TOTAL VOLUME:
$154.4b
24H VOL:
$245,801,863
24H TRANSACTIONS:
2,984,028,936
OPEN INTEREST:
$1,902,097,102
417,059
Markets across
40,178
events
MATCHED EVENTS:
4,415
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Oct 29, 3:56 PM EST
Kalshi
This market tracks the outcome of a Saudi Professional League soccer match between Al Nassr Saudi Club and Al Kholood Saudi Club, scheduled for October 29, 2026. Currently, the consensus probability of Al Nassr Saudi Club winning is 99.0%, while Al Kholood Saudi Club winning is estimated at 1.0%. This prediction aggregates data from Kalshi, Predict, and Polymarket, and will resolve based on official match statistics, with potential fallbacks to Flashscore or Sofascore as defined by the resolution source. Keep an eye on the official schedule confirmation as the October 29, 2026 date approaches to ensure the match proceeds as planned.
This event is for the upcoming Saudi Professional League game, scheduled for Thursday, October 29, 2026 between Al Nassr Saudi Club and Al Kholood Saudi Club.
The markets resolve based on the result of the Al Nassr vs Al-Kholood professional Saudi Pro League soccer game scheduled for Oct 29, 2026, after 90 minutes plus stoppage time, excluding extra time or penalties. If Al Nassr wins, the 'Al Nassr' market resolves to Yes. If Al-Kholood wins, the 'Al-Kholood' 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 more than 48 hours away from the original date, all markets resolve to a fair price.
This event is for the upcoming Saudi Professional League game, scheduled for Thursday, October 29, 2026 between Al Nassr Saudi Club and Al Kholood Saudi Club.
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 Al Nassr vs. Al Kholood match can diverge due to several factors. Each platform has its own user base, trading dynamics, and fee structures, all of which influence price discovery. Furthermore, differing levels of liquidity on each platform can lead to price discrepancies. Even with the same underlying question, the composition of traders and their individual perspectives contribute to variations in the assessed probabilities. These differences are normal and reflect the independent price-setting mechanisms of each venue.