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ScoreCast
A revived football prediction project for match insights
ScoreCast is a football match prediction project I originally built in college and recently revisited after 3 years. It predicts match outcomes (Win/Draw/Lose), Over/Under goals, and Both Teams To Score (BTTS). The project has been improved and restructured for better predictions and future expansion. It’s an ongoing experiment in football analytics and predictive modeling. 🔗 https://costas.pythonanywhere.com/ 💻 https://github.com/Costasgk/ScoreCast
I originally built ScoreCast 3 years ago as a small college project out of curiosity around football match prediction. At the time, it was a simple experiment to see if I could estimate match outcomes using basic data and logic.
After revisiting it recently, I realized how much I had learned since then, and decided to rebuild and improve it instead of leaving it as an old experiment. The goal was not just to “finish” it, but to turn it into something more structured and expandable.
Since then, I’ve added support for multiple prediction types like Win/Draw/Lose, Over/Under goals, and Both Teams To Score (BTTS), and refactored the system to make it easier to extend in the future.
This launch is more about the journey of improving an old idea than building something perfect. I’m continuing to iterate on it and would really appreciate any feedback, suggestions, or ideas for improvement.
Happy to answer any questions about the project or approach
About ScoreCast on Product Hunt
“A revived football prediction project for match insights”
ScoreCast was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #148 on the daily leaderboard. ScoreCast is a football match prediction project I originally built in college and recently revisited after 3 years. It predicts match outcomes (Win/Draw/Lose), Over/Under goals, and Both Teams To Score (BTTS). The project has been improved and restructured for better predictions and future expansion. It’s an ongoing experiment in football analytics and predictive modeling. 🔗 https://costas.pythonanywhere.com/ 💻 https://github.com/Costasgk/ScoreCast
On the analytics side, ScoreCast competes within Web App, Football, Artificial Intelligence and GitHub — topics that collectively have 640.6k followers on Product Hunt. The dashboard above tracks how ScoreCast performed against the three products that launched closest to it on the same day.
Who hunted ScoreCast?
ScoreCast was hunted by Costas Gkinos. 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.
For a complete overview of ScoreCast including community comment highlights and product details, visit the product overview.
Costas Gkinos