My
My 10 yr olds recent scratch creations
Hacker NewsMy 10 yr olds recent scratch creations
Hi HN, my 10 yr old asked me to share his recent scratch creations with ya'll so here I am. He's relatively new to scratch. If you have a moment to spare, check out some of his work here. Enjoy! Swamp (platformer) - https://scratch.mit.edu/projects/412453144/ Unstoppable (visualizer) - https://scratch.mit.edu/projects/412468010/
Share cardActual performance
13points
9comments
Made the leaderboard
Launch Intel predictions
Analyze your own launch →Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released66%66% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting46%46% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: visualize · Missing: mobile apps, ios, personal41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews23%23% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: new, visual · Missing: mac, agents, macos21%21% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue15%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, crypto8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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