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Crypto Rock Paper Scissors over WebSockets

Hacker News

Crypto Rock Paper Scissors over WebSockets

Hey HN, I've just launched a new game that I think this community might find interesting. It's a decentralized take on the classic Rock Paper Scissors game, but with a twist – it uses cryptocurrency to place real stakes on the outcomes. No signup necessary, but you will need a browser with native support for Web3 like Opera or Brave, or a crypto wallet with an integrated browser like MetaMask. You may have to wait for a moment to be matched with an opponent due to a small, but growing player base, though refreshing the browser could get you a match more quickly. Features: - *Smart Contracts*: Each game is governed by a transparent smart contract, ensuring fairness and non-repudiation. - *Crypto Integration*: Currently supporting only ETH, but support for custom tokens coming soon. - *Decentralized Verification*: Game outcomes are verified through a decentralized network to prevent tampering. - *WebSockets*: Real-time data exchange notifies you immediately of the outcome of any game: win, lose, draw, or refund. I built this as an experiment to explore game theory and smart contract interactions in a simple, yet familiar setting. I'm curious to see how introducing real stakes with cryptocurrency might change the way people play Rock Paper Scissors. You can try out a Sepolia testnet version here: https://test.crypto-rockpaperscissors.com I'd love to hear your feedback on the game mechanics, smart contract security, UI/UX, and any other aspect of the game. If you're into crypto, gaming, or both, I'd especially appreciate your take on how it could be improved or what features you'd like to see next. Thanks for checking it out!

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85%85% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
AppSumoStrong fit for a featured deal · Strong signals: soon · Missing: plus, platform, intuitive
62%62% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
44%44% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos
16%16% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: web3, crypto, cryptocurrency · Missing: chat, make money, real time
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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