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402,751

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2,632

PLATFORM COVERAGE:

5

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Troy vs Utah St.: 1st Half Winner
kalshi

What is the result of Troy vs Utah St.?

Volume:
$40,206

Troy wins 1st Half

 - Kalshi

Troy wins 1st Half - Kalshi

1W

News

Positive

Negative

Neutral

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Vol.

·

Resolved Sep 27, 2026

Closed: Sep 26, 9:03 PM EST

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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

Troy wins 1st Half

View
100%
Yes 100¢No 0¢
100¢
N/A
$24,088
N/A
N/A
$15,640
Settled
Yes
kalshi

Utah St. wins 1st Half

0%
49%
Yes 0¢No 100¢
100¢
N/A
$15,249
N/A
N/A
$9,684
Settled
No
kalshi

Tie 1st Half

0%
11%
Yes 0¢No 100¢
100¢
N/A
$869
N/A
N/A
$833
Settled
No
Total markets: 3

Description

This market tracks the outcome of the first half in an upcoming college football game between Troy and Utah State. It determines which team will lead at halftime or if the half will end in a tie. The result reflects only the scoring performance during the first two quarters of play.

Kalshi

If Utah St. wins the 1st half of the Troy vs Utah St. college football game originally scheduled for Sep 26, 2026, then the market resolves to Yes. If Troy wins the 1st half of the Troy vs Utah St. college football game originally scheduled for Sep 26, 2026, then the market resolves to Yes. If neither team wins the 1st half of the Troy vs Utah St. college football game originally scheduled for Sep 26, 2026, then the market resolves to Yes.

Frequently asked questions

On Kalshi, the dashboard for the Troy vs Utah State 1st half market tracks the current odds, price history, and 24-hour trading volume. You can see how the implied probabilities are shifting as traders buy and sell contracts. Currently, the total volume for this market is $40,206, with $39,989 traded in the last 24 hours. This provides a real-time view of where the crowd believes the outcome of the first half will land, offering insight beyond traditional pre-game analysis. The dashboard is updated continuously to reflect the latest market activity.

Typically, prediction market odds reflect a wisdom-of-the-crowd perspective, often differing from initial sportsbook lines. Sportsbooks set lines to balance action and incorporate a profit margin, while this market aggregates the beliefs of many individual traders. This can lead to prediction market odds being more accurate, especially as the event approaches and more information becomes available. However, sportsbook odds are readily accessible and widely publicized, offering a common benchmark for comparison. Discrepancies can arise due to differing information sources and risk assessments.

On Kalshi, this market is priced through a continuous order book where traders buy and sell contracts representing potential outcomes. The price of a contract reflects the probability of that outcome occurring, as determined by supply and demand. As more people buy contracts for a particular team, the 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 are influenced by the number of active traders and the overall interest in the event. This dynamic pricing mechanism allows for a real-time assessment of expectations.

This market resolves around Sep 27, 2026, with the outcome confirmed once the event is verifiable from credible public reporting. Specifically, the market will settle based on which team is leading at the end of the first half of the Troy vs Utah State game. Official game results from a reputable sports data provider will be used to determine the winning outcome. The platform will then distribute payouts to contract holders based on the final result, reflecting the probabilities established by trading activity leading up to resolution.

Several factors could influence trading activity and shift the odds in this market. Late-breaking news regarding key player injuries or suspensions for either Troy or Utah State would likely have a significant impact. Changes in weather conditions, particularly if they favor one team’s playing style, could also move the market. Additionally, any major shifts in public perception, perhaps driven by pre-game analysis or expert opinions, could influence trader behavior. Finally, large volume trades from individual participants can create short-term price fluctuations.