This event group covers a men's college basketball game between the South Florida Bulls and Rice Owls scheduled for February 25, 2026 at 8:00 PM ET. Markets include moneyline (winner), point spread (-11.5 for South Florida), and total points (O/U 157.5).
Kalshi moneyline market contains a logical contradiction where both possible game outcomes (South Florida win or Rice win) are mapped to the same resolution value (Yes), making the market fundamentally unresolvable. Polymarket moneyline and all derivative markets (spread, total) maintain consistent binary logic.
Hero Tip:
Do not trade the Kalshi moneyline market in its current form. The market logic is broken and will create settlement disputes. Trade only Polymarket moneyline, spread, and total markets, which have internally consistent resolution criteria. Verify with Kalshi support that the moneyline market terms will be corrected before settlement.
Critical Divergence Points:
Kalshi: Moneyline market resolves to Yes for both South Florida win AND Rice win, creating logical impossibility. Exact quote: 'If South Florida wins...then the market resolves to Yes' and 'If Rice wins...then the market resolves to Yes'. This is a data integrity failure.
Polymarket: Moneyline market correctly resolves to 'South Florida Bulls' if South Florida wins or 'Rice Owls' if Rice wins. Spread market resolves to 'South Florida Bulls' if they win by 12+ points, otherwise 'Rice Owls'. Total market resolves to 'Over' if combined score is 158+, otherwise 'Under'. All three markets use consistent binary logic with clear thresholds.
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.