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 15, 7:49 AM EST
Kalshi
This group resolves based on the outcome of a single NPB (Nippon Professional Baseball) game between the Orix Buffaloes and the Fukuoka SoftBank Hawks, scheduled for September 15th. The market determines which team wins the game, with a 50-50 split in the event of a tie or cancellation without a make-up game.
In the upcoming NPB game, scheduled for September 15 at 5:00AM ET: If the Orix Buffaloes win, the market will resolve to "Orix Buffaloes". If the Fukuoka SoftBank Hawks win, the market will resolve to "Fukuoka SoftBank Hawks". If the game is postponed, this market will remain open until the game has been completed. If the game is canceled entirely, with no make-up game, or ends in a tie, this market will resolve 50-50. The primary resolution source will be official information from the NPB. A consensus of credible reporting may also be used.
If Fukuoka Hawks wins the Fukuoka Hawks vs Orix Buffaloes Japan NPB game originally scheduled for Sep 15, 2026 at 5:00 AM EDT, then the market resolves to Yes. If Orix Buffaloes wins the Fukuoka Hawks vs Orix Buffaloes Japan NPB game originally scheduled for Sep 15, 2026 at 5:00 AM EDT, then the market resolves to Yes.
Prediction market odds, like those found in this market, often reflect the collective wisdom of a diverse group of participants, potentially offering a different perspective than traditional sportsbooks. Sportsbooks set lines based on their own models and aim to balance action on both sides, while prediction markets allow traders to freely express their beliefs. This can lead to discrepancies, especially when public sentiment strongly deviates from expert analysis. However, both types of odds ultimately aim to accurately predict the probability of an event occurring, and both can be valuable tools for informed decision-making.
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. Differences in pricing between Polymarket and Kalshi often arise due to variations in trader demographics, market design, and available liquidity. Polymarket may attract a different class of traders than Kalshi, leading to differing risk assessments and, consequently, price discrepancies. Additionally, the specific rules and fee structures of each platform can influence trading behavior. While both platforms address the same underlying event, these factors contribute to the observed price variations in this market. These differences are natural and reflect the dynamic nature of prediction markets.