TOTAL VOLUME:
$154.4b
24H VOL:
$290,393,159
24H TRANSACTIONS:
2,984,640,614
OPEN INTEREST:
$1,944,100,805
420,493
Markets across
40,511
events
MATCHED EVENTS:
4,612
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Oct 17, 12:49 PM EST
Polymarket
This group covers markets on the outcome of a Chinese Super League match between Shandong Taishan FC and Zhejiang Zhiye FC on October 17, 2026. Markets ask whether Shandong Taishan FC will win, Zhejiang Zhiye FC will win, or if the game will end in a draw.
This event is for the upcoming Chinese Super League game, scheduled for Saturday, October 17, 2026 between Shandong Taishan FC and Zhejiang Zhiye FC.
This event is for the upcoming Chinese Super League game, scheduled for Saturday, October 17, 2026 between Shandong Taishan FC and Zhejiang Zhiye FC.
Prediction market odds, like those found on Polymarket and Predict, often differ from traditional sportsbook odds due to the mechanisms behind price discovery. Sportsbooks set odds based on their internal models and aim to profit from margins, while prediction markets rely on the collective intelligence of traders who have skin in the game. This market’s odds reflect what participants believe is the true probability of each outcome, potentially incorporating information not fully captured by sportsbooks. Consequently, discrepancies can arise, offering opportunities for arbitrage or highlighting differing perspectives on the event’s probability.
Polymarket and Predict 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 Predict can diverge for several reasons. Each platform attracts a different user base with varying levels of expertise and access to information related to the Chinese Super League. Trading volume and liquidity also differ between the two platforms, influencing price sensitivity. Furthermore, the specific market design and available trading options on Polymarket versus Predict can lead to differing price levels. These factors contribute to a dynamic pricing environment where the odds reflect the unique characteristics of each platform’s trading activity.