Counter-Strike: ASTRAL vs Heroic (BO3) - DraculaN Playoffs
Volume:
$10,796
Markets
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
This event group covers a Counter-Strike best-of-three match between ASTRAL and Heroic scheduled for February 26, 2026 at 6:00 AM ET in the DraculaN Playoffs. Markets span match winner, individual map winners, total maps played, and map handicaps across Kalshi and Polymarket platforms.
Kalshi's match winner market contains a logical contradiction where both ASTRAL and Heroic winning conditions resolve to Yes, making the market fundamentally unresolvable. Polymarket's equivalent market has clear binary resolution logic.
Hero Tip:
Do not trade Kalshi's match winner market until clarification is issued. Use Polymarket's match winner market and map-specific markets (Map 1 Winner, Map 2 Winner, Games Total O/U 2.5, Map Handicaps) as primary trading instruments. All map-level and aggregate markets show consistent resolution logic across platforms.
Critical Divergence Points:
Kalshi: Match winner market states: If ASTRAL wins, resolve Yes. If Heroic wins, resolve Yes. This creates a logical impossibility where both mutually exclusive outcomes produce identical resolution. No tie/cancellation handling specified.
Polymarket: Match winner market states: Resolve ASTRAL if ASTRAL wins, resolve Heroic if Heroic wins. Includes explicit handling for cancellations, ties, delays beyond 7 days, and forfeits (50-50 resolution). Clear binary structure with defined edge cases.
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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