TOTAL VOLUME:
$154.8b
24H VOL:
$277,138,640
24H TRANSACTIONS:
2,984,640,614
OPEN INTEREST:
$1,905,404,943
412,077
Markets across
39,838
events
MATCHED EVENTS:
4,526
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Nov 1, 9:25 AM EST
Kalshi
This group forecasts the outcome of the 2. Bundesliga match between FC St. Pauli and 1. FC Nürnberg on November 1, 2026. Markets exist for St. Pauli winning, Nürnberg winning, and the game ending in a draw.
This event is for the upcoming 2. Bundesliga game, scheduled for Sunday, November 1, 2026 between FC St. Pauli 1910 and 1. FC Nürnberg.
If St. Pauli wins the St. Pauli vs Nuremberg professional Bundesliga 2 soccer game originally scheduled for Nov 1, 2026 after 90 minutes plus stoppage time (does not include extra time or penalties), then the market resolves to Yes. If Nuremberg wins the St. Pauli vs Nuremberg professional Bundesliga 2 soccer game originally scheduled for Nov 1, 2026 after 90 minutes plus stoppage time (does not include extra time or penalties), then the market resolves to Yes. If Tie is the result of the St. Pauli vs Nuremberg professional Bundesliga 2 soccer game originally scheduled for Nov 1, 2026 after 90 minutes plus stoppage time (does not include extra time or penalties), 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. The differing prices on Polymarket and Kalshi for the St. Pauli vs. Nürnberg match can stem from several factors. Each platform has its own user base with varying expertise and information, leading to different interpretations of the teams' strengths and potential performance. Trading volume also plays a role; lower volume on one platform can result in wider bid-ask spreads and less efficient price discovery. Furthermore, the specific market design – the available outcomes and contract specifications – can influence how traders assess and price the event. These factors contribute to the observed price discrepancies.