Open-source analytics for Japan’s Numbers3, Numbers4 & Loto6: historical draws, ensemble ML forecasts, SQLite + GitHub Actions pipelines, and a Next.js dashboard (optional Supabase). Made for transparency and reproducible research—not betting advice, not affiliated with any official lottery operator, and not a promise of results. Feedback from data/ML folks especially welcome.
Hi Product Hunt 👋 I’m [Takeshi Kubokawa / @kubocchi.studio], maker of Million
Pocket Orchestra.
I started this project because I wanted a place where lottery draw
data isn’t just “numbers on a page,” but something you can
explore with clear pipelines: historical results, ensemble ML
forecasts, charts, and reproducible workflows (SQLite + GitHub
Actions) instead of a black box.
It focuses on Japan’s public draws (Numbers3, Numbers4, Loto6) and
ships with a Next.js dashboard (optional Supabase) plus Python
tooling. Everything is open source so you can verify how
predictions are produced and extend the models yourself.
Important context: this is for research, learning, and
transparency—not gambling advice, not affiliated with any official
operator, and not a guarantee of outcomes.
🔗 Source: https://github.com/kubokawa-dev/...
I’d love your thoughts—especially if you’re into data science or
OSS: what would you want to see next (better explainability, more
benchmarks, docs for contributors)?
Thanks for checking it out, and happy to answer questions in the
thread!
No comment highlights available yet. Please check back later!
About takarakuji-ai on Product Hunt
“japanese lottery prediction site”
takarakuji-ai was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #244 on the daily leaderboard. Open-source analytics for Japan’s Numbers3, Numbers4 & Loto6: historical draws, ensemble ML forecasts, SQLite + GitHub Actions pipelines, and a Next.js dashboard (optional Supabase). Made for transparency and reproducible research—not betting advice, not affiliated with any official lottery operator, and not a promise of results. Feedback from data/ML folks especially welcome.
takarakuji-ai was featured in Open Source (68.3k followers), Analytics (171.4k followers) and GitHub (41.2k followers) on Product Hunt. Together, these topics include over 44.1k products, making this a competitive space to launch in.
Who hunted takarakuji-ai?
takarakuji-ai was hunted by Takeshi Kubokawa. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Takeshi Kubokawa