TOTAL VOLUME:
$154.5b
24H VOL:
$271,200,656
24H TRANSACTIONS:
2,984,640,614
OPEN INTEREST:
$1,922,627,141
420,368
Markets across
40,352
events
MATCHED EVENTS:
4,484
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Oct 31, 6:45 PM EST
Kalshi
This group covers various markets related to the college football game between Colorado State and Utah State scheduled for October 31st. Markets include the winner, point spreads, and over/under totals for the game and specific quarters/halves, as well as team totals.
In the upcoming college football game between Colorado State and Utah State, scheduled for October 31 at 3:30PM ET: This market will resolve to "Colorado State" if Colorado State win the game. This market will resolve to "Utah State" if Utah State win the game. Overtime is included if played. If the game ends in a tie, this market will resolve 50-50. If the game is postponed, this market will remain open until the game has been completed. If the game is canceled entirely, with no make-up game, this market will resolve 50-50.
The market resolves to Yes if either Colorado State or Utah State wins the game as scheduled on October 31, 2026. If the game is postponed but begins within 48 hours of the original start time, the market will remain open and resolve based on the official final result. If the game is cancelled or not started within 48 hours, the market resolves to a fair price.
Prices for the Colorado State vs. Utah State game may differ between Polymarket and Kalshi due to several factors. 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. Each platform has its own user base, trading dynamics, and fee structure, which can influence price discovery. Differences in liquidity – the amount of volume traded – can also cause price discrepancies. Furthermore, the specific market design on each platform (e.g., different contract types or settlement conditions) can attract different types of traders and lead to varying valuations. These factors combine to create independent price signals, even for the same underlying event.