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: Nov 1, 1:59 AM EST
Kalshi
This market tracks the probability of the total points scored in the second half of the Northern Illinois vs. UNLV college football game exceeding 21.5. Currently, the aggregated consensus across Polymarket and Kalshi gives a 100.0% probability to “Northern Illinois vs. UNLV: 2H O/U 21.5”. This prediction market will resolve based on the outcome of the Northern Illinois vs UNLV game, as determined by whether UNLV wins the game originally scheduled for Oct 31, 2026. Keep an eye on the game itself on October 31st, 2026, to see if the total second-half points surpass the threshold.
In the upcoming college football game between Northern Illinois and UNLV, scheduled for October 31 at 10:30PM ET: This market will resolve to "Northern Illinois" if Northern Illinois win the game. This market will resolve to "UNLV" if UNLV 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 the specified team wins the Northern Illinois vs UNLV college football game originally scheduled for Oct 31, 2026. If the game is postponed but begins within 48 hours of its originally scheduled 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 of its originally scheduled start, the market resolves to a fair price. Kalshi is not affiliated with the NCAA, and all trademarks remain property of their respective owners.
Prices on Polymarket and Kalshi can diverge 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 fees, and liquidity, which can all influence price discovery. Differences in market design, such as the types of contracts offered (e.g., spread vs. outright winner), also contribute to price variations. Furthermore, differing levels of information awareness and trading strategies among users on each platform can lead to distinct price signals for the Northern Illinois vs. UNLV game. Volume also plays a role; lower volume on one platform may result in greater price volatility.