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%

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Ohio St. vs Iowa: 4th Quarter Winner
kalshi

What is the result of Ohio St. vs Iowa?

Volume:
$10,842

Iowa

 - Kalshi

Iowa - Kalshi

1W

News

Positive

Negative

Neutral

Hover marker for details

Vol.

·

Resolved Oct 3, 2026

Closed: Oct 3, 7:03 PM EST

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Kalshi

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Join Kalshi and score $25 for your first trade.
Outcome
Trade
Chance %
Price
Spread
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
kalshi

Iowa

View
100%
Yes 100¢No 0¢
—
N/A
$2,413
N/A
N/A
$1,955
Settled
Yes
kalshi

Ohio St.

0%
56%
Yes 0¢No 100¢
—
N/A
$6,976
N/A
N/A
$5,860
Settled
No
kalshi

Tie

0%
Yes 0¢No 100¢
—
N/A
$1,454
N/A
N/A
$1,154
Settled
No
Total markets: 3

Description

This market focuses on determining which team will score more points in the final quarter of an upcoming college football game. It provides a way to speculate on the momentum and performance of the teams specifically in the last quarter of play, rather than the overall game outcome.

Kalshi

If Iowa wins the 4th quarter (excluding overtime) of the Ohio St. vs Iowa college football game originally scheduled for Oct 3, 2026, then the market resolves to Yes. If Ohio St. wins the 4th quarter (excluding overtime) of the Ohio St. vs Iowa college football game originally scheduled for Oct 3, 2026, then the market resolves to Yes. If neither team wins the 4th quarter (excluding overtime) of the Ohio St. vs Iowa college football game originally scheduled for Oct 3, 2026, then the market resolves to Yes.

Frequently asked questions

On Kalshi, the dashboard for the Ohio State vs Iowa game tracks the current odds for each potential winner of the fourth quarter, along with a price history showing how those odds have changed over time. You can also see the 24-hour trading volume, which currently stands at $9,277, and the total volume traded to date, which is $10,842. This information allows you to gauge market sentiment and see how other traders are positioning themselves on who will win the final quarter of the game.

Typically, prediction market odds reflect the wisdom of the crowd and can differ from traditional sportsbook odds. Sportsbooks set lines based on their own models and need to account for a profit margin, while this market is driven purely by traders’ beliefs about the likelihood of each outcome. If a significant discrepancy exists, arbitrage opportunities may arise, where traders can profit by simultaneously betting on both platforms. However, it’s important to remember that both represent probabilities as perceived by different groups.

On Kalshi, this market is priced through a continuous order book where traders buy and sell contracts representing each possible outcome. The price of a contract reflects the market’s implied probability of that outcome occurring. As more traders buy contracts for a particular outcome, its price increases, and the implied probability rises. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. The market’s depth and liquidity, indicated by the trading volume, also influence price discovery, allowing for efficient price adjustments based on new information and changing sentiment.

This market resolves around Oct 3, 2026, with the outcome confirmed once the event is verifiable from credible public reporting. Specifically, the market will settle based on which team is winning at the end of the fourth quarter of the Ohio State vs Iowa game. The official game results, as reported by a reputable sports news source, will be used to determine the winning team and finalize the market’s outcome. Traders will then be paid out according to their positions.

Several factors could significantly impact this market. Any news regarding key player injuries for either Ohio State or Iowa would likely cause shifts in the odds. Unexpected changes in weather conditions, such as heavy rain or strong winds, could also influence the game’s dynamics and affect trading activity. Furthermore, in-game performance during the first three quarters, including scoring drives and defensive stops, will likely drive significant movement as traders react to the unfolding events and adjust their predictions.