The growing market for sports betting has increased the need for a safe, sustainable, legal revenue model. Better Fan has developed an innovative sports betting platform that combines a Web3-based infrastructure with the play-to-earn (P2E) concept.
Better Fan CEO Metin Durgun highlights the platform’s “closed economy” model: “Better Fan’s gamified platform promises to revolutionize the world of sports betting,” he said, noting that 47 million Americans placed at least one bet during the last NFL season , according to American Gaming Association data.
The world’s first Web3 based gamified betting platform, Better Fan aims to introduce the idea of legal, ethical and sustainable betting to the global sports betting market. It “gamifies” the sports betting ecosystem, reducing gamers’ potential losses by letting them place bets without using fiat currencies or crypto.
Durgun distinguished: “On Web2 based platforms, people use real money to place their bet. But if they lose, their whole effort is lost.”
Since Better Fan users don’t wager anything of value, they can only lose their daily bets – which are refreshed every 24 hours. Each user’s NFT-based fan cards determine the wagering amounts and daily wagering limits. Users can upgrade these NFTs, increasing their card rates.
If bets are successful, users have been rewarded with Better Fan’s BTB (Better Than Bet) utility tokens. These can be used for in-game activities and users can exchange them for USDT directly in-game.
“Better Fan’s gamification approach is based on the P2E model,” explains Durgun. “It prevents illegal activities because it doesn’t leave ‘hard money’ on the platform.”
The sports betting market continues to grow
Research indicates that the global sports betting market will grow at nearly 12% annually and reach a total value of $178 billion by 2030.
“With traditional betting, only a small portion of this revenue is shared with sports clubs,” says Durgun. “But with Better Fan, in-game taxes and fees are collected in a common pool, creating a much fairer distribution.”
