DataGuessr – a daily quiz that teaches global statistics through play

Hacker News

I'm a journalist and product developer by day, and a curious generalist who loves making things whenever I find time. I've always loved building little web apps, even with my limited coding skills. As a student and early in my career, I had a lot of time, so it didn't matter. In recent years however, with life being busy as it is, most of my ideas stayed at the back of my mind. There simply wasn't enough time to compensate for my limited skills. Until I started working with Cursor, that is. All of a sudden, the time needed to turn an idea into a working prototype is once again within what I'm able to carve out. That's how this project came to be. I'm a longtime admirer of the work Gapminder and Our World in Data are doing, and I wanted to build something that lets people explore the vast amounts of data about the world Our World in Data provides – in a playful way. Would love to hear what you think, what you'd improve, and what topics you'd like to see added next.

Visit product View on Hacker NewsSep 17, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: cursor, apps, coding · Missing: mac, agents, macos

87%87% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

86%86% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: apps, way · Missing: mobile apps, ios, personal

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% 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.

Correct prediction on native model

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