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%
Rhode Island
- Kalshi
Rhode Island - Kalshi
1W
News
Positive
Negative
Neutral
Hover marker for details
Vol.
·
Resolves Nov 3, 2026
Time left: 01d:01h:31m
$
This event group concerns the outcome of a college basketball game between Holy Cross and Rhode Island scheduled for November 3rd. Markets ask who will win the game, with provisions for postponed or canceled games.
This event is for the CBB game between Holy Cross Crusaders and Rhode Island Rams on November 3 at 7:00PM 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.
The market resolves based on the winner of the Holy Cross vs. Rhode Island men’s college basketball game scheduled for November 3, 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 official final result. Should the game be cancelled or fail to start within this 48-hour window, both markets 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.
This event is for the CBB game between Holy Cross Crusaders and Rhode Island Rams on November 3 at 7:00PM 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, often differ from traditional sportsbook odds due to the mechanisms behind price discovery. Sportsbooks set odds based on internal models and aim to balance action on both sides, incorporating a profit margin. In contrast, this market relies on the wisdom of the crowd, where prices are driven by traders buying and selling based on their own information and analysis. This can lead to more accurate probabilities, especially when significant information isn't yet reflected in sportsbook lines. However, liquidity differences can also create discrepancies.
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 may diverge due to several factors. Each platform has its own user base, trading rules, and fee structure, influencing supply and demand. Furthermore, differing levels of liquidity can lead to price discrepancies, as smaller volumes are more susceptible to individual trades. Currently, Polymarket currently favors Holy Cross Crusaders vs. Rhode Island Rams at 4.0%, while Kalshi leans toward Rhode Island wins at 93.0%. These differences highlight the independent nature of each market and the diverse perspectives of their traders.
This market resolves around Nov 4, 2026, with the outcome confirmed once the event is verifiable from credible public reporting. The final result of the Holy Cross vs. Rhode Island game will be used to determine the winning outcome in this market. The resolution will be based on the official game results as reported by a trusted sports data source. Traders should monitor official sources for updates as the resolution date approaches, ensuring they are aware of the final outcome and how it impacts their positions.
Several signals could significantly impact this market before it resolves around Nov 4, 2026. Key player injuries or suspensions on either the Holy Cross or Rhode Island teams would likely cause shifts in probabilities. Unexpected news regarding team coaching strategies or internal dynamics could also influence trading activity. Finally, any significant changes in public perception or expert analysis regarding the teams' chances of winning would be reflected in the market prices. These factors contribute to the dynamic nature of prediction markets, allowing traders to react to new information as it becomes available.