This event group covers the professional La Liga 2 soccer match between UD Almería and FC Andorra scheduled for February 13, 2026. Markets across Kalshi and Polymarket assess the outcome (win/loss/draw) based on the result after 90 minutes of regular play plus stoppage time, excluding extra time and penalties.
Kalshi market contains a logical contradiction where all three possible match outcomes (Andorra win, Tie, Almeria win) are specified to resolve to Yes, making the market fundamentally unresolvable. Polymarket uses standard mutually exclusive binary markets with consistent logic.
Hero Tip:
Do not trade Kalshi markets until the platform clarifies the resolution logic. The current structure is logically impossible. Use Polymarket's three separate binary markets (Andorra win, Almeria win, Draw) as the reliable settlement reference, as they follow standard prediction market conventions with mutually exclusive outcomes.
Critical Divergence Points:
Kalshi: Three binary markets all specified to resolve Yes: 'If Andorra wins...resolves to Yes', 'If Tie wins...resolves to Yes', 'If Almeria wins...resolves to Yes'. This creates a logical impossibility where every possible outcome triggers Yes resolution, making the market unresolvable as drafted.
Polymarket: Three separate binary markets with mutually exclusive outcomes: Andorra win (Yes/No), Almeria win (Yes/No), Draw (Yes/No). Postponement keeps markets open until completion; cancellation resolves per market terms (No for win markets, Yes for draw market). Consistent with standard prediction market logic.
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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