This event group covers a men's college basketball game between Weber State Wildcats and Portland State Vikings scheduled for March 2, 2026 at 10:00 PM ET. Markets span moneyline (winner), spread, and multiple over/under total point thresholds across Kalshi and Polymarket platforms.
Over/Under threshold fragmentation across Polymarket (four distinct thresholds: 142.5, 143.5, 144.5, 145.5) creates settlement value mismatch. Kalshi moneyline lacks explicit cancellation and postponement protocol compared to Polymarket's detailed edge-case handling.
Hero Tip:
Traders should map their O/U exposure to the specific threshold. A combined score of 144 points triggers different resolutions across Polymarket's four markets. For moneyline exposure, Polymarket's explicit 50-50 cancellation rule provides clarity that Kalshi does not offer.
Critical Divergence Points:
Kalshi: Moneyline only: resolves Yes if Weber St. wins OR if Portland St. wins the game originally scheduled for Mar 2, 2026. No explicit handling of postponement, overtime, or cancellation. Quote: 'If Weber St. wins the Weber St. at Portland St. men's college basketball game originally scheduled for Mar 2, 2026, then the market resolves to Yes.'
Polymarket: Comprehensive: moneyline resolves to winning team name; spread resolves based on 5+ point margin; four O/U markets at 142.5, 143.5, 144.5, 145.5 thresholds. All include overtime in final score. Postponement keeps markets open; cancellation with no makeup resolves 50-50. Quote: 'If the game is canceled entirely, with no make-up game, this market will resolve 50-50.'
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.
Follow the signals, not the noise
Get insights on market conviction, notable shifts, and what the data is quietly signaling.