This event group covers a men's college basketball game between Davidson Wildcats and St. Bonaventure Bonnies scheduled for March 7, 2026 at 12:00 PM ET. Markets include moneyline (winner), point spreads at -3.5 and -4.5, and over/under total points at 141.5. The group tests resolution consistency across multiple market types and platforms.
Kalshi moneyline market contains a logical contradiction where both possible game outcomes (Davidson win or St. Bonaventure win) are stated to resolve to Yes, making the market non-binary and unresolvable as written. Polymarket markets are logically sound and mutually exclusive.
Hero Tip:
Do not trade the Kalshi moneyline in its current form. The resolution logic is broken—both teams winning cannot both resolve to Yes. Polymarket offers clear, resolvable alternatives: use the moneyline (binary outcome), spreads (-3.5 or -4.5), or O/U 141.5. Request clarification from Kalshi before engaging.
Critical Divergence Points:
Polymarket: Five distinct markets with clear binary or threshold-based logic. Moneyline resolves to team name of winner. Spreads resolve based on margin (4+ points for -3.5, 5+ for -4.5). O/U resolves on combined score (142+ = Over). All markets resolve 50-50 if canceled with no makeup. Source: NCAA.org.
Kalshi: Moneyline market states: 'If Davidson wins... resolves to Yes. If St. Bonaventure wins... resolves to Yes.' Both outcomes map to identical resolution (Yes), violating binary market logic. No specification of No outcome or edge case handling.
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.