TOTAL VOLUME:
$154.8b
24H VOL:
$277,138,640
24H TRANSACTIONS:
2,984,640,614
OPEN INTEREST:
$1,905,404,943
412,077
Markets across
39,838
events
MATCHED EVENTS:
4,526
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Time left: 04d:15h:20m
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This group covers markets related to the Penn vs. Cornell college football game scheduled for November 7th, 2026. Markets include the winner of the game, point spreads, and the over/under on total points scored. The markets are designed to resolve based on the official outcome of the game.
In the upcoming college football game between Penn and Cornell, scheduled for November 7 at 1:00PM ET: This market will resolve to "Penn" if Penn win the game. This market will resolve to "Cornell" if Cornell 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 based on the winner of the Penn vs Cornell college football game scheduled for November 7, 2026. If the game is postponed but commences within 48 hours of its original scheduled start time, the market remains open and resolves according to the final official result. Should the game be canceled or fail to start within the 48-hour window, the market will resolve to a fair price. Kalshi clarifies that it holds no official affiliation with the NCAA, and all related trademarks remain property of their respective owners.
In the upcoming college football game between Penn and Cornell, scheduled for November 7 at 1:00PM ET: This market will resolve to "Penn" if Penn win the game. This market will resolve to "Cornell" if Cornell 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.
Prediction market odds, like those found in this market, often reflect a 'wisdom of the crowd' that can differ from traditional sportsbooks. Sportsbooks set lines to balance action and ensure profit, while prediction markets are driven by individuals wagering their own capital based on their beliefs. This can lead to prediction markets being more accurate, especially when information is asymmetric or subjective. However, sportsbooks often have higher liquidity and may react faster to breaking news. The difference in odds can also be influenced by the types of bettors each attracts.
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. Differences in pricing between Polymarket and Kalshi for the Penn vs. Cornell game stem from several factors. Each platform has its own unique user base, trading fees, and market-making algorithms, all of which can influence price discovery. Furthermore, the liquidity and volume on each platform can vary considerably, impacting how quickly prices react to new information. Different risk appetites among traders on Polymarket versus Kalshi can also contribute to price discrepancies. These variations are a normal part of decentralized prediction markets and reflect the dynamic interplay of supply and demand.
This market resolves around Nov 7, 2026, with the outcome confirmed once the event is verifiable from credible public reporting. The final result of the Penn vs. Cornell game, as reported by official sources, will determine the winning outcome. The resolution will be based on the official game statistics and final score, ensuring a transparent and objective determination. Traders should monitor official announcements for the definitive result that will settle this market.
Several factors could significantly impact this market. Any news regarding key player injuries or suspensions for either Penn or Cornell would likely cause shifts in probabilities. Unexpected coaching changes or significant team performance fluctuations in preceding games could also influence trader sentiment. Major upsets in other relevant college basketball games might indirectly affect perceptions of team strength. Furthermore, any late-breaking news regarding the game's location or conditions could also move the market as traders adjust their expectations before Nov 7, 2026.