TOTAL VOLUME:
$147.1b
24H VOL:
$114,512,865
24H TRANSACTIONS:
2,782,936,628
OPEN INTEREST:
$1,736,882,761
506,007
Markets across
37,578
events
MATCHED EVENTS:
2,852
PLATFORM COVERAGE:
5
Polymarket:
38%
VS.
Kalshi:
62%
Closed: Oct 3, 6:50 PM EST
Kalshi
This market tracks the total number of 4th down conversions—over or under 0.5—in the upcoming college football game between Ohio State and Iowa. Currently, the consensus probability that Ohio State vs. Iowa: Total 4th Down Conversions will be Over 0.5 is 100.0%. This aggregation combines data from Polymarket and Kalshi, with resolution determined by data reported on https://www.ncaa.com/. Keep an eye on the game itself, scheduled for October 3rd, as the final 4th down conversion count will determine the outcome of this market.
In the upcoming college football game between Ohio State and Iowa, scheduled for October 3 at 3:30PM ET: This market will resolve to "Ohio State" if Ohio State win the game. This market will resolve to "Iowa" if Iowa 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.
On Polymarket, traders set the odds by directly bidding on the probability of different outcomes, while Kalshi uses a different mechanism. 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. This difference in market mechanics can lead to price discrepancies. Additionally, each platform attracts a different user base with varying levels of expertise and information. Trading volume also plays a role; higher volume on one platform can lead to more efficient price discovery. Finally, differing liquidity and the specific incentives offered on each platform can influence how traders value potential outcomes in the Ohio State-Iowa football game.
Several factors could significantly impact this market before the game concludes. Key player injuries on either the Ohio State or Iowa teams would likely cause shifts in probabilities. Unexpected weather forecasts, particularly those predicting adverse conditions, could also influence trading activity. Major news regarding team morale, coaching changes, or significant strategic adjustments could also move the market. Finally, public perception and any late-breaking information released through reputable sports news outlets could all contribute to changes in the odds for the Ohio State-Iowa football game.