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I developed a nostalgic Pokemon web game – Pokemon Journey Together

Hacker News

I developed a nostalgic Pokemon web game – Pokemon Journey Together

Hi everyone! I'm excited to share a web-based Pokémon journey game I've developed. It's a turn-based game that reminds me of the ones I played in my childhood. The gameplay is straightforward, featuring battle images and combat logs. This little project fulfills one of my childhood dreams from watching Pokémon anime: collecting various Pokémon through battles. As someone who grew up watching the series, it's particularly meaningful to me. This is my first attempt at developing a web game, and I would really appreciate your support and feedback! The game may be simple, but it's made with passion and nostalgia.

Visit product View on Hacker NewsJan 26, 2025

Actual performance

2points

4comments

Did not reach leaderboard

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

63%63% 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.

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

55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

50%50% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: excited, io · Missing: https docs, just released, exist

32%32% 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 · Missing: arr, mrr, revenue

12%12% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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