TOTAL VOLUME:
$154.4b
24H VOL:
$230,589,906
24H TRANSACTIONS:
2,984,028,936
OPEN INTEREST:
$1,885,293,300
410,482
Markets across
40,213
events
MATCHED EVENTS:
4,340
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Oct 3, 7:08 PM EST
Polymarket
Exact margin markets for Ohio vs. Kent State.
Exact margin markets for Ohio vs. Kent State.
On Polymarket, this market is priced through a continuous auction mechanism where traders buy and sell shares representing different point differentials in the Ohio-Kent State game. The price of each share reflects the market’s probability assessment of that specific margin occurring. On Polymarket, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. As more traders participate and new information becomes available, the prices adjust accordingly, providing a real-time indication of expectations. The market’s efficiency is driven by the incentive for traders to accurately predict the outcome, as profitable trades are rewarded.
This market resolves around Oct 3, 2026, with the outcome confirmed once the event is verifiable from credible public reporting. The final point differential between Ohio and Kent State, as determined by official game statistics, will be used to determine the winning shares. The market will settle to 100% for the share corresponding to the exact final margin. Traders holding shares in the correct margin will receive a payout, while those holding shares in incorrect margins will receive nothing. It’s important to monitor official sources for the final result.
Several signals could significantly impact this market. Any news regarding key player injuries for either Ohio or Kent State would likely cause shifts in the odds. Unexpected changes in coaching strategies or team performance during upcoming games could also influence trader sentiment. Furthermore, weather forecasts for the game day could play a role, particularly if adverse conditions are expected. Publicly available analysis from sports analysts and updated power rankings may also contribute to price movements as traders incorporate new information into their predictions.