TOTAL VOLUME:
$154.3b
24H VOL:
$228,458,490
24H TRANSACTIONS:
2,984,028,936
OPEN INTEREST:
$1,879,276,037
410,833
Markets across
40,345
events
MATCHED EVENTS:
4,363
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Oct 3, 8:41 PM EST
Kalshi
This market tracks which team will lead at the end of the first half in an upcoming college football game between UTSA and Rice. It focuses solely on the scoring performance during the first 30 minutes of play, ignoring the final game result. The outcome depends on whether Rice, UTSA, or neither team (in case of a tie) holds the advantage at halftime.
If Rice wins the 1st half of the UTSA vs Rice college football game originally scheduled for Oct 3, 2026, then the market resolves to Yes. If UTSA wins the 1st half of the UTSA vs Rice college football game originally scheduled for Oct 3, 2026, then the market resolves to Yes. If neither team wins the 1st half of the UTSA vs Rice college football game originally scheduled for Oct 3, 2026, then the market resolves to Yes.
Typically, prediction market odds reflect the wisdom of the crowd and can differ from traditional sportsbook odds. Sportsbooks often set initial lines to balance action, while this market’s prices are driven purely by supply and demand among traders who are incentivized to be accurate. If a significant discrepancy exists, it may indicate that the market believes a sportsbook has mispriced a particular outcome. However, it’s important to remember that both represent probabilities as perceived by different groups, and neither guarantees the actual result of the UTSA vs Rice game. These differences can present opportunities for arbitrage.
On Kalshi, this market is priced through a continuous order book where traders bid to buy 'yes' contracts (believing an outcome will happen) and ask to sell 'no' contracts (believing it won’t). On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. The price of a contract represents the probability of that outcome occurring, scaled to a value between 0 and 100. As more traders buy 'yes' contracts to Rice winning the first half, for example, the price of those contracts will increase, and the price of 'no' contracts will decrease. This dynamic pricing mechanism reflects the collective intelligence of the market participants.
Several factors could influence the price movement in this market. News regarding key player injuries to either UTSA or Rice would likely have a significant impact. Changes in weather forecasts, particularly if they suggest adverse playing conditions, could also shift the odds. Unexpected announcements about coaching strategies or team morale might also cause traders to reassess their probabilities. Finally, any significant betting activity—a large volume of contracts being bought or sold—could quickly move the price, reflecting a change in market sentiment regarding the UTSA vs Rice first half outcome.