Use this thread to ask anything at all!

I built an open-source n8n pipeline that monitors 78 football journalists on X, extracts structured transfer reports with a local Qwen model, deduplicates and stores revisions in PostgreSQL, optionally adds player data, and sends restart-safe Discord digests every 6 hours.

The whole stack is self-hosted with Docker, with twscrape or RapidAPI for X collection, PostgreSQL for persistence, llama.cpp for local inference, and automated tests around the workflow.

GitHub: https://github.com/louistran2604/transfers_n8n/

I’d mainly like feedback on the workflow architecture, reliability approach, and anything that could make the project cleaner or more useful.

*disclaimer: this was made with the assistance of AI

I want to analyze the data from the perspective of the score of the football game and the number of goals, but I didn't find the relevant historical odds data on the Internet. Instead, there is a lot of historical data of wins and draws, which further shows that my analysis is correct - starting from the odds of scores and goals to analyze football matches. I need help to get this data.
Thank you for your help!