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According to a Polymarket news release, the new initiative will give users a dedicated place to talk markets, share their picks and trade together directly on Polymarket.
“People are constantly debating what’s going to happen next with their friends and sharing predictions in group chats,” said Travis VanderZanden, who serves as chief growth officer at Polymarket. “With Squads, we’re bringing the conversation and trading together so friends can follow the events they care about and make their predictions in one place.”
Taking a page from a number of humourous Nike commercials during the 1990s, along with a farcical spot aired by the NFL during Super Bowl LIII, Berg injected slapstick comedy into the ad in an apparent attempt to cater to sports fans.
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The announcement came on the same week that Indian Gaming Association leaders met with CFTC Chair Michael Selig. The meetings centred on prediction market-related discussions that IGA Chair David Bean deemed mostly unproductive. On Wednesday, the US Court of Appeals for the Ninth Circuit reversed a lower court’s decision in Blue Lake Rancheria vs Kalshi.
Per the ruling, the Ninth Circuit determined that Kalshi’s sports event contracts amount to unauthorised gaming under the Indian Gaming Regulatory Act (IGRA) when accessed on tribal land.
“Today’s decision reinforces a fundamental principle: when sports wagering occurs on Indian lands, federal Indian gaming law matters,” said Bean on Wednesday.
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An ACMA spokesperson reiterated: “BetStop is an important consumer protection measure, but it only works if wagering companies follow the rules.”
As of January 2027, BetStop will be further promoted as part of a reform package to gambling laws in Australia. Following a statutory review, the government committed to improving system usability and boosting promotional efforts. It is also committed to funding ACMA marketing to support BetStop and recovering operational costs from industry participants.
Additionally, the register will receive AU$28.7 million over four years, with AU$3.2 million ongoing annually beyond that to improve data-matching systems.
