Dota 2: OG vs Team Yandex (BO2) - DreamLeague Stage 1 Group A
Volume:
$155,044
Markets
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
This event group covers a best-of-two Dota 2 match between OG and Team Yandex scheduled for February 17, 2026 at 11:00 AM ET during DreamLeague Stage 1 Group A. Markets track the overall match winner, Game 1 winner, and Game 2 winner across Polymarket and Kalshi platforms.
Polymarket specifies official data sources (dotabuff.com for match; Twitch for games) with clear fallback logic, while Kalshi provides vague resolution criteria without source designation or edge-case handling. Kalshi's dual Yes outcomes also create logical ambiguity.
Hero Tip:
Use Polymarket markets as primary trading vehicles; they have explicit sources and clear tie/cancellation rules. Treat Kalshi markets as secondary until their resolution methodology is clarified. Monitor dotabuff.com and https://www.twitch.tv/esl_dota2 directly for real-time results.
Critical Divergence Points:
Polymarket: Match winner resolves via dotabuff.com; Game 1 and Game 2 via Twitch with 12-hour publication window before consensus reporting allowed. Forfeits before match start = 50-50; forfeits during match with one team winning = that team wins. Cancellations or delays beyond 7 days = 50-50.
Kalshi: Resolution criteria state both Team Yandex and OG outcomes resolve to Yes, with no specified data source, tie-breaking logic, or cancellation handling. Lacks reference to dotabuff, Twitch, or other official sources.
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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