This event group covers a college basketball game between the Maine Black Bears and New Hampshire Wildcats scheduled for February 21, 2026 at 4:00 PM ET. Markets include moneyline (winner), spread (-3.5 NH), and multiple over/under totals (134.5, 135.5, 136.5, 137.5). The group tests resolution consistency across moneyline, spread, and total markets on two platforms.
Kalshi moneyline market contains a logical contradiction: both Maine win and New Hampshire win are stated to resolve to Yes, making the market unresolvable as a binary contract. Polymarket markets are logically consistent across all three market types (moneyline, spread, totals).
Hero Tip:
Avoid trading the Kalshi moneyline until the platform clarifies the intended resolution logic. The market appears to have a documentation error. Polymarket offers consistent, resolvable markets for this matchup across all three categories.
Critical Divergence Points:
Polymarket: Moneyline resolves to winner name (Maine Black Bears or New Hampshire Wildcats). Spread (-3.5 NH) resolves to New Hampshire if they win by 4+ points, otherwise Maine. Totals (134.5, 135.5, 136.5, 137.5) resolve Over/Under based on combined score thresholds. All markets: remain open if postponed; resolve 50-50 if canceled with no makeup. Source: NCAA.org. Final score includes overtime.
Kalshi: Moneyline states: 'If Maine wins...resolves to Yes' AND 'If New Hampshire wins...resolves to Yes' — both outcomes map to Yes, creating a logical impossibility. No edge case or cancellation language provided. This contradicts standard binary market design.
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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