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I made an app to help plan your Weekly Runs

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I made an app to help plan your Weekly Runs

Hello there, When I started training for the first marathon in my life, I download a 6 months training plan, printed it, pinned it to my fridge, and started circling each completed training day. Sadly, I would often get injured during my runs, which would lead to days or weeks without running, and a lot of changes to the plan I had printed. All running apps that I tried either forced me to follow their plan from the start (which I didn’t want to do because I was already in the middle of training) or made it extremely slow and difficult to add a custom plan. So I decided to create my own app, that would allow me not only to quickly import the training plan I was following but also to easily adapt it to real-life events. I called it “Weekly Runs”. The app makes it easy to enter a new training plan, by cloning existing weeks and making only necessary adjustments. More importantly, the app allows to insert non-running and recovery weeks after an injury, into the existing training plan. I also noticed that I would often forget to perform some of the warm-up exercises I planned to do before every run. This is why I added a custom checklist of pre-run activities, that must be checked before starting each run. I hope this app will be as useful to you, as it was to me. I’d appreciate any feedback on the app. Please let me know of any changes or additional features that you would like to see in the app. Thanks for your feedback!

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
89%89% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: apps, new · Missing: mac, agents, macos
74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
64%64% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: apps, month · Missing: mobile apps, ios, personal
51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: training · Missing: arr, mrr, revenue
30%30% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
30%30% predicted probability of success on AppSumo, 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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