A college basketball game between Monmouth Hawks and Charleston Cougars scheduled for February 21, 2026 at 4:00 PM ET. Polymarket offers moneyline, spread, and over/under markets with consistent resolution logic. Kalshi offers a binary market that appears to resolve to Yes regardless of outcome.
Kalshi market contains a logical contradiction where both possible game outcomes (Monmouth win and Charleston win) are stated to resolve to Yes, making the market fundamentally unresolvable. Polymarket markets are internally consistent and resolvable.
Hero Tip:
Do not trade the Kalshi market in its current form. The resolution logic is broken and will cause settlement disputes. Polymarket offers clear, mutually exclusive outcomes for moneyline, spread, and total markets. Verify Kalshi market intent with the platform before trading.
Critical Divergence Points:
Polymarket: Moneyline resolves to Hawks or Cougars based on final score. Spreads resolve based on margin (Charleston -4.5 requires 5+ point win; -5.5 requires 6+ point win). Over/unders resolve based on combined score thresholds (145.5, 146.5, 148.5, 149.5, 150.5). All markets resolve 50-50 if canceled with no makeup. Key Quote: "The result will be determined based on the final score including any overtime periods."
Kalshi: Market states both outcomes resolve to Yes: "If Monmouth wins...resolves to Yes. If Charleston wins...resolves to Yes." This creates a logical impossibility with no mutually exclusive outcomes. Key Quote: Both conditional branches map to identical resolution value, violating binary market 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.
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