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 17, 10:21 PM EST
Polymarket
This event group concerns the halftime result of a Major League Soccer (MLS) match between New York City FC and Los Angeles FC. Markets exist to predict whether New York City FC, Los Angeles FC, or a draw will be leading at halftime.
In the upcoming MLS game between New York City FC and Los Angeles FC, scheduled for October 17, 2026 at 7:30 PM ET: This event contains halftime result markets for home, draw, and away outcomes within the first 45 minutes of regular play plus stoppage time.
In the upcoming MLS game between New York City FC and Los Angeles FC, scheduled for October 17, 2026 at 7:30 PM ET: This event contains halftime result markets for home, draw, and away outcomes within the first 45 minutes of regular play plus stoppage time.
Prediction market odds, like those found on Polymarket and Predict, often reflect the collective wisdom of a diverse group of traders, potentially offering a different perspective than traditional sportsbooks. Sportsbooks set odds based on models and expert analysis, while this market is driven by real money at stake, incentivizing participants to be accurate. This can lead to discrepancies, especially when public sentiment differs from expert opinion. It’s common to see prediction markets move faster to incorporate new information, potentially providing an edge over static sportsbook lines.
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. The prices for the NYCFC vs. LAFC halftime result on Polymarket and Predict may differ due to variations in user base, trading volume, and market design. Polymarket might attract a different type of trader than Predict, leading to differing opinions reflected in the prices. Additionally, the specific rules and fee structures on each platform can influence trading behavior and, consequently, the odds. These factors contribute to a dynamic pricing environment where discrepancies are common and can present opportunities for arbitrage.