I made a site to track graded Pokemon card sales

Hacker News

Hey everyone, this is my side project that I’ve been working on during my evenings and weekends for the last few months. I got tired of constantly checking ebay sold listings just to figure out what a graded card was worth, so I built chasecard.gg. Other sites just show a basic trend line, but I wanted deeper insights so this one includes things like moving averages to help spot momentum shifts like golden crosses and death crosses. Plus, it has card comparison and portfolio tracking. I have lots of ideas for other things to add, but I’d love any feedback for things you think I should add!

Visit product View on Hacker NewsFeb 24, 2025

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

82%82% 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 · Missing: mac, agents, macos

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

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

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

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

39%39% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

35%35% 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

15%15% 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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