TOTAL VOLUME:
$134.1b
24H VOL:
$113,466,932
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,423,222,590
402,751
Markets across
30,217
events
MATCHED EVENTS:
2,632
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
Closed: Sep 24, 4:30 PM EST
Kalshi
This group resolves based on the outcome of a Euroleague basketball game between Saski Baskonia and Olympiacos B.C. The market determines which team wins the game, with a 50-50 split if the game is canceled without a reschedule.
In the upcoming Euroleague basketball game, scheduled for September 24 at 2:30PM ET: If the Saski Baskonia win, the market will resolve to "Saski Baskonia". If the Olympiacos B.C. win, the market will resolve to "Olympiacos B.C.". 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, this market will resolve 50-50.
If Baskonia Vitoria-Gasteiz wins the BC Olympiakos Piraeus vs Baskonia Vitoria-Gasteiz men's professional EuroLeague basketball game originally scheduled for Sep 24, 2026 at 2:30 PM EDT, then the market resolves to Yes. If BC Olympiakos Piraeus wins the BC Olympiakos Piraeus vs Baskonia Vitoria-Gasteiz men's professional EuroLeague basketball game originally scheduled for Sep 24, 2026 at 2:30 PM EDT, then the market resolves to Yes.
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. Price discrepancies between Polymarket and Kalshi for the Baskonia vs. Olympiacos game can arise due to several factors. Each platform has its own user base, trading incentives, and liquidity, which can influence price discovery. Different levels of participation and risk appetite on each venue can also lead to divergent opinions reflected in the market prices. Furthermore, the specific market structures and fee schedules on Polymarket and Kalshi may contribute to these differences, even when tracking the same underlying event. These variations are normal in decentralized prediction markets.
Several factors could influence this market before resolution. Any news regarding player injuries, changes in team lineups, or coaching decisions could significantly shift probabilities. Unexpected performance in preceding games or shifts in public perception of each team’s form could also impact trading activity. Major upsets in related basketball events or broader sporting news might also indirectly affect sentiment. Monitoring these signals will be key to understanding potential price movements in this market.