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What is Heroic Spins?
Two operators alone – Kalshi and Polymarket – topped the combined $1 billion mark in NFL trading activity over the first six days of Week 1, according to numerous measures this week. During the period, Kalshi recorded NFL volume of $983.4 million, according to DeFi Rate, earning the pole position by a large margin. Mahomes and the Kansas City Chiefs thrashed the Denver Broncos 31-10 on Monday Night Football, capping the largest week for prediction markets ever.
Even before the primetime matchup in Kansas City, it became abundantly clear that the industry would shatter previous marks for weekly activity. The AFC West showdown bolstered the already robust totals. Overall, volume for the week hit a record $15.9 billion, according to Bank of America, up 16% from a week earlier.
The pure-play prediction market-operators, Polymarket and Kalshi, emerged from Week 1 as the clear winners. On one hand, Kalshi’s market share lead narrowed over its competitors, falling to 82% for the week ended 13 September, down from 86% a week earlier.
What is Heroic Spins?
“Our investigation revealed certain clients had allowed for Evolution’s game content to be provided on their online gaming websites in clear violation of their contracts, which expressly prohibited such game play in specified regions,” the report states.
Spectrum blames Evolution’s “ineffective complaince procedures”, noting these activities appeared to go undetected by the supplier.
“In our judgment, Evolution’s ineffective compliance procesures have allowed these situations to develop and therefore need prompt reevaluation and enhancement in order to comply fully with the terms of the contracts,” the report reads.
What is Heroic Spins?
Large and demanding portfolios were highlighted as a key challenge, with 64% of managers overseeing 100 or more VIPs, while one in five managed more than 500.
The report highlighted the intense workload by estimating that a manager looking after 250 players would have roughly 100 seconds to commit to each player each day if their time was split equally. Data quality and fragmentation were also issues.
Grygorenko emphasised that prioritisation was the key to adapting these portfolio sizes.
