ChessMonitor – Analytics for Chess Players

Hacker News

Hi everyone! ChessMonitor is an analytics platform for chess players that provides stats on your games. The link shows an example of Magnus Carlsen. Connecting your own Chess.com or Lichess accounts only takes a few clicks. The project has received a significant update in the past weeks, as it's now receiving the "EXIST startup grant" provided by the German Ministry for Economic Affairs and Climate Action. This grant allows me to work on the project full-time. Most features are currently free, but I’m actively working on new additions, many of which will be only available in the paid plans. If you have any feedback or questions, please let me know! Thanks, Thomas

Visit product View on Hacker NewsJun 9, 2024

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2points

Did not reach leaderboard

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

86%86% 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.

Product HuntOn track for Day 1 leaderboard · Strong signals: new · Missing: mac, agents, macos

62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

43%43% 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, reviews

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: paid · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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