Multiplayer Voronoi

Hacker News

Multiplayer Voronoi

A multiplayer hommage to Jean-Michel Sanejouand's Jeu de Topo (1963), a game with no winner or loser where partners arrange stones until both points of view are satisfied. Here, stones become colored points in a game based on Voronoi diagrams. The original opposing points of view become each player's screen: everyone shares the same points, but phones, tablets, and browser windows frame the space differently, so each player is likely seeing a different Voronoi view.

Visit product View on Hacker NewsApr 30, 2026

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Actual performance

4points

Did not reach leaderboard

Launch Intel predictions

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

52%52% 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 · Missing: mac, agents, macos

47%47% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

44%44% predicted probability of success on BetaList, based on ML models trained on real launch data.

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

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

29%29% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Incorrect prediction on native model

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