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Blox Fruits Catalog – A Trading Hub for Roblox Players

Hacker News

Blox Fruits Catalog – A Trading Hub for Roblox Players

Hey HN, I’ve recently built a platform called Blox Fruits Catalog aimed at making trading in the popular Roblox game, Blox Fruits, easier and more transparent for players. Blox Fruits has a huge, active community where players trade in-game items like fruits, game passes, and rare collectibles. However, I noticed that the existing trade systems are often disorganized, lack value transparency, and rely heavily on informal channels like Discord and random groups. I built BloxFruitsCatalog to address these issues. Here’s what it does: Organized trade system: Players can easily list and browse available trades. Real-time value calculator: Helps users evaluate the fair value of items/fruits to make smarter trade decisions. Free to use: Open to everyone, no hidden fees or logins required (unless you want to save trade history). This is a passion project and I’d love to hear your thoughts, feedback, and suggestions on how to make it more useful or improve the user experience. Check it out: https://www.bloxfruitscatalog.com/ Thanks for reading!

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
75%75% 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.
TrustMRRFits verified-revenue profile · Strong signals: users, trading · Missing: mobile apps, ios, personal
60%60% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: user, open · Missing: mac, agents, macos
41%41% 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: exist, lua, existing · 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.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: smart · 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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