TOTAL VOLUME:
$154.4b
24H VOL:
$245,801,863
24H TRANSACTIONS:
2,984,028,936
OPEN INTEREST:
$1,902,097,102
417,059
Markets across
40,178
events
MATCHED EVENTS:
4,415
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Oct 3, 7:10 PM EST
Kalshi
This group covers various markets related to the UTEP vs. New Mexico college football game scheduled for October 3rd. Markets include the winner of the game, point spreads, and over/under totals for points scored by both teams and in specific game quarters/halves.
In the upcoming college football game between UTEP and New Mexico, scheduled for October 3 at 4:00PM ET: This market will resolve to "UTEP" if UTEP win the game. This market will resolve to "New Mexico" if New Mexico 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 UTEP or New Mexico wins the game as scheduled on October 3, 2026. If the game is postponed but begins within 48 hours of the original start time, the market remains open and resolves based on the official final result. If the game is cancelled or not started within 48 hours, the market resolves to a fair price.
Differences in prices between Polymarket and Kalshi can arise from 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 attracts a different user base with varying expertise and information, leading to distinct perspectives on the UTEP vs. New Mexico game. Trading mechanisms and fee structures also vary, influencing how quickly prices adjust to new information. Additionally, the volume traded on each platform can impact price discovery; a market with higher volume generally exhibits more efficient pricing. These factors contribute to the observed price discrepancies, offering traders opportunities for arbitrage.