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Queuedle – Daily word-sliding puzzle inspired by Wordle and Scrabble

Hacker News

Queuedle – Daily word-sliding puzzle inspired by Wordle and Scrabble

Hey HN! Queuedle is a daily word-sliding puzzle that I play with my friends. It combines the positional gameplay of Scrabble with the daily puzzle and discovery elements of Wordle. The letter distribution mirrors Scrabble's tile frequencies, and daily puzzles are generated deterministically using the current date as a seed. It uses the Scrabble (TWL06-US) word list, but excludes two-letter words. The design/interface aims to be fairly understated. Any feedback is welcome but I'm especially keen on onboarding people to the mechanics quicker. Devlog: https://healeycodes.com/how-i-made-queuedle

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
49%49% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
29%29% 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
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: using, code · Missing: mac, agents, macos
16%16% predicted probability of success on Product Hunt, 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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