Club Universitario de Deportes will face CD Garcilaso in a Peru Liga 1 match scheduled for April 22, 2026. This event group captures three mutually exclusive outcomes: a Universitario win, a Garcilaso win, or a draw. All markets resolve based on the result after 90 minutes of regular play plus stoppage time, excluding extra time or penalties.
Unified Resolution Criteria (Consistent across platforms)
Both Polymarket and Kalshi resolve based on the official match outcome within 90 minutes plus stoppage time on April 22, 2026, with identical treatment of postponements and cancellations across all three possible outcomes (Universitario win, Garcilaso win, draw).
Primary resolution logic:
Official statistics from Liga 1 Peru (the governing body/event organizer), with fallback to credible reporting consensus if official statistics are not published within 2 hours of match conclusion.
Core resolution logic:
Market resolves based on the final score after 90 minutes of regular play plus stoppage time only (no extra time or penalties).
Exactly one of the three mutually exclusive outcomes will resolve YES: Universitario win, Garcilaso win, or draw.
If the match is postponed, all markets remain open until the match is completed.
If the match is canceled entirely with no make-up game, Universitario win and Garcilaso win markets resolve NO, and the draw market resolves YES.
Timing:
Resolution occurs upon official publication of final match statistics by Liga 1 Peru within 2 hours of match conclusion, or upon consensus of credible reporting if official statistics are delayed.
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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