TOTAL VOLUME:
$154.7b
24H VOL:
$279,496,801
24H TRANSACTIONS:
2,984,640,614
OPEN INTEREST:
$1,923,931,766
416,910
Markets across
40,107
events
MATCHED EVENTS:
4,571
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Oct 3, 6:45 PM EST
Kalshi
This market tracks the outcome of various bets related to the Old Dominion versus Georgia State college football game. Currently, the aggregated probability of Old Dominion vs. Georgia State: Total 4th Down Conversions O/U 0.5 resolving to ‘Yes’ is 100.0%, with an identical 100.0% probability for Old Dominion vs. Georgia State: 4Q Moneyline. These probabilities are an aggregate of Polymarket and Kalshi, and will resolve based on data from https://www.ncaa.com/. Keep an eye on the game itself, scheduled for October 3rd, as the final score will determine the outcome of these markets.
In the upcoming college football game between Old Dominion and Georgia State, scheduled for October 3 at 3:30PM ET: This market will resolve to "Old Dominion" if Old Dominion win the game. This market will resolve to "Georgia State" if Georgia State 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 the specified team wins the college football game originally scheduled for Oct 3, 2026. If the game is postponed but begins within 48 hours of its originally scheduled start time, the market will remain open and resolve based on the official final result. If the game is cancelled or not started within 48 hours of its originally scheduled start, the market will resolve to a fair price. Kalshi is not affiliated, associated, authorized, endorsed by, or in any way officially connected with the NCAA. All trademarks, logos, and brand names are the property of their respective owners.
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 user base, market design, and trading fees can cause price discrepancies between Polymarket and Kalshi for the Old Dominion vs. Georgia State game. Each platform attracts different types of traders with varying levels of expertise and risk tolerance. Additionally, the specific rules and liquidity provisions on each platform can influence how prices are formed. For example, tighter spreads on one platform may attract more arbitrage activity, leading to faster price convergence, while other platforms may exhibit more volatility due to lower volume.