TOTAL VOLUME:
$154.4b
24H VOL:
$230,589,906
24H TRANSACTIONS:
2,984,028,936
OPEN INTEREST:
$1,885,293,300
410,482
Markets across
40,213
events
MATCHED EVENTS:
4,340
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Nov 2, 4:52 PM EST
Polymarket
This group contains a large number of markets related to the FC Lorient vs. Stade Brestois 29 Ligue 1 match, covering spread betting (with varying handicaps) for both teams, over/under goals markets (with varying thresholds), and both teams to score markets for the full game and first/second halves. The markets all resolve based on the official final score.
More markets for the Ligue 1 game, scheduled for October 31 at 3:45 PM ET.
More markets for the Ligue 1 game, scheduled for October 31 at 3:45 PM ET.
Prediction market odds, like those found on Polymarket and Predict, often reflect the wisdom of the crowd, potentially offering a different perspective than traditional sportsbooks. Sportsbooks set initial lines based on their own models and aim to balance action on both sides, incorporating a profit margin. This market, however, allows traders to freely adjust probabilities based on new information and collective insight. While sportsbooks may be influenced by public perception, prediction markets can sometimes identify mispricings or incorporate information faster, leading to odds discrepancies. It’s a useful exercise to compare both to gain a more well-rounded understanding.
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. Price discrepancies between Polymarket and Predict on this market can arise from several factors. Each platform has its own user base, trading dynamics, and fee structures, all of which can influence price discovery. Additionally, the liquidity and volume on each platform can vary, leading to different levels of price efficiency. Polymarket may attract a different type of trader than Predict, resulting in differing opinions and risk assessments reflected in the market prices. These differences highlight the value of aggregating data across multiple platforms to gain a more robust view of potential outcomes.