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A self-hosted website to track Pinball scores between friends

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A self-hosted website to track Pinball scores between friends

Hi there! I have been a huge fan of pinballs for a few months, discovering all pinballs that are in my city, and I converted quite a few friends to it. The only problem was that we wanted to keep an eye on everyone's score and I always did it in some notes on my phone. This was not very practical. I decided to create a small website so that all my friends can add their scores while we're playing in a gig. The app is minimalistic on purpose: no user authentication, no call to any fancy Pinball API whatsoever. I just need a list of players, gigs, pinballs and scores. The app is built with Laravel and SQLite so it should be easily deployed anywhere. I personally host it on Fly for free (they have a generous free tier). One can add HTTP Basic authentication with a common user/password to avoid having anyone unkown messing with your data. The link to the repo is in the banner. License MIT.

Visit productView on Hacker NewsJan 25, 2024
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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, notes · Missing: mac, agents, macos
64%64% 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: ide, io · Missing: https docs, excited, just released
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.
AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal, month, way · Missing: mobile apps, ios, entrepreneurs
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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