TOTAL VOLUME:
$155.8b
24H VOL:
$742,973,284
24H TRANSACTIONS:
3,002,895,743
OPEN INTEREST:
$2,215,342,919
426,856
Markets across
40,308
events
MATCHED EVENTS:
4,596
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Time left: 03d:19h:00m
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This prediction group centers around the college football game between Rutgers and Wisconsin, scheduled for November 7th. Markets cover the game's outcome, point spreads, over/under totals, and various player/team statistics. The markets aim to predict the results of the game and related performance metrics.
In the upcoming college football game between Rutgers and Wisconsin, scheduled for November 7 at 1:00PM ET: This market will resolve to "Rutgers" if Rutgers win the game. This market will resolve to "Wisconsin" if Wisconsin 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 Rutgers or Wisconsin wins the college football game originally scheduled for November 7, 2026. If the game is postponed but starts within 48 hours of the original scheduled time, the market stays open and resolves based on the official result. If the game is cancelled or does not start within 48 hours, the market resolves to a fair price.
In the upcoming college football game between Rutgers and Wisconsin, scheduled for November 7 at 1:00PM ET: This market will resolve to "Rutgers" if Rutgers win the game. This market will resolve to "Wisconsin" if Wisconsin 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 on Polymarket and Kalshi, often differ from traditional sportsbook odds due to the different incentives and information sources involved. Sportsbooks set odds to maximize profit, factoring in a “vig” or commission. Prediction markets, however, allow participants to directly trade on their beliefs, leading to more efficient price discovery. This market benefits from the collective intelligence of a diverse group of traders, potentially identifying mispriced outcomes that sportsbooks might miss. The difference can be especially noticeable when public sentiment strongly deviates from the sportsbook’s initial assessment.
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 attracts a different user base with varying levels of expertise and access to information, leading to differing opinions. Trading mechanisms also play a role; Polymarket currently favors Spread: Wisconsin (-0.5) at 87.5%, while Kalshi leans toward Wisconsin wins at 88.0%. Furthermore, liquidity and volume can vary between the two platforms, impacting price stability and responsiveness to new information. These differences create opportunities for arbitrage, where traders attempt to profit from price discrepancies.
This market resolves around Nov 8, 2026, with the outcome confirmed once the event is verifiable from credible public reporting. The final result of the Rutgers-Wisconsin football game, as reported by official sources, will determine the winning outcome. Trading will cease once the game concludes and the result is officially announced. The market's resolution will reflect which outcome was ultimately realized on the field, providing a clear and objective determination of the market's result. This ensures a transparent and verifiable process for all participants.
Several signals could significantly impact this market before Nov 8, 2026. Unexpected news regarding key player injuries on either the Rutgers or Wisconsin team would likely cause shifts in probabilities. Changes in weather forecasts, particularly if severe weather is predicted, could also influence trading activity. Late-breaking news about coaching strategies or team morale could also play a role. Finally, significant betting activity on traditional sportsbooks might prompt traders to reassess their positions, leading to price movements in this market. Monitoring these factors can provide valuable insights into potential market shifts.