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 29, 5:38 PM EST
Kalshi
This market tracks whether Everton FC will win their match against Newcastle United FC on October 29, 2026. Currently, the consensus probability of Everton FC winning is 100.0%, aggregated from Kalshi, Predict, and Polymarket. Resolution will be based on official statistics of the event as recognized by the governing body or event organizers (EFL). Keep an eye on the kickoff of the match on October 29, 2026, to see if this prediction holds true.
This event is for the upcoming EFL Cup (Carabao Cup) game, scheduled for Thursday, October 29, 2026 between Everton FC and Newcastle United FC.
The event resolves based on the result of the Everton vs Newcastle professional EFL Cup soccer match originally scheduled for October 29, 2026, after 90 minutes plus stoppage time, excluding extra time or penalty shootouts. Three distinct markets correspond to the possible outcomes: Everton win, Newcastle win, or a tie. If the match ends in a tie after regulation time, the 'Tie' market resolves to Yes. Should the game be 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 rules. The platform explicitly states it is not affiliated with or connected to the governing league, and all trademarks remain the property of their respective owners.
This event is for the upcoming EFL Cup (Carabao Cup) game, scheduled for Thursday, October 29, 2026 between Everton FC and Newcastle United FC.
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 due to several factors. Each platform attracts a different user base with varying levels of expertise and access to information, leading to differing opinions. Trading volume also plays a role; 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 differences highlight the dynamic nature of prediction markets and the value of aggregating information across multiple venues.