This event group covers a Counter-Strike best-of-three match between Vitality and G2 at PGL Cluj-Napoca Group Stage scheduled for February 14, 2026 at 9:00 AM ET. Markets span individual map winners, overall match outcome, map handicap, and series length, with resolution sourced from HLTV.org.
Kalshi's binary Yes/No structure lacks explicit edge-case handling for forfeits, walkovers, and cancellations, while Polymarket provides detailed 50-50 resolution rules for these scenarios. This creates potential divergence in settlement outcomes.
Hero Tip:
Monitor match status closely. If a forfeit, walkover, or cancellation occurs, Polymarket will resolve 50-50, but Kalshi's resolution is ambiguous. Request clarification from Kalshi on whether a forfeit counts as a team 'winning' (Yes) or triggers a different outcome. Avoid arbitrage until Kalshi's edge-case rules are confirmed.
Critical Divergence Points:
Kalshi:
Binary Yes/No market that resolves Yes if either G2 or Vitality wins the match. No explicit rules provided for forfeits, walkovers, cancellations, or delays. Implicit assumption: any match outcome (including forfeit) may resolve Yes.
Polymarket:
Resolves to Vitality or G2 if match winner is determined. Explicitly resolves to 50-50 if match is canceled, delayed beyond 7 days without play, ends in tie, or if either team forfeits/is disqualified/walks over before start. Key Quote: 'If the match ends in a forfeit, disqualification, or walkover (team withdraws before the start and the other wins automatically), this market will resolve to 50-50.'
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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