TOTAL VOLUME:
$54.4b
24H VOL:
$224,446,576
24H TRANSACTIONS:
531,611,392
OPEN INTEREST:
$1,198,377,813
501,416
Markets across
13,642
events
MATCHED EVENTS:
1,816
PLATFORM COVERAGE:
4
Polymarket:
51%
VS.
Kalshi:
49%
SHL: Brynaes vs. HV 71
Volume:
$3,669
Outcome
Chance %
Price
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
Trade
Description
This event group covers the SHL (Swedish Hockey League) match between Brynaes and HV 71 scheduled for March 14, 2026. The markets resolve based on which team wins the game, with special handling for postponements, cancellations, and shootouts.
PredictionHero - Resolution Divergence Alerts (RDA)
Divergence Detected
Issue:
Kalshi's resolution criteria logically contradicts itself by stating both possible match outcomes (Brynas IF wins OR HV71 wins) resolve to Yes, making the market fundamentally unresolvable. Polymarket provides coherent binary logic.Hero Tip:
Avoid trading on Kalshi until the resolution criteria is corrected. The market cannot settle properly as written. Polymarket's logic is sound: trade there if you have conviction on the match outcome.Critical Divergence Points:
- Polymarket: Binary outcome resolution: Brynaes win resolves to Brynaes, HV 71 win resolves to HV 71. Postponements keep market open; cancellations resolve 50-50. Shootout adds one goal to winner's score for resolution purposes.
- Kalshi: Logical contradiction: Both "If Brynas IF wins" and "If HV71 wins" are stated to resolve to Yes, creating an impossible resolution scenario where the market cannot distinguish between outcomes.
Our PredictionHero Resolution Divergence Alerts (RDA) are there to help users identify potential differences across platforms. They do not replace or supersede the official rules and description of any prediction market. Users are solely responsible for reviewing and understanding the applicable rules and resolution criteria before placing any trade or bet. If you notice a potential inconsistency, discrepancy, or error in an alert, please report it to our team so we can review and improve the accuracy of our data.
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