TOTAL VOLUME:
$154.7b
24H VOL:
$279,496,801
24H TRANSACTIONS:
2,984,640,614
OPEN INTEREST:
$1,923,931,766
416,910
Markets across
40,107
events
MATCHED EVENTS:
4,571
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Oct 14, 11:38 PM EST
Polymarket
This group covers markets on the outcome of a Major League Soccer (MLS) match between D.C. United SC and New York Red Bulls on October 14, 2026. Markets ask whether D.C. United will win, New York Red Bulls will win, or the game will end in a draw.
This event is for the upcoming MLS game, scheduled for Wednesday, October 14, 2026 between D.C. United SC and New York Red Bulls.
This event is for the upcoming MLS game, scheduled for Wednesday, October 14, 2026 between D.C. United SC and New York Red Bulls.
Prediction market odds, like those displayed for this market, often reflect a wisdom-of-the-crowd effect, potentially offering different insights than traditional sportsbooks. Sportsbooks set lines based on their own models and to balance action, while prediction markets are driven by traders directly expressing their beliefs. This can lead to discrepancies, especially when public sentiment strongly diverges from the sportsbook’s initial assessment. The difference in probabilities can also stem from differing levels of information available to each group and the incentives driving their predictions. It’s valuable to compare both to form a well-rounded view.
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 has its own user base, trading dynamics, and risk tolerance, which can lead to differing opinions on the probability of outcomes. Furthermore, the liquidity and volume on each platform can influence price discovery. While both platforms address the same question regarding the D.C. United vs. Red Bulls match, differing market participation and information flow can create temporary discrepancies in the perceived probabilities reflected in the prices.