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: Oct 24, 3:10 PM EST
Kalshi
This group tracks the outcome of a college football game between San Diego and Dayton scheduled for October 24th. Markets exist to predict the winner, the margin of victory (spreads), and the total points scored.
In the upcoming college football game between San Diego and Dayton, scheduled for October 24 at 12:00PM ET: This market will resolve to "San Diego" if San Diego win the game. This market will resolve to "Dayton" if Dayton 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 for the respective team if they win the college football game originally scheduled for Oct 24, 2026. If the game is postponed but starts within 48 hours of the original time, the market stays open and resolves based on the final 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 San Diego and Dayton, scheduled for October 24 at 12:00PM ET: This market will resolve to "San Diego" if San Diego win the game. This market will resolve to "Dayton" if Dayton 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.
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. Price discrepancies between Polymarket and Kalshi for the San Diego vs. Dayton game can arise from several factors. Each platform attracts a different user base with varying levels of expertise and information. Trading fees and market-making incentives also differ, influencing price formation. Furthermore, the liquidity available on each platform impacts price discovery; lower volume can lead to greater price volatility. Finally, differing interpretations of available information and risk appetite among traders on each platform contribute to the observed price divergence. These factors create a dynamic interplay that results in unique pricing signals on each venue.
Several signals could significantly impact this market. Any news regarding player injuries, changes in coaching strategies, or unexpected team performance could shift trader sentiment. Major upsets in other games involving these teams could also influence predictions. Furthermore, public statements from key players or analysts might sway the market. As the game date approaches, even weather forecasts could play a role, especially if conditions are expected to favor one team over the other. Monitoring these factors will be crucial for understanding potential price movements in this market.