TOTAL VOLUME:
$154.4b
24H VOL:
$290,393,159
24H TRANSACTIONS:
2,984,640,614
OPEN INTEREST:
$1,944,100,805
420,493
Markets across
40,511
events
MATCHED EVENTS:
4,612
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Oct 18, 1:33 PM EST
Polymarket
This group covers markets on the outcome of a Ligue 1 soccer match between FC Lorient and AS Monaco FC on October 18, 2026. Markets ask whether either team will win or if the match will end in a draw.
This event is for the upcoming Ligue 1 game, scheduled for Sunday, October 18, 2026 between FC Lorient and AS Monaco FC.
This event is for the upcoming Ligue 1 game, scheduled for Sunday, October 18, 2026 between FC Lorient and AS Monaco FC.
Prediction market odds, like those found on Polymarket and Predict, often reflect the collective wisdom of a diverse group of participants, while sportsbook odds are typically set by professional oddsmakers. This market’s odds can sometimes diverge from traditional sportsbooks due to differences in information access, incentives, and the types of bettors involved. Sportsbooks aim to balance risk and profit, whereas prediction markets incentivize accurate forecasting. Generally, prediction markets are considered to be more efficient at forecasting probabilities, especially when there is significant trading volume, and can provide a valuable alternative perspective to traditional betting options.
Polymarket and Predict can show different implied probabilities for the same outcome because of liquidity, fee structure, participant mix, and how each venue defines the contract. Prices on Polymarket and Predict may differ due to variations in user base, trading activity, and the specific incentives offered on each platform. Each venue attracts a different mix of traders with varying levels of expertise and information. Additionally, the liquidity and volume on each platform can influence price discovery. For example, if Polymarket has significantly higher volume, its prices may be more responsive to new information than those on Predict. These factors contribute to the dynamic pricing observed across different prediction market platforms.