TOTAL VOLUME:
$134.2b
24H VOL:
$130,522,377
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,438,389,636
404,028
Markets across
30,214
events
MATCHED EVENTS:
2,681
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
Closed: Sep 13, 12:32 AM EST
Kalshi
This group forecasts the halftime result of a soccer match between Phoenix Rising FC and FC Tulsa. Markets exist for Phoenix Rising leading, Tulsa leading, or a draw at halftime, based on the first 45 minutes of play plus stoppage time.
In the upcoming USL Championship game between Phoenix Rising FC and FC Tulsa, scheduled for September 12, 2026 at 10:00 PM ET: This event contains halftime result markets for home, draw, and away outcomes within the first 45 minutes of regular play plus stoppage time.
The market resolves based on the outcome of the Phoenix Rising vs Tulsa professional USL Championship soccer game scheduled for September 12, 2026. A win for Phoenix Rising within 90 minutes plus stoppage time (excluding extra time or penalties) resolves the "Phoenix Rising" market to Yes. A win for Tulsa under the same conditions resolves the "Tulsa" market to Yes. If the game ends in a tie after 90 minutes plus stoppage time, the "Tie" market resolves to Yes. If the match is cancelled or rescheduled to more than 48 hours beyond the original date, all markets will resolve to a fair price as per the rules. The markets exclusively consider the result after regular time and do not account for extra time or penalty shootouts.
Polymarket and Kalshi can show different implied probabilities for the same outcome because of liquidity, fee structure, participant mix, and how each venue defines the contract. Prices on Polymarket and Kalshi can diverge due to several factors. Each platform has a different user base with varying levels of expertise and information. Trading volume also plays a role; higher volume typically leads to more efficient price discovery. Furthermore, the specific mechanisms for setting prices – order books versus automated market makers – can influence how quickly and to what extent prices react to new information. Finally, differing risk appetites and interpretations of available data among traders on each platform contribute to price discrepancies in this market.