Self Sport – A lifestyle tracker for building a better sense of self

Hacker News

Hello HN, I'm Clay, a solo developer based in Austin. After struggling with self-esteem issues for over a decade, I decided to confront them head on by learning React Native and building Self Sport ( https://hiselfsport.com ). I am excited to share it with you all here. In Brief: Self Sport is an app that's designed to foster lifestyle mindfulness and promote an active, engaged life. It's slated for “launch” in August and I'm hoping to get early adopters on board who can share their invaluable feedback. The Journey: For years, I was grappling with generalized anxiety, avoidance behavior, and depression. I felt like I was constantly struggling to maintain a semblance of normalcy in my life. For me, my life took a turn when I shifted focus from my symptoms to their causes. This led to a new lifestyle of fitness, mindfulness, self-improvement and generally seeking more variety in my life. As part of this journey, I learned to code and built Self Sport. The App: Self Sport isn't just another lifestyle tracker; it's an attempt to create a community that promotes a better sense of self through lifestyle mindfulness. I don't expect it to become a viral sensation, but I do think that this is a tool that can help individuals transform their lives — it helps me. Call to Action: I'm now on the hunt for early users who can help me refine this app and grow the community. If you're interested, please sign up or drop me a line. Self Sport is more about lifestyle optimization and presence than anything else. I guess you can call it a wellness app, in a sense, but it’s more active than most. Thanks for taking the time to check it out, and I'm eager to hear your thoughts! Best, Clay https://hiselfsport.com

Visit product View on Hacker NewsJun 26, 2023

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Indie HackersFits the IH revenue-focused audience · 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.

Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, code · Missing: mac, agents, macos

62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: users, fitness · Missing: mobile apps, ios, personal

56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

46%46% 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 · Strong signals: active · Missing: arr, mrr, revenue

19%19% 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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