TOTAL VOLUME:
$134.1b
24H VOL:
$141,541,542
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,440,096,988
406,065
Markets across
30,522
events
MATCHED EVENTS:
2,692
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
Closed: Sep 13, 10:04 AM EST
Kalshi
This group covers the outcome of a Danish Superliga soccer match between Lyngby BK and Sønderjyske Fodbold on September 13, 2026. Markets ask whether Lyngby BK will win, Sønderjyske Fodbold will win, or if the match will end in a draw.
This event is for the upcoming Denmark Superliga game, scheduled for Sunday, September 13, 2026 between Lyngby BK and Sønderjyske Fodbold.
If Lyngby wins the Lyngby vs Soenderjyske professional Danish Superliga soccer game originally scheduled for Sep 13, 2026 after 90 minutes plus stoppage time (does not include extra time or penalties), then the market resolves to Yes. If Soenderjyske wins the Lyngby vs Soenderjyske professional Danish Superliga soccer game originally scheduled for Sep 13, 2026 after 90 minutes plus stoppage time (does not include extra time or penalties), then the market resolves to Yes. If Tie is the result of the Lyngby vs Soenderjyske professional Danish Superliga soccer game originally scheduled for Sep 13, 2026 after 90 minutes plus stoppage time (does not include extra time or penalties), then the market resolves to Yes.
Prediction market odds, like those found for this market, often reflect the collective wisdom of a diverse group of participants, potentially offering a different perspective than traditional sportsbooks. Sportsbooks set lines based on their own models and aim to balance action on both sides, while prediction markets allow traders to freely express their beliefs. This can lead to discrepancies, especially when public sentiment strongly diverges from the sportsbook's initial assessment. It’s common to see prediction markets move faster to incorporate new information and adjust probabilities accordingly.
Price discrepancies between Polymarket and Kalshi for the Lyngby vs. Sønderjyske match can occur for several reasons. 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. Each platform has its own user base, trading fees, and liquidity, which can influence price discovery. Additionally, differing levels of information access and interpretation among traders on each platform can lead to divergent opinions. Market sentiment and the timing of trades can also contribute to these price variations, as can the specific mechanisms each platform uses for order matching and price updates. These factors result in unique market dynamics on each venue.