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CSSBattle 2.0 – The funnest CSS game for web designers and developers

Hacker News

CSSBattle 2.0 – The funnest CSS game for web designers and developers

Hello HN! My name is Kushagra, and I am the co-founder of CSSBattle[1]. We built CSSBattle to make web designing a bit more fun. CSSBattle is an online competitive game where you have to replicate a given target image with CSS. When you submit your CSS code, you get a score based on how well you replicated the image + how short your code is. Our community has now grown to 320k+ players across the world. Over the past 3 years, we've been working hard to make it even more fun and educative for our players. I am very excited to show you a completely revamped version of CSSBattle with great new features which makes it the best frontend gaming platform on the web. Here's what's new: - Daily Targets: after talking to our users, we realized that not all players liked the pressure of leaderboards and competition. So we've introduced Daily Targets where players get a new target every day. These targets don't have leaderboards and are great for beginners who are just getting started - CSS Courses: We've also introduced game-like interactive courses for learning CSS - Monthly Battles: We now host monthly battles for players who crave competition. These are heated battles where players spend hours on shaving off a single character from their code just to rise up on the leaderboards! - Redesign: We've revamped the whole site to make it look nicer, and the whole experience smoother. We've also optimized it to work on mobile devices We would love it if you get a chance to check it out and are excited to hear all your feedback. Thank you for the support! [1] https://cssbattle.dev

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14points
3comments
Made the leaderboard

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
96%96% 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, new, single · Missing: mac, agents, macos
74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, io · Missing: https docs, just released, exist
73%73% 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 · Strong signals: platform, host, users · Missing: plus, intuitive, reviews
52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month, monthly, users · Missing: mobile apps, ios, personal
45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: introduce · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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