This event group covers a Best-of-3 Valorant match between 100 Thieves and Cloud9 scheduled for February 13, 2026 at 3:00 PM ET in the VCT Americas Kickoff Playoffs. Markets span match winner, individual map winners, games total, and map handicaps across Polymarket and Kalshi platforms.
Source fragmentation across platforms (Liquipedia vs vlr.gg) and ambiguous scope in Kalshi market language regarding match outcome versus tournament outcome.
Hero Tip:
Use Liquipedia as the primary consensus source for all match-level markets. For the Map Handicap (C9 -1.5) market on Polymarket, cross-reference vlr.gg independently. Request clarification from Kalshi on whether their market resolves based on the individual match result or the broader tournament outcome.
Critical Divergence Points:
Polymarket: Five markets (Map 1 Winner, Games Total O/U 2.5, Map Handicap 100T -1.5, Map 2 Winner, Match Winner) use Liquipedia as the authoritative source. One market (Map Handicap C9 -1.5) specifies vlr.gg as the source, explicitly excluding broadcasts and streams. All markets include 50-50 resolution for cancellations, delays beyond 7 days, ties, and forfeits (except Match Winner, which resolves to the winning team if forfeiture occurs mid-match).
Kalshi: Market language conflates tournament victory with match outcome: 'If 100 Thieves wins the VCT Americas Kickoff 2026: Cloud9 vs. 100 Thieves Valorant match...then the market resolves to Yes.' This creates ambiguity as to whether resolution depends on the match result or the tournament result. No explicit resolution source 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.
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