Bee Genius, a multiplayer word game inspired by the NYT Spelling Bee

Hacker News

My friends and family like to text each other every day while playing the NYT Spelling Bee puzzle, trading hints, etc. So I thought it would be fun to build a multiplayer game inspired by the spelling bee where people can play together. You can start a new game whenever you want and you can invite up to 3 people to play with you. You can each find words and you'll see what words your friends have found. You can try it here: https://bee-genius.onrender.com/ I created a dictionary and generated thousands of puzzles. I tried to reach a good balance of including enough words for the puzzle to be challenging without so many obscure words that it's frustrating.

Visit product View on Hacker NewsNov 17, 2021

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Actual performance

2points

Did not reach leaderboard

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

76%76% 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: trading · Missing: mobile apps, ios, personal

57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io, including · Missing: https docs, excited, just released

56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos

20%20% 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, revenue

16%16% 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.

Incorrect prediction on native model

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