This event group covers a Counter-Strike: Global Offensive best-of-one match between ESC Gaming and Qual4 in the Conquest of Prague Online Stage Group Stage, scheduled for April 13, 2026 at 11:00 AM ET. The group includes three markets: match winner, Map 1 odd/even total rounds, and Map 1 odd/even total kills.
Kalshi's market definition is logically contradictory and unresolvable as a binary. It states the market resolves Yes if either team wins, which covers all normal match outcomes and leaves no path to No resolution except cancellation/forfeit—making it a tautology rather than a true binary prediction market.
Hero Tip:
Kalshi's market is fundamentally broken and should not be traded. Polymarket offers three separate, well-defined markets with proper edge-case handling. Use Polymarket's match winner market for binary exposure to the match outcome.
Critical Divergence Points:
Polymarket:
Three distinct markets with granular resolution logic. Match winner resolves to ESC Gaming, Qual4, or 50-50 (on cancel, tie, delay >7 days, or forfeit/walkover). Map 1 rounds and kills markets resolve to Odd, Even, or 50-50 based on game statistics or non-play scenarios. Primary source: HLTV.org with 2-hour fallback to credible reporting.
Kalshi:
Single binary market: 'If Qual4 wins...then Yes. If ESC Gaming wins...then Yes.' No resolution path to No is defined for normal match outcomes. This creates a logical tautology where the market always resolves Yes unless the match is canceled or forfeited, eliminating meaningful price discovery.
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.