Club Necaxa and CD Guadalajara will compete in a Liga MX professional soccer match on April 22, 2026. The outcome will be determined by the result after 90 minutes of regular play plus stoppage time, excluding extra time or penalties. This is a standard league fixture where one team will either win, lose, or draw.
Kalshi market structure is logically contradictory: all three possible match outcomes (Necaxa win, Tie, Guadalajara win) resolve to YES, making the market fundamentally unresolvable and inconsistent with Polymarket's mutually exclusive binary structure.
Hero Tip:
Do not trade the Kalshi market. The resolution logic guarantees YES regardless of match outcome, rendering it a guaranteed payout with no predictive value. Polymarket offers the only coherent betting structure where exactly one of three markets resolves YES based on actual result.
Critical Divergence Points:
Polymarket: Three mutually exclusive binary markets: (1) Necaxa win resolves YES only if Necaxa wins, NO otherwise; (2) Draw resolves YES only if match ends in draw, NO otherwise; (3) Guadalajara win resolves YES only if Guadalajara wins, NO otherwise. Exactly one market resolves YES. Quote: 'If Club Necaxa wins, this market will resolve to Yes. Otherwise, this market will resolve to No.'
Kalshi: Single market with three outcome clauses, each resolving to YES: 'If Necaxa wins... then resolves to Yes. If Tie wins... then resolves to Yes. If Guadalajara wins... then resolves to Yes.' This creates logical impossibility where all outcomes trigger YES resolution.
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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