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 2, 8:03 AM EST
Kalshi
This event group covers the outcome of the Shimizu S-Pulse vs. FC Tōkyō soccer match scheduled for September 2, 2026, focusing on win/draw outcomes within regular play plus stoppage time.
This event is for the upcoming Japan J. League game, scheduled for Wednesday, September 2, 2026 between Shimizu S-Pulse and FC Tōkyō.
The event resolves based on the result of the Shimizu vs Tokyo professional Japan J1 League soccer match scheduled for September 2, 2026, after 90 minutes plus stoppage time. If Shimizu wins the match within regulation time, the 'Shimizu' market resolves to Yes. If Tokyo wins the match within regulation time, the 'Tokyo' market resolves to Yes. If the match ends in a tie after regulation time, the 'Tie' market resolves to Yes. If the game is cancelled or rescheduled to more than 48 hours beyond the original date, all markets will resolve to a fair price in accordance with the platform's rules. The event exclusively considers the result after regular time and does not account for extra time or penalty shootout outcomes.
Prediction market odds often reflect sharper, crowd-sourced insights than traditional sportsbook lines, especially for niche matchups like this one. While sportsbooks may incorporate broader public sentiment and adjusted margins, prediction markets price outcomes based on direct trader participation, sometimes revealing tighter spreads or different favorites. The gap between the two can hint at where informed traders are placing their confidence.
On Polymarket and Kalshi, pricing can vary due to differences in user bases, liquidity depth, and market design. 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. For example, one venue might attract more local fans or data-driven traders, skewing its odds. Additionally, each platform’s fee structure and order flow can influence how quickly prices adjust, leading to temporary mispricings between the two.