TOTAL VOLUME:
$134.1b
24H VOL:
$113,466,932
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,423,222,590
402,751
Markets across
30,217
events
MATCHED EVENTS:
2,632
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
Closed: Sep 16, 9:16 PM EST
Kalshi
This market tracks the outcome of a Colombian Liga DIMAYOR soccer match between Once Caldas and CD Tolima. Currently, the consensus probability of Once Caldas winning on August 27, 2026, is 100.0%, while CD Tolima winning has a 0.1% probability, aggregating views from Polymarket and Kalshi. The resolution source for this market is https://dimayor.com.co/. Keep an eye on September 16, 2026, as this is the date Kalshi uses for the match and will determine market settlement.
This event is for the upcoming Colombia Primera A game, scheduled for Thursday, August 27, 2026 between Once Caldas and CD Tolima.
The event resolves based on the result of the Once Caldas vs Tolima professional Colombian Liga DIMAYOR soccer game scheduled for September 16, 2026. A market resolves to Yes if the specified team wins the match within 90 minutes plus stoppage time, excluding extra time or penalties. If the game ends in a tie, the 'Tie' market resolves to Yes. Should the match be cancelled or rescheduled to more than 48 hours beyond the original date, all markets will resolve to a fair price. Kalshi disclaims any official affiliation with the governing league, and all trademarks remain property of their respective owners.
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 can arise from several factors. Each platform has its own user base with varying levels of expertise and access to information related to the Once Caldas vs. Tolima match. Trading fees and platform-specific rules can also influence prices. Furthermore, the liquidity of this market may differ across platforms, impacting how readily prices adjust to new information. These factors contribute to the observed price discrepancies, even though both platforms are tracking the same underlying event.