LoL: GAM Esports vs CTBC Flying Oyster (BO3) - LCP Regular Season

This market refers to the LoL match between GAM Esports and CTBC Flying Oyster in the LCP Regular Season, initially scheduled for May 17 at 7:30AM ET.

This market will resolve to "GAM Esports" if GAM Esports win the match against CTBC Flying Oyster.

This market will resolve to "CTBC Flying Oyster" if CTBC Flying Oyster win the match against GAM Esports.

If the match is canceled (not played at all), ends in a tie, or is delayed beyond 7 days from the scheduled date without a winner determined, this market will resolve to 50-50.

If the match begins but is not completed, and one team wins due to the opponent's forfeiture, disqualification, or walkover, this market will resolve to the team who wins.

If the match ends in a forfeit, disqualification, or walkover (team withdraws before the start and the other wins automatically), this market will resolve to 50-50.

The resolution source for this market will be official information from https://gol.gg/esports/home. However, if https://gol.gg/esports/home has not published final results within 2 hours after the event’s conclusion, a consensus of credible reporting may be used instead including video evidence.

In cases where a team’s listed name includes minor discrepancies from the resolution source, this market will resolve based on the underlying real-world match rather than exact name matching. Recognizable abbreviations, alternate or erroneous spellings, sponsor tags, affiliate or academy designations, regional identifiers, and minor formatting differences will be treated as referring to the same team, provided the intended team can be clearly and uniquely identified within the relevant competition. If a listed team name has no reasonable connection to any participating team, or if it matches or could reasonably refer to another team in the same competition such that the intended team cannot be unambiguously determined, this market will resolve 50-50.

Prediction markets function as real-time belief compression layers where distributed information becomes executable probability.

Each trade represents:

• updated information processing
• position hedging against future states
• narrative reinforcement or rejection
• asymmetric knowledge correction

Unlike polling or forecasting models, these systems continuously self-correct through financial exposure, making them sensitive to:

This produces a live probabilistic system that behaves closer to a market-driven intelligence engine than a static prediction tool.