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Election Bets Drive Fee Spike at Predictions Platform Polymarket
Amid the election excitement, decentralized predictions site Polymarket has become the fourth-highest blockchain project by fees generated.
Updated May 9, 2023, 3:13 a.m. Published Nov 5, 2020, 12:49 p.m.
Decentralized predictions platform Polymarket has passed DeFi protocol SushiSwap to become the fourth-highest blockchain project in terms of fees generated.
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According to Cryptofees, the platform is averaging over $100,000 in daily takings and currently trails behind first-place Bitcoin, Ethereum (second) and DeFi protocol Uniswap (third).
The rise is partly due to excitement around the U.S. election, which has seen Polymarket users taking punts on bets ranging from "Will Trump win the 2020 U.S. presidential election" through to "Which party will win the state of Georgia."
"I think us being top 4 of fee-generating blockchain apps, literally anything blockchain-related, is insanity," said Shayne Coplan, Polymarket founder and CEO. "Just in this election cycle alone we have seen our volume surpass $10 million, which is a lot higher than we expected in such a short time frame."
Since going live on Ethereum's Layer 2 transaction scaling sidechain Matic and a product launch 4.5 months ago, Polymarket's liquidity providers have done "extremely well" in terms of fees generated, according to Coplan.
While competitors such as PredictIt and Electionbettingodds went offline during the vote count on Wednesday Polymarket remained live throughout the entire election process.
"There's a lot of services out there, there's a lot of volume but what are people really paying for?" he said. "What are people really getting the most value out of where they are willing to pay fees to some market operator?"
See also: Predictions Platform Polymarket Raises $4M From Polychain, Naval Ravikant and More
"Polymarket had live markets for a handful of swing states and had accurately forecasted and priced the outcome of a lot of these," Coplan noted. "It stands to show the significance in the social news cycle in market-based data and market-based journalism."
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