This event group covers a League of Legends Best-of-One match between Solary and Ici Japon Corp. Esport in the LFL Regular Season, scheduled for April 22, 2026 at 1:00 PM ET. The markets span both the match outcome and specific in-game mechanics (inhibitors, kills, dragons, Baron, penta/quadra kills, and kill parity). Resolution depends on official match completion and in-game statistics from gol.gg.
Kalshi market has a logical contradiction: it resolves YES if EITHER team wins, making it impossible to resolve NO. This creates a fundamental data integrity failure that makes the market unresolvable as stated.
Hero Tip:
Do not trade the Kalshi market as written. On Polymarket, you have clear binary outcomes (Solary wins or Ici Japon wins). On Kalshi, the market structure guarantees YES resolution regardless of match outcome, which violates basic market logic and suggests a drafting error. Seek clarification from Kalshi before placing any position.
Critical Divergence Points:
Polymarket:
Binary match outcome market. Resolves to 'Solary' if Solary wins, 'Ici Japon Corp. Esport' if Ici Japon wins. Includes standard cancellation/delay/forfeit clauses that resolve to 50-50. Clear mutually exclusive outcomes with well-defined resolution source (gol.gg).
Kalshi:
Market states: 'If Solary wins... then resolves to Yes. If Ici Japon Corp. Esport wins... then resolves to Yes.' This creates a logical impossibility where both possible match outcomes trigger YES resolution, leaving no path to NO resolution. No cancellation or edge-case handling is specified.
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.