TOTAL VOLUME:
$154.6b
24H VOL:
$323,326,361
24H TRANSACTIONS:
2,984,640,614
OPEN INTEREST:
$1,969,435,260
419,363
Markets across
40,411
events
MATCHED EVENTS:
4,612
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Oct 11, 1:26 PM EST
Polymarket
This prediction group covers a variety of markets related to the Stade Rennais FC 1901 vs. AJ Auxerre Ligue 1 match on October 11th. Markets include spreads, over/under goals, and both teams to score, both for the full match and for the first and second halves. The markets are designed to predict the outcome of various aspects of the game.
More markets for the Ligue 1 game, scheduled for October 11 at 11:15 AM ET.
More markets for the Ligue 1 game, scheduled for October 11 at 11:15 AM ET.
Prediction market odds, like those found on Polymarket and Predict, often differ from traditional sportsbook odds due to the differing incentives and information sources. Sportsbooks set odds to maximize profit, incorporating a margin for themselves, while prediction markets allow participants to directly express their beliefs. This market benefits from the “wisdom of the crowd,” potentially leading to more accurate probabilities, especially as more traders participate. However, sportsbook odds often react faster to breaking news, while prediction markets may take longer to adjust, creating temporary discrepancies. The volume on this market is currently $141,794.
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 can diverge due to several factors. Each platform attracts a different user base with varying levels of expertise and access to information regarding the Stade Rennais vs. Auxerre match. Furthermore, the liquidity and trading volume on each platform – currently $141,794 overall – can influence price discovery. Different fee structures and platform-specific rules may also contribute to these discrepancies. It's common to see variations even when tracking the same underlying event across multiple prediction market venues.