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 14, 3:08 PM EST
Kalshi
This group forecasts the outcome of a single Allsvenskan soccer match between Djurgardens IF and GAIS on September 14, 2026. Markets exist for Djurgardens IF winning, GAIS winning, or the game ending in a draw.
This event is for the upcoming Allsvenskan game, scheduled for Monday, September 14, 2026 between Djurgardens IF and GAIS.
The market resolves based on the result of the Djurgarden vs GAIS professional Allsvenskan soccer game scheduled for Sep 14, 2026, after 90 minutes plus stoppage time. If Djurgarden wins, the 'Djurgarden' market resolves to Yes. If GAIS wins, the 'GAIS' market resolves to Yes. If the game ends in a tie, the 'Tie' market resolves to Yes. If the game is cancelled or rescheduled to over 48 hours away from the original date, all markets will resolve to a fair price according to the rules. The markets exclusively consider regulation time outcomes and do not include extra time or penalty shootouts.
Prediction market odds, like those found in this market, often reflect the wisdom of the crowd, potentially offering a different perspective than traditional sportsbooks. Sportsbooks set odds based on their own models and aim to profit from margins, while prediction markets allow participants to directly express their beliefs. This can lead to discrepancies, especially when public opinion diverges from expert analysis. It’s common to see prediction markets move more quickly to incorporate new information, as traders continuously update their forecasts based on available data. Examining both sources can provide a more comprehensive understanding of the likely outcome.
Prices on Polymarket and Kalshi for this market can diverge due to several factors. 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. Furthermore, differing levels of information available to traders on each platform, or variations in trading strategies, can lead to discrepancies. While both platforms are tracking the same event, the dynamics of supply and demand within each venue independently determine the odds, resulting in potentially different probabilities assigned to the same outcomes. This is a normal occurrence in decentralized prediction markets.