A men's college basketball game between California Baptist Lancers and Utah Tech Trailblazers scheduled for February 14, 2026 at 9:00 PM ET at Utah Tech. Markets cover moneyline (winner), point spread (-2.5 favoring California Baptist), and multiple over/under total points variants (140.5, 141.5, 142.5, 143.5).
Kalshi's moneyline market contains a logical contradiction where both possible game outcomes (Utah Tech win and California Baptist win) are mapped to the same resolution (Yes), making the market unresolvable. Polymarket and all spread/total markets use standard binary or outcome-based resolution.
Hero Tip:
Do not trade the Kalshi moneyline market - it cannot be resolved. Trade Polymarket moneyline instead. Spread and total markets are safe across both platforms with unified logic: resolve based on final score including overtime, remain open if postponed, split 50-50 if canceled with no makeup.
Critical Divergence Points:
Kalshi:
Moneyline market maps both Utah Tech win and California Baptist win to Yes resolution. This creates a logical impossibility - the market cannot distinguish between outcomes. Quote: 'If Utah Tech wins...resolves to Yes. If California Baptist wins...resolves to Yes.'
Polymarket:
Moneyline resolves to team name (California Baptist Lancers or Utah Tech Trailblazers). Spread and totals use binary outcomes (Over/Under or team name). All markets remain open if postponed and split 50-50 if canceled with no makeup. Quote: 'If the California Baptist Lancers win, the market will resolve to California Baptist Lancers.'
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.