Simple coop game to demonstrate Club (decentralized networking) library

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Few weeks back I posted here a link to Club library I've been working on. https://github.com/inetic/club It is a library for decentralized networking designed (not only) for computer games with the main goal to avoid paying for game servers. People asked me whether it can be used for real time multiplayer games and since there wasn't a game using it already I hesitated to give a yes/no answer. Since then I started to work on this little game. It is a space shooter game with ugly graphics with the main goal to showcase Club. https://play.google.com/store/apps/details?id=com.sicoop Given that Club is still in its alpha stage, I think the result is good. When players connect using WiFi I was able to play with 4 players simultaneously. I had problems when I connected through my mobile carries because my mobile internet is slow and Club currently lacks a congestion control mechanism.

Visit product View on Hacker NewsJul 12, 2016

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting

76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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TrustMRRFits verified-revenue profile · Strong signals: apps, google · Missing: mobile apps, ios, personal

61%61% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: google, apps, computer · Missing: mac, agents, macos

46%46% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: real time · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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