TOTAL VOLUME:
$154.4b
24H VOL:
$235,918,089
24H TRANSACTIONS:
2,984,028,936
OPEN INTEREST:
$1,884,820,873
413,109
Markets across
40,428
events
MATCHED EVENTS:
4,364
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Oct 28, 9:30 PM EST
Predict
This group covers markets on the outcome of a Major League Soccer (MLS) match between Toronto FC and D.C. United SC scheduled for October 28, 2026. Markets ask whether Toronto FC or D.C. United SC will win, or if the game will end in a draw.
This event is for the upcoming MLS game, scheduled for Wednesday, October 28, 2026 between Toronto FC and D.C. United SC.
This event is for the upcoming MLS game, scheduled for Wednesday, October 28, 2026 between Toronto FC and D.C. United SC.
Prediction market odds, like those displayed for this market, often differ from traditional sportsbook odds. Sportsbooks set lines to balance their risk and incorporate a profit margin, while prediction markets are driven by the collective wisdom of traders who are incentivized to accurately forecast the outcome. This can lead to prediction markets being more efficient and accurate, especially as more information becomes available. However, sportsbooks may offer different types of bets or have different limitations, influencing their odds. It's useful to compare both to gain a broader perspective.
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. Price discrepancies between Polymarket and Predict can occur due to several factors. Each platform attracts a different user base with varying risk tolerances and information sets, leading to differing opinions on the Toronto FC vs. D.C. United match. Trading volume can also play a role; a larger volume on one platform may indicate greater confidence in a particular outcome. Additionally, the specific market mechanics and fee structures on Polymarket and Predict can influence pricing. These factors combine to create potentially different probabilities for the same event across the two platforms.