TOTAL VOLUME:
$154.3b
24H VOL:
$228,458,490
24H TRANSACTIONS:
2,984,028,936
OPEN INTEREST:
$1,879,276,037
410,833
Markets across
40,345
events
MATCHED EVENTS:
4,363
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Penn St.
all
3 markets
Kalshi
Polymarket
Predict
consensus
News
Positive
Negative
Neutral
Hover marker for details
Vol.
·
Resolves Nov 2, 2026
Time left: 06h:02m:21s
$
This event group concerns the November 2nd, 2026 NCAA Men's Basketball game between the Canisius Golden Griffins and the Penn State Nittany Lions. The markets ask who will win the game, with provisions for postponed or canceled games.
This event is for the CBB game between Canisius Golden Griffins and Penn State Nittany Lions on November 2 at 7:30PM ET. 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.
Resolution depends on the winner of the Canisius vs Penn St. men's college basketball game set for November 2, 2026. If the game is postponed but starts within 48 hours of the 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, both markets resolve to a fair price. Kalshi emphasizes it is not affiliated with the NCAA, and all trademarks are property of their respective owners.
This event is for the CBB game between Canisius Golden Griffins and Penn State Nittany Lions on November 2 at 7:30PM ET. 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 for the Canisius vs. Penn State game, often differ from traditional sportsbook odds due to the underlying mechanisms. Sportsbooks set odds to ensure profit, incorporating a margin, while prediction markets are driven by genuine buyer and seller activity. This market reflects the collective intelligence of traders, who are incentivized to accurately assess probabilities. Consequently, prediction markets can sometimes offer more accurate forecasts, especially when there is significant trading volume. The difference between these odds can also reveal public sentiment and potential biases not captured by sportsbooks.
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. Prices on Polymarket and Kalshi for the Canisius vs. Penn State game may diverge due to several factors. Each platform has its own user base, trading rules, and liquidity levels. Differences in these factors can lead to varying price discovery processes. For example, Polymarket might attract more sophisticated traders, while Kalshi could have a broader range of participants. Furthermore, the volume traded on each platform influences price stability and responsiveness to new information. These differences can create temporary discrepancies in the perceived probabilities of each outcome.
This market resolves around Nov 3, 2026, with the outcome confirmed once the event is verifiable from credible public reporting. The result will be determined by the official outcome of the Canisius Golden Griffins versus Penn State Nittany Lions game, as reported by official sources. Traders will be able to see the final result reflected in the market’s settlement data, confirming the winning outcome. This allows for a transparent and verifiable record of the prediction market’s accuracy.
Several signals could significantly impact this market before Nov 3, 2026. Any news regarding injuries to key players on either the Canisius or Penn State teams would likely cause shifts in the probabilities. Changes in team performance leading up to the game, such as unexpected wins or losses, could also influence trader sentiment. Furthermore, weather conditions on game day, or any major announcements related to the teams’ strategies, could all contribute to movement in the market. Monitoring these factors will be crucial for understanding how the predictions evolve as the event draws closer.