TOTAL VOLUME:
$134b
24H VOL:
$103,397,351
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,410,176,180
399,592
Markets across
30,097
events
MATCHED EVENTS:
2,622
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
Closed: Sep 16, 6:57 PM EST
Polymarket
This market tracks the outcome of a Europa League soccer match between RSC Anderlecht and Olympique Lyonnais, specifically whether Olympique Lyonnais will win on September 16, 2026. Currently, the consensus probability of Olympique Lyonnais winning is 100.0%. This forecast is an aggregation of views from Kalshi, Polymarket, and Predict, and will resolve based on the result reported by https://www.uefa.com/. Keep an eye on the match itself on September 16, 2026, to see if Olympique Lyonnais secures a victory.
This event is for the upcoming UEFA Europa League game, scheduled for Wednesday, September 16, 2026 between RSC Anderlecht and Olympique Lyonnais.
The event evaluates different goal-differential thresholds for either team winning the Anderlecht vs Lyon Europa League match scheduled for September 16, 2026. All markets resolve based solely on the final score after 90 minutes plus stoppage time; extra time and penalty shootouts are excluded from consideration. A 'Yes' outcome occurs if Anderlecht wins by more than 2.5 or 1.5 goals, or if Lyon wins by more than 1.5 or 2.5 goals. The governing rules emphasize that Kalshi holds no official affiliation with the league, and all trademarks remain property of their respective owners.
This event is for the upcoming UEFA Europa League game, scheduled for Wednesday, September 16, 2026 between RSC Anderlecht and Olympique Lyonnais.
Polymarket and Kalshi can show different implied probabilities for the same outcome because of liquidity, fee structure, participant mix, and how each venue defines the contract. The prices on Polymarket and Kalshi may diverge due to several factors. Each platform attracts a different user base with varying levels of expertise and access to information regarding the Anderlecht vs. Lyon match. Trading mechanisms also differ; Polymarket operates with a continuous trading model, while Kalshi may use a different approach. These variations in user composition and market structure can lead to discrepancies in price discovery. Additionally, differing liquidity levels on each platform can influence price volatility and create temporary divergences in the perceived probability of each outcome.