Running for stuck to chair programmers

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Hi, I don't like sports but I'm overweight and my doctor leaves me no choice but to start running a little bit.I read a lot of methods for those who, like me, can't even run for more than a minute so I made this little android app to motivate me. It's only a chronometer that alternates walking and running phases and uses text to speech (so I don't have to look at my phone while running). Hope this helps https://play.google.com/store/apps/details?id=com.deliriom.runbabyrun

Visit product View on Hacker NewsSep 8, 2012

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

76%76% 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: apps, google · Missing: mobile apps, ios, personal

69%69% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Strong signals: google, apps · Missing: mac, agents, macos

50%50% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

nativeThis product was originally launched on this platform.

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.

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

30%30% 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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