This event group covers a Counter-Strike BO1 match between B8 and maquinas in the Parken Challenger Championship Group A, scheduled for March 31, 2026 at 6:00 AM ET. Markets track the match winner, and two derivative markets on Map 1 statistics (odd/even kills and odd/even total rounds).
Kalshi match winner markets lack explicit edge-case definitions (cancellations, forfeits, delays, no-play scenarios) that Polymarket comprehensively addresses. Scope and source transparency differ materially.
Hero Tip:
Polymarket's 50-50 resolution for cancellations, forfeits, and delays >7 days is explicit and trader-friendly. Kalshi's silence on these scenarios creates settlement risk. If you hold both platforms, monitor for match status changes closely. Polymarket will resolve predictably; Kalshi may default to contract rules or require manual adjudication.
Critical Divergence Points:
Polymarket:
Match winner resolves to team name if they win; resolves to 50-50 if canceled, tied, delayed >7 days without winner, or ends in forfeit/disqualification before start. Forfeits mid-match resolve to the winning team. Primary source: HLTV.org with 2-hour fallback to credible consensus. Map 1 stats (kills/rounds odd-even) also resolve to 50-50 if map not played or series already clinched.
Kalshi:
Match winner resolves to Yes if either B8 or maquinas wins the match. No explicit handling of cancellations, forfeits, delays, or no-play scenarios. No stated resolution source or fallback protocol. Resolution logic is binary (Yes/No) with no 50-50 provision.
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.