Golazo – Live soccer updates in your terminal

Hacker News

Hey all! I built Golazo because I wanted a minimal but effective way to get soccer live updates and catch up on finished matches right in my terminal. No browser tabs, no ads, no distractions: just clean match data where I already spend most of my day. I couldn’t find any actively maintained tool like this, so I thought it could be cool to build something just for what I need. It was a great learning experience and if it’s useful to other people, then even better! Current features: - Live match tracking with real-time score updates (90-second polling intervals) - Minute-by-minute match events (goals, cards, substitutions) - Finished match statistics and full event history - Goal notifications via beeep (macOS, Linux, Windows) - 40+ leagues supported (and growing) with customizable preferences to limit what you fetch - Smart caching: data cached for 5 minutes, polling only when viewing live matches Technical details: - Built with Go using Cobra for CLI, Charm’s Bubble Tea/Bubbles/Lip Gloss for the TUI - Data from a trimmed-down version of the Fotmob API - Cross-platform terminal rendering has been the biggest challenge – still working through some rough edges Easy to install via install script or build from source. Pre-built binaries available for macOS, Windows, and Linux. Would love to hear feedback from fellow terminal enthusiasts and soccer fans!

Visit product View on Hacker NewsDec 28, 2025

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

87%87% 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: mac, macos, using · Missing: agents, agent, cursor

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: platform · Missing: plus, intuitive, reviews

58%58% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal

37%37% predicted probability of success on TrustMRR, 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

36%36% 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

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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