-50. Spread and Over/Under markets follow identical edge-case logic.
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.