TOTAL VOLUME:
$154.3b
24H VOL:
$228,458,490
24H TRANSACTIONS:
2,984,028,936
OPEN INTEREST:
$1,879,276,037
410,833
Markets across
40,345
events
MATCHED EVENTS:
4,363
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Nov 1, 10:37 AM EST
Kalshi
This group forecasts the outcome of a soccer match between SK Brann and Molde FK scheduled for November 1, 2026. Markets exist for Brann winning, Molde winning, and the game ending in a draw. Resolution is based on the official result after 90 minutes plus stoppage time.
This event is for the upcoming Norway Eliteserien game, scheduled for Sunday, November 1, 2026 between SK Brann and Molde FK.
The event resolves based on the result of the Brann vs Molde professional Eliteserien soccer match originally scheduled for November 1, 2026, after 90 minutes plus stoppage time. Three possible outcomes are considered: a win for Brann, a win for Molde, or a tie. If either team wins within the standard match duration, the corresponding market resolves to Yes. If the match ends in a tie after regular time, the Tie market resolves to Yes. Should the game be cancelled or rescheduled to more than 48 hours beyond the original date, the markets will resolve to a fair price as determined by the platform’s rules. Extra time and penalty shootouts are explicitly excluded from consideration in determining the outcome.
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. Differences in pricing between Polymarket and Kalshi for this market can arise due to variations in trader demographics, liquidity, and market-specific rules. Polymarket may attract a different type of trader than Kalshi, leading to differing opinions on the probability of each outcome. Additionally, the volume of trading on each platform – currently $227,440 overall – can influence price discovery. The spread between the two platforms reflects these factors and the ongoing process of price convergence as traders react to new information and adjust their positions. These price discrepancies are a natural part of a decentralized prediction market.