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 9, 5:28 AM EST
Kalshi
This group forecasts the outcome of a K League 1 soccer match between Incheon United FC and Pohang Steelers FC on October 9, 2026. Markets exist for Incheon United winning, Pohang Steelers winning, and the game ending in a draw.
This event is for the upcoming K-League game, scheduled for Friday, October 9, 2026 between Incheon United FC and Pohang Steelers FC.
The event resolves based on the result of the Incheon Utd vs Pohang Steelers professional Korea K League 1 soccer match scheduled for October 9, 2026, after 90 minutes plus stoppage time. A win for Incheon Utd resolves the 'Incheon Utd' market to Yes; a win for Pohang Steelers resolves the 'Pohang Steelers' market to Yes; and a tie resolves the 'Tie' market to Yes. If the match 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, with no account for extra time or penalty shootouts. Kalshi explicitly disclaims any official affiliation with the governing league, and all trademarks remain the 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 can diverge for several reasons. Each platform attracts a different user base with varying levels of expertise and access to information regarding the K League 1 match. Trading volume and liquidity also play a role; a higher volume on one platform can lead to more efficient price discovery. Furthermore, the specific market structures and fee schedules on Polymarket and Kalshi can influence trading behavior and, consequently, the displayed probabilities. These factors contribute to the observed differences in how traders assess the likelihood of various outcomes.