TOTAL VOLUME:
$154.4b
24H VOL:
$230,589,906
24H TRANSACTIONS:
2,984,028,936
OPEN INTEREST:
$1,885,293,300
410,482
Markets across
40,213
events
MATCHED EVENTS:
4,340
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Oct 25, 2:01 PM EST
Kalshi
This group forecasts the outcome of a soccer match between Volos NPS and Panathinaikos Athens scheduled for October 25, 2026. Markets exist for Volos NPS winning, Panathinaikos Athens winning, and the game ending in a draw.
This event is for the upcoming Greece Super League game, scheduled for Sunday, October 25, 2026 between Volos NPS and Panathinaikos Athens.
The event resolves based on the full-time result of the Volos vs Panathinaikos professional Greece Super League soccer match scheduled for October 25, 2026, after 90 minutes plus stoppage time. A 'Yes' outcome occurs for the Volos market if Volos wins, for the Panathinaikos market if Panathinaikos wins, and for the Tie market if the game concludes in a draw. All markets exclusively consider the result at the end of regular time, excluding extra time or penalty shootouts. If the match is cancelled or rescheduled to more than 48 hours beyond the original date, the markets will resolve to a fair price, ensuring equitable treatment for all participants. The event explicitly disclaims any official affiliation with the governing league, and all trademarks remain the property of their respective owners.
Differences in pricing between Polymarket and Kalshi for the Volos vs. Panathinaikos match can arise from several factors. 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. Each platform attracts a different user base with varying levels of expertise and information, leading to differing interpretations of the same event. Trading volume also plays a role; lower volume on one platform can result in greater price volatility and divergence. Furthermore, the specific market structures and fee schedules on Polymarket and Kalshi can influence trader behavior and, consequently, the prices observed for this market. These factors contribute to the dynamic pricing seen across prediction markets.