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Heart Rate Zones Plus – The first iOS app I developed

Hacker News

Heart Rate Zones Plus – The first iOS app I developed

I built this iOS app because I wanted to get an overview of my time in zones per week without checking zones after every workout manually - Now I'm looking for feedback. Description: Track time in heart rate zones. Track per day, week, month, 7 days and 30 days time period and how much time you spend in each zone. Set goals & visualize progress. Get details about heart rates zones of your workouts. Features: Custom time periods, Workout to zone attribution to get a feeling which sport attributed most to each zone, Multiple zone calculation methods, Set personal time goals for any zone, Workout breakdown Pricing: Free Privacy: Nothing is tracked or send somewhere. Data is just on your device. Any feedback and features request is appreciated. Download: https://apps.apple.com/us/app/heart-rate-zones-plus/id674474... Video of the app in action: https://www.youtube.com/shorts/-qtHxEdMEv0

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93comments
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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
78%78% 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.
TrustMRRFits verified-revenue profile · Strong signals: ios, personal, apps · Missing: mobile apps, entrepreneurs, google
61%61% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: plus · Missing: platform, intuitive, reviews
39%39% 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
38%38% 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
23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: apple, apps, visual · Missing: mac, agents, macos
22%22% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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