TOTAL VOLUME:
$134b
24H VOL:
$103,397,351
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,410,176,180
399,592
Markets across
30,097
events
MATCHED EVENTS:
2,622
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
Closed: Sep 5, 11:29 PM EST
Kalshi
This group covers multiple markets related to the college football game between Butler and Montana State on September 5th. Markets include the winner of the game, the point spread, and the over/under total points scored. These markets allow users to predict various outcomes of the game.
In the upcoming college football game, scheduled for September 5 at 8:30PM ET: If Butler wins, the market will resolve to "Butler". If Montana State wins, the market will resolve to "Montana State". If the game is postponed, this market will remain open until the game has been completed. If the game is canceled entirely or ends in a tie, with no make-up game, this market will resolve 50-50.
All markets resolve based on whether the total points scored by both teams in the Butler vs Montana St. college football game scheduled for Sep 5, 2026, exceed specified thresholds ranging from 39.5 to 79.5 points. Each market has a unique threshold, and if the combined score surpasses that threshold, the market resolves to Yes; otherwise, it resolves to No. If the game is postponed but commences within 48 hours of the original start time, all markets remain open and resolve according to the final official score. If the game does not start within this 48-hour window, all markets will resolve to a fair price, ensuring equitable treatment for all participants regardless of the specific threshold chosen.
Prediction market odds, like those found for this market, often reflect the collective wisdom of a diverse group of traders, potentially offering a different perspective than traditional sportsbooks. Sportsbooks set lines based on internal models and risk management, while prediction markets are driven by individuals wagering their own capital. This can lead to discrepancies, especially when public sentiment diverges from expert opinion. It's also common to see prediction markets react more quickly to new information, as traders continuously update their forecasts based on the latest news and analysis.
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. Price discrepancies between Polymarket and Kalshi for the Butler vs. Montana State game can arise due to several factors. Each platform attracts a different user base with varying risk appetites and predictive expertise, influencing trading behavior and price discovery. Furthermore, the liquidity and trading volume on each platform can differ, leading to price variations. Market makers and arbitrageurs may also play a role, exploiting temporary price differences to profit, but these effects are often short-lived. These dynamics contribute to the unique price signals observed on Polymarket and Kalshi.