TOTAL VOLUME:
$134.2b
24H VOL:
$134,145,987
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,441,166,947
406,422
Markets across
30,383
events
MATCHED EVENTS:
2,688
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
Closed: Aug 20, 6:40 PM EST
Polymarket
This event group covers various betting markets for the UEFA Europa Conference League match between Heart of Midlothian FC and SK Rapid Wien, including spread bets, over/under totals, and team-specific goal scoring outcomes across different halves and overall match.
More markets for the UEFA Europa Conference League game, scheduled for August 20 at 2:45 PM ET.
The event resolves based on the margin of victory for either SK Rapid or Heart of Midlothian during the 90 minutes of play plus any stoppage time, excluding extra time and penalty kicks. Specific thresholds define whether SK Rapid must win by more than 1.5 or 2.5 goals, or Heart of Midlothian must win by more than 1.5 or 2.5 goals for the market to resolve to Yes. The match is the professional Conference League game originally scheduled for August 26, 2026. Kalshi disclaims any official affiliation with the governing league, and all trademarks remain the property of their respective owners.
Prediction market odds often differ from traditional sportsbook lines because they reflect trader sentiment rather than set odds from bookmakers. In this market, the probability percentages you see incorporate real-time betting activity and can shift quickly as new information emerges. Sportsbook odds may include adjustments for handling fees or market controls, while prediction markets price outcomes purely through volume and consensus. Comparing both can reveal differences in implied probabilities and potential value opportunities.
On Polymarket, this market is priced through continuous trading where users bet directly on outcomes, creating rapid price adjustments based on betting patterns. 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. Meanwhile, Kalshi may use different liquidity models or user bases that respond to news and analysis at varying speeds. These differences in user activity, available liquidity, and market design can lead to varying probability assessments. Additionally, each platform might have unique listing timelines or promotional events that temporarily skew prices. The combination of these factors often results in divergent odds across venues for the same underlying question.
Injuries, weather conditions, and lineup changes can all shift expectations and move this market. Key moments like pre-match announcements, recent form of players, or even shifts in betting volume on either platform may cause odds to swing. As the match nears, any last-minute updates — such as a star player being ruled out or a tactical change — will likely create rapid adjustments in probability estimates across venues.