This event group covers a men's college basketball game between San Diego Toreros and Portland Pilots scheduled for February 28, 2026 at 4:00 PM ET. Markets include moneyline (winner), multiple over/under totals (146.5, 147.5, 148.5, 149.5), and point spreads (-3.5, -4.5 for Portland).
Kalshi moneyline market has contradictory resolution logic that resolves to Yes for both possible outcomes (Portland win OR San Diego win), making it logically unresolvable. Polymarket markets are internally consistent but diverge from Kalshi on the fundamental moneyline structure.
Hero Tip:
Do not trade the Kalshi moneyline market in its current form - it contains a data integrity failure. All Polymarket markets (moneyline, spreads, over/unders) use consistent logic based on final score including overtime. Use Polymarket as the authoritative source for this event group.
Critical Divergence Points:
Polymarket: Binary moneyline resolves to winner (San Diego Toreros or Portland Pilots). Spreads resolve based on margin of victory (Portland -3.5 requires 4+ point win, Portland -4.5 requires 5+ point win). Over/unders resolve based on combined total (thresholds: 146.5, 147.5, 148.5, 149.5). All markets remain open if postponed, resolve 50-50 if canceled without makeup. Final score includes overtime.
Kalshi: Moneyline market states: 'If Portland wins...resolves to Yes. If San Diego wins...resolves to Yes.' This creates logical impossibility - market resolves Yes regardless of outcome. No resolution criteria provided for postponement or cancellation.
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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