TOTAL VOLUME:
$134b
24H VOL:
$103,397,351
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,410,176,180
399,592
Markets across
30,097
events
MATCHED EVENTS:
2,622
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
Closed: Sep 6, 1:05 PM EST
Kalshi
This group forecasts the outcome of a soccer match between MVV Maastricht and Roda JC Kerkrade scheduled for September 6, 2026. Markets exist for either team winning, or the game ending in a draw, all determined within 90 minutes of regular play plus stoppage time.
This event is for the upcoming Netherlands Eerste Divisie game, scheduled for Sunday, September 6, 2026 between MVV Maastricht and Roda JC Kerkrade.
The event resolves based on the result of the Maastricht vs Roda professional Eerste Divisie soccer match scheduled for September 6, 2026, after 90 minutes plus stoppage time. Three distinct markets correspond to possible outcomes: Maastricht win, Roda win, or a tie. If Maastricht scores more goals than Roda by the end of regulation time, the Maastricht market resolves positively. Conversely, if Roda scores more goals, their market resolves positively. If both teams score an equal number of goals, the Tie market resolves positively. No outcomes—including wins or ties—are determined by extra time, penalty shootouts, or similar post-regulation procedures. Should the match be cancelled or rescheduled to more than 48 hours beyond the original date, all markets will resolve to a fair price as determined by the platform, ensuring equitable treatment for all participants under exceptional circumstances.
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. The differing prices on Polymarket and Kalshi for the MVV vs. Roda JC match reflect variations in trader participation, market design, and information access. Each platform attracts a different user base with potentially unique insights. Additionally, the fee structures and liquidity on each platform can influence pricing. For example, higher fees on one platform might lead to slightly lower prices, while greater liquidity on another could result in tighter spreads. These factors combine to create distinct price discovery processes, even for the same underlying event.