Holy Cross Crusaders vs. Loyola Maryland Greyhounds
Volume:
$1,639,270
Markets
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
A men's college basketball game between Holy Cross Crusaders and Loyola Maryland Greyhounds scheduled for February 15, 2026 at 1:00 PM ET. Markets cover moneyline, multiple spread variations, and over/under total points.
Kalshi moneyline market contains a logical contradiction where both possible game outcomes (Loyola Maryland win and Holy Cross win) are stated to resolve to Yes, making the market fundamentally unresolvable. Polymarket moneyline and all spread/total markets across both platforms use consistent binary resolution logic.
Hero Tip:
Do not trade the Kalshi moneyline market in its current form due to the logical contradiction. All Polymarket markets (moneyline, spreads, over/under) and Kalshi spread/total markets (if any exist) use sound resolution logic. Treat Kalshi moneyline as broken until platform clarification.
Critical Divergence Points:
Kalshi: Moneyline market states both outcomes resolve to Yes: 'If Loyola Maryland wins...resolves to Yes' AND 'If Holy Cross wins...resolves to Yes'. This is logically impossible since only one team can win. The market lacks a coherent resolution path.
Polymarket: Moneyline market correctly resolves to 'Holy Cross Crusaders' if Holy Cross wins, or 'Loyola Maryland Greyhounds' if Loyola Maryland wins. Spread and over/under markets use consistent threshold-based logic with 50-50 cancellation clause. All outcomes are mutually exclusive and resolvable.
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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