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 25, 11:02 PM EST
Kalshi
This market tracks the Over/Under 3.5 goals outcome for the Liga MX soccer match between Atlante FC and CF Monterrey, aggregating data from Polymarket and Kalshi. Currently, the consensus probability of Atlante FC vs. CF Monterrey: O/U 3.5 reaching over 3.5 goals is 100.0%. Resolution will be based on data reported at https://ligamx.net/cancha/partidos. Keep an eye on the match itself, as the final whistle on September 26, 2026 will determine the total goals scored and thus resolve this market.
More markets for the Liga MX game, scheduled for September 25 at 9:00 PM ET.
All markets resolve based on the total number of goals scored in the Atlante vs Monterrey professional Liga MX soccer game scheduled for September 25, 2026, after 90 minutes plus stoppage time. Extra time and penalty kicks are excluded from goal counts. A 'Yes' outcome occurs if the total goals exceed the specified threshold (0.5, 1.5, 2.5, 3.5, 4.5, or 5.5) for each respective market. Kalshi disclaims any official affiliation with the governing league, and all trademarks remain property of their respective owners.
Prices on Polymarket and Kalshi can diverge due to several factors. Each platform has its own user base, trading dynamics, and fee structure, all of which can influence price discovery. 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. Furthermore, differences in liquidity – the amount of volume traded – can also contribute to price discrepancies. A smaller market on one platform may be more susceptible to price swings from individual trades. The differing interfaces and user experiences on each platform may also attract traders with different risk tolerances and predictive models, leading to varied valuations of the same event.