This event group covers a Counter-Strike best-of-one match between KOLESIE and Young Ninjas in the Conquest of Prague Online Stage Group Stage, scheduled for April 12, 2026 at 1:00 PM EDT. Markets track the match winner, and two map-level statistics (total kills and total rounds in Map 1).
Kalshi's match-winner market contains a logical contradiction: both possible outcomes (KOLESIE win and Young Ninjas win) resolve to Yes, leaving no valid No outcome. This makes the market fundamentally unresolvable as stated. Polymarket's match-winner market is logically sound with mutually exclusive outcomes.
Hero Tip:
Do not trade Kalshi's match-winner market as written. The resolution logic is broken. If forced to settle, map the actual match result to the correct winner (KOLESIE or Young Ninjas) and treat that as the intended outcome. For the map-level markets (Odd/Even Kills and Odd/Even Rounds), both platforms use consistent HLTV-sourced logic with aligned edge cases; those markets are safe.
Critical Divergence Points:
Kalshi:
Match-winner market states: 'If KOLESIE wins... resolves to Yes' AND 'If Young Ninjas wins... resolves to Yes.' This creates a logical impossibility where both outcomes map to the same resolution, leaving the No outcome undefined and the market unresolvable.
Polymarket:
Match-winner market states: 'Resolves to KOLESIE if KOLESIE wins' and 'Resolves to Young Ninjas if Young Ninjas wins.' Outcomes are mutually exclusive and exhaustive, with clear 50-50 fallback for cancellation, delay beyond 7 days, or forfeit.
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.