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Apple Activity Rings, but for Anything

Hacker News

Apple Activity Rings, but for Anything

Hi HN, Closing my Apple Rings has helped me stay disciplined and tracking my fitness progress daily. The only downside is that it is not configurable outside of fitness-related goals. So I built Orbit Progress Rings, it's pretty much the same concept as far functionality, but configurable for whatever hobby you want to track and see your progress at a glance on your watch. I would love your feedback.

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: apple, activity · Missing: mac, agents, macos
70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: fitness · Missing: mobile apps, ios, personal
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
40%40% predicted probability of success on AppSumo, 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
33%33% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
22%22% 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
5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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