Graphs – A daily puzzle game to guess data sets

Hacker News

Hi everyone. I'm making Graphs as a love letter to the crossword, Wordle, Connections, and other "educational" daily games. I started building it a week or two ago and have some more ideas on the roadmap, but I'd love to share it today to see what people think. Every day, you are given a nameless graph and 3 options to select the right data set it is representing. It's super simple - check out today's chart and you should be able to get the gist quickly. My email + # is on the page. Would love feedback on the game as well as ideas for future graphs and/or data sets to look into! It's been a balancing act between finding a data set that is quality and public, not too niche, and visually interesting. Winning streaks and/or archive coming soon! Don't hesitate to reach out ~Ari https://www.graphs.world

Visit product View on Hacker NewsJul 27, 2024

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AppSumoStrong fit for a featured deal · Strong signals: soon · Missing: plus, platform, intuitive

66%66% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

47%47% 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: education · 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: email, visual · Missing: mac, agents, macos

34%34% 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

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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

Correct prediction on native model

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