TOTAL VOLUME:
$154.7b
24H VOL:
$279,496,801
24H TRANSACTIONS:
2,984,640,614
OPEN INTEREST:
$1,923,931,766
416,910
Markets across
40,107
events
MATCHED EVENTS:
4,571
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Nov 2, 3:40 PM EST
Kalshi
This group forecasts the outcome of a soccer match between Hapoel Tel Aviv FC and Maccabi Haifa FC scheduled for November 2, 2026. Markets exist for Hapoel Tel Aviv winning, Maccabi Haifa winning, and the game ending in a draw.
This event is for the upcoming Israel Premier League game, scheduled for Monday, November 2, 2026 between Hapoel Tel Aviv FC and Maccabi Haifa FC.
The event resolves based on the result of the Hapoel Tel Aviv vs Maccabi Haifa professional Israeli Premier League soccer game scheduled for November 2, 2026, after 90 minutes plus stoppage time. If Hapoel Tel Aviv wins, that market resolves to Yes. If Maccabi Haifa wins, that 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 as determined by the platform. The event exclusively considers the result after regular time and stoppage time, with no account for extra time or penalty shootouts. Kalshi explicitly states it is not affiliated 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. Prices on Polymarket and Kalshi may differ due to variations in user base, trading volume, and market-specific rules. Polymarket may attract a different demographic of traders than Kalshi, leading to differing opinions reflected in the prices. Additionally, the volume traded on each platform impacts price discovery; a larger volume generally leads to more efficient pricing. Differences in the fees charged by each platform can also contribute to price discrepancies. These factors combine to create potentially distinct probabilities for the same event across the two venues.