TOTAL VOLUME:

$154.3b

24H VOL:

$219,029,434

24H TRANSACTIONS:

2,984,028,936

OPEN INTEREST:

$1,869,293,526

411,051

Markets across

40,408

events

MATCHED EVENTS:

4,377

PLATFORM COVERAGE:

5

Polymarket:

37%

VS.

Kalshi:

63%

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Texas A&M vs Missouri: 1st Quarter Winner
kalshi

What is the result of Texas A&M vs Missouri?

Volume:
$40,243

Texas A&M

 - Kalshi

Texas A&M - Kalshi

1W

News

Positive

Negative

Neutral

Hover marker for details

Vol.

·

Resolved Oct 10, 2026

Closed: Oct 10, 12:47 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

Texas A&M

View
100%
63%
Yes 100¢No 0¢
—
N/A
$16,222
N/A
N/A
$10,947
Settled
Yes
kalshi

Missouri

0%
45%
Yes 0¢No 100¢
—
N/A
$16,643
N/A
N/A
$10,284
Settled
No
kalshi

Tie

0%
Yes 0¢No 100¢
—
N/A
$7,378
N/A
N/A
$6,914
Settled
No
Total markets: 3

Description

This market tracks which team will lead after the first quarter of a college football game between Texas A&M and Missouri. It focuses solely on the scoring during the initial 15 minutes of play, ignoring the rest of the game. The outcome depends on whether Texas A&M, Missouri, or neither team (in case of a tie) scores more points in that period.

Kalshi

If Missouri wins the 1st quarter of the Texas A&M vs Missouri college football game originally scheduled for Oct 10, 2026, then the market resolves to Yes. If Texas A&M wins the 1st quarter of the Texas A&M vs Missouri college football game originally scheduled for Oct 10, 2026, then the market resolves to Yes. If neither team wins the 1st quarter of the Texas A&M vs Missouri college football game originally scheduled for Oct 10, 2026, then the market resolves to Yes.

Frequently asked questions

On Kalshi, the dashboard for the Texas A&M vs Missouri game tracks the current odds of each team winning the first quarter, the total volume traded on this market – currently $40,243 – and the 24-hour trading volume, which is $29,752. You can also see a price history chart illustrating how the probabilities have shifted over time. This allows traders to monitor market sentiment and identify potential opportunities as people react to news and analysis regarding the matchup. The dashboard provides a real-time view of where the crowd believes the initial advantage lies.

Typically, prediction market odds reflect the wisdom of the crowd, often differing from initial sportsbook lines due to the influence of public opinion and specialized knowledge. Sportsbooks set lines to balance action and ensure profit, while this market is driven purely by individuals wagering on their beliefs about the outcome. Over time, prediction market prices tend to be more accurate than traditional point spreads, as they incorporate a wider range of information and are continuously updated based on trading activity. It’s common to see discrepancies, especially before significant events or news breaks.

This market resolves around Oct 10, 2026, with the outcome confirmed once the event is verifiable from credible public reporting. The team leading after the first quarter of the Texas A&M vs Missouri game will be declared the winner of this market. Official game results from a reputable sports source will be used to determine the winning team. Traders will be able to see the final result reflected in their account balances shortly after the conclusion of the first quarter and official confirmation of the score. The outcome will be based on the official game statistics.

Several factors could influence the trading activity in this market. Any news regarding injuries to key players on either the Texas A&M or Missouri teams would likely cause significant price movement. Changes in weather forecasts, particularly if they suggest conditions favorable to one team's playing style, could also impact the market. Additionally, late-breaking analysis from sports commentators or unexpected lineup changes could shift trader sentiment. Public perception, fueled by social media or pre-game polls, can also contribute to price fluctuations as traders react to evolving information.