TOTAL VOLUME:
$154.3b
24H VOL:
$219,029,434
24H TRANSACTIONS:
2,984,028,936
OPEN INTEREST:
$1,869,293,526
411,051
Markets across
40,408
events
MATCHED EVENTS:
4,377
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
This market tracks the outcome of a Premier League football match between Manchester United and AFC Bournemouth on October 25, 2026, specifically whether AFC Bournemouth will win. Currently, the aggregated probability of an AFC Bournemouth win is 99.0%, while Manchester United FC winning is estimated at 1.0%. This consensus view combines data from Predict and Polymarket, and will resolve based on official statistics of the event as recognized by the Premier League governing body. Keep an eye on the match itself on October 25, 2026, to see if Bournemouth can secure a victory as heavily predicted.
This event is for the upcoming Premier League game, scheduled for Sunday, October 25, 2026 between Manchester United FC and AFC Bournemouth.
This event is for the upcoming Premier League game, scheduled for Sunday, October 25, 2026 between Manchester United FC and AFC Bournemouth.
Prediction market odds often differ from traditional sportsbook odds due to the differing incentives of participants. Sportsbooks aim to profit by setting lines that attract balanced betting, while prediction market participants are incentivized to accurately forecast the outcome. This can lead to prediction markets being more efficient at reflecting true probabilities, especially as more information becomes available. However, sportsbooks may offer different markets, such as prop bets, not currently available in this market. Both offer valuable insights, but prediction markets benefit from the wisdom of the crowd and direct skin in the game.
Prices on Polymarket and Predict for this market can diverge due to several factors. 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. Each platform attracts different user bases with varying risk appetites and information access, leading to distinct market dynamics. Trading fees and platform-specific rules also contribute to price discrepancies. Furthermore, the volume traded on each platform influences price discovery; a larger volume on one platform may result in a more efficient and potentially different price than on the other. These differences reflect the independent price-setting mechanisms at play on Polymarket and Predict.