Plain Text Live Cricket Score

Hacker News

Hi HN, I built CricLite ( https://criclite.com ), a minimalist live cricket scores website. A few months back, I saw plaintextsports.com and loved its simple design, but it didn't cover cricket. With cricket having around 2.5 billion fans worldwide, I thought this was a perfect side project. The site is deliberately simple: pure ASCII text, no JavaScript, loads instantly (around 10KB), and works everywhere - browsers, terminals, you name it. You can even grab scores directly from the terminal: curl -s https://criclite.com/plain.txt The entire goal was to create the fastest, most no-nonsense way to check cricket scores. Source code is on GitHub: https://github.com/rishikeshsreehari/criclite

Visit product View on Hacker NewsMar 24, 2025

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80%80% 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.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

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

54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

38%38% 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

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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