TOTAL VOLUME:
$134.2b
24H VOL:
$126,324,530
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,434,646,834
406,019
Markets across
30,401
events
MATCHED EVENTS:
2,689
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
Closed: Sep 13, 5:32 PM EST
Kalshi
This market tracks the probability of a draw in the Mirassol FC versus EC Vitória Brasileiro Serie A soccer game. Currently, the consensus probability of a draw is 100.0%, aggregated from Polymarket and Kalshi. The market will resolve based on the official result of the game after 90 minutes plus stoppage time, as determined by the game’s outcome on September 13, 2026. Keep an eye on the official kickoff of the Mirassol FC vs. EC Vitória match on September 13, 2026, as this will initiate the resolution window.
This event is for the upcoming Brazil Série A game, scheduled for Sunday, September 13, 2026 between Mirassol FC and EC Vitória.
The event resolves based on the result of the Mirassol vs Vitoria professional Brasileiro Serie A soccer match scheduled for September 13, 2026, after 90 minutes plus stoppage time. If Mirassol wins, the 'Mirassol' market resolves to Yes. If Vitoria wins, the 'Vitoria' market resolves to Yes. If the match ends in a tie, the 'Tie' market resolves to Yes. If the game is cancelled or rescheduled to more than 48 hours beyond the original date, all markets will resolve to a fair price. The event exclusively considers the result after regular time and stoppage time, with no account for extra time or penalty shootout outcomes.
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. Prices on Polymarket and Kalshi for the Mirassol vs. Vitória match can diverge for several reasons. Each platform attracts a different user base with varying expertise and information. Furthermore, the liquidity and trading volume on each platform can influence price discovery. Polymarket might have more traders specializing in soccer, leading to a different assessment of the teams’ probabilities than on Kalshi. Market design choices, such as trading limits or fee structures, can also contribute to price discrepancies. These differences highlight the benefits of aggregating information across multiple platforms to gain a more robust view.