TOTAL VOLUME:

$154.8b

24H VOL:

$277,138,640

24H TRANSACTIONS:

2,984,640,614

OPEN INTEREST:

$1,905,404,943

412,077

Markets across

39,838

events

MATCHED EVENTS:

4,526

PLATFORM COVERAGE:

5

Polymarket:

37%

VS.

Kalshi:

63%

BETA
Dashboards
Tour
All
Sports
Texas vs Oklahoma: Overtime
kalshi

What is the result of Texas vs Oklahoma?

Volume:
$123,385

Game goes to overtime

 - Kalshi

Game goes to overtime - Kalshi

1W

News

Positive

Negative

Neutral

Hover marker for details

Vol.

·

Resolved Oct 10, 2026

Closed: Oct 10, 7:39 PM EST

kalshi

Kalshi

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

Game goes to overtime

View
0%
3%
Yes 0¢No 100¢
—
N/A
$123,385
N/A
N/A
$53,034
Settled
No
Total markets: 1

Description

In the Texas vs Oklahoma college football game set for October 10, 2026, if neither team leads at the conclusion of regulation play, the match will continue into overtime. This extra time allows each team further chances to score and decide the winner through additional periods of play.

Kalshi

If at least 1 overtime period is played in the Texas vs Oklahoma college football game originally scheduled for Oct 10, 2026, then the market resolves to Yes.

Frequently asked questions

On Kalshi, the dashboard for the Red River Showdown overtime market tracks the current odds of the game going to overtime, as well as the price history showing how those odds have changed over time. You can also see the 24-hour trading volume, which currently stands at $97,780, and the total volume traded to date, which is $123,385. This provides a real-time view of how traders are assessing the likelihood of overtime in this highly anticipated matchup. The top outcome currently favored by traders is a game going to overtime.

Typically, prediction market odds offer a distinct perspective compared to traditional sportsbooks. Sportsbooks often incorporate a 'vig' or commission into their odds, representing their profit margin, while this market reflects the collective judgment of traders. If a significant difference emerges between this market and sportsbook odds, it could indicate disagreement about the true probability of overtime, potentially stemming from differing information or analytical approaches. This divergence can be a valuable signal for informed bettors, though it's important to consider the volume traded in this market as well.

On Kalshi, this market is priced using a continuous double auction, meaning traders buy and sell contracts representing the probability of overtime. As more traders believe overtime is likely, the price of contracts increases, and vice versa. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. The price reflects the collective wisdom of the crowd, and changes rapidly based on new information and sentiment. This dynamic pricing mechanism allows for a highly liquid and efficient market, providing a real-time assessment of the event's probability.

This market resolves around Oct 10, 2026, with the outcome confirmed once the result of the Texas vs Oklahoma football game is verifiable from credible public reporting. Specifically, the market will determine whether the game went to overtime based on the official game results. The resolution will be based on the official game statistics and records, ensuring a transparent and accurate outcome. Traders will then be able to claim their winnings or adjust their strategies for future events.

Several factors could significantly influence this market before the game concludes. Any news regarding key player injuries for either Texas or Oklahoma would likely cause a shift in the odds. Changes in weather forecasts, particularly if severe weather is predicted, could also impact the market, as weather can affect game strategy and scoring. Furthermore, late-breaking news about coaching decisions or team morale could influence trader sentiment and move the market. Public polling data and expert analysis, while not directly reflected in the market, could also indirectly affect trading activity.