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WOC Street- Wallstreetbets Without Noise

Hacker News

WOC Street- Wallstreetbets Without Noise

Hi Everyone, I was frustrated that online investing sites are filled with self-promotion, noise, and misinformation. There is no way to verify someone's credibility online. Retail investors are easily faced with poor advices due to lack of knowledge & time. WOC Street crowdsource community predictions, filter out noises, and show everyone's win rate while letting everyone have some fun playing the game. If you are not familiar with the prediction market concept, it's like predicting sports game outcomes, but instead of teams, you'll be predicting whether stocks will go up or down by the end of the week. It calculate a live probability for everyone to make a more informed decision. We have a few hundreds players already. If you don’t mind playing and seeing if you can achieve a 50% win rate, I appreciate any feedback.

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Actual performance

5points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
70%70% 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: way · Missing: mobile apps, ios, personal
52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
45%45% 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
38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
15%15% 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
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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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