In the wake of successful predictions for the presidential election, cryptocurrency-based betting platform Polymarket disclosed its intentions to reestablish its prediction markets for U.S. users.

What Happened: While talking about the company’s growth strategy in a CNBC interview on Thursday, CEO Shayne Coplan said that having a presence in the U.S. market was “part of the plan” and that they were in a position to be “aggressive around expansion.”

“I want to give a lot of credit to the people who fought the battle to go in and legalize political prediction markets in America,” Coplan stated.

Polymarket has remained offshore since the CFTC penalized it $1.4 million and issued a cease-and-desist order for regulatory violations in January 2022. As such, U.S. residents can’t use the platform.

Kalshi, a rival firm, resumed taking bets on the outcome of congressional elections after an appeals court lifted a ban on the platform’s operations by the CFTC last month.

Since then, other players have thrown their hats in the ring, with Robinhood launching its presidential election event contracts just ahead of the Nov. 5 elections.

See Also: Will MicroStrategy’s $42 Billion Bitcoin Bet Boost MSTR Stock Further?

Why It Matters: Polymarket’s re-entry into the US market comes on the heels of its successful prediction of election outcomes, which, according to Coplan, offered a more accurate view than traditional media.

About $3.6 billion was wagered on the outcome of the presidential race on Polymarket, making it the biggest election prediction market. A fraction of it—about $440 million—was invested in Kalshi for the presidential contract.

One notable bettor, a French ‘Trump Whale’ known as Theo, netted almost $50 million on Polymarket following Trump’s victory.

There were widespread concerns over his significantly larger bets in favor of Trump leading to the election, with many pointing to foreign influence and market manipulation.

However, Theo said that his bets were essentially a challenge to conventional polling methods, and he employed what is known as “the neighbor method” to get his predictions right.

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