n8n.io
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FBPlot
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FBPlot is a football data visualization and player analysis platform for creating professional, customizable football charts.
Compare players across 80+ performance metrics and visualize the results using radar, pizza, scatter, bar and swarm charts. Metrics can be analyzed as absolute values, per 90, percentiles or contribution to the player's team.
Charts can be customized with colors, typography, backgrounds and other visual settings, then exported as high-resolution PNG images for scouting reports, presentations, media and social content.
FBPlot is built for football analysts, scouts, journalists, content creators and fans. A free plan provides access to the Top 5 European leagues, while Pro unlocks all available leagues and competitions.
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FBPlot's answer:
FBPlot is built as a modern web application with a lightweight data architecture optimized for football analytics. Its infrastructure includes SQLite for football data storage and querying, Cloudflare R2 for object storage and CDN delivery, and OVH infrastructure with Coolify for deployment and application management.
FBPlot's answer:
-Independent football analysts -Football scouts and recruitment professionals -Football content creators -Sports journalists and media professionals
FBPlot's answer:
FBPlot combines football player data analysis and professional data visualization in a single tool. Instead of simply displaying statistics, it lets users decide how players should be evaluated โ using per-90 values, absolute values, percentiles, performance relative to the best player, or contribution to their team โ and turn the analysis directly into customizable, publication-ready charts.
FBPlot's answer:
FBPlot is designed specifically for football analysis rather than being a generic visualization or live-score platform. Users can explore player data, choose meaningful comparison cohorts, combine metrics and create radar, pizza, scatter, bar and swarm visualizations without exporting data to another application. It is particularly useful when both the analysis and the final presentation of the data matter.
FBPlot's answer:
FBPlot is primarily designed for football analysts, scouts, recruitment professionals, journalists, content creators and data-driven football fans. It is especially useful for people who need to compare players, investigate performance profiles or communicate football data through clear visualizations.
FBPlot's answer:
FBPlot started as an independent project to make football data analysis easier to explore and communicate. Many football statistics platforms are good at providing data, while general visualization tools are good at creating charts, but using both often requires exporting data and building visualizations manually. FBPlot was created to bring those two workflows together: explore football data, analyze players and create professional visualizations from the same platform.
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It takes a little sweat, but you can wire Claude Code into n8n by running Claude through Docker, SSH, or local command execution from inside a workflow. That means n8n can route a request to Claude as one of its LLM backends. See: https://n8n.io/. - Source: Hacker News / 12 days ago
n8n โ open source, self-hostable. The hosted cloud tier exists if you'd rather not run it, but self-hosting is the whole point here. - Source: dev.to / about 2 months ago
You'll need an n8n instance (cloud or self-hosted), an FFmpeg Micro API key from ffmpeg-micro.com, and a cloud storage folder your team already uses for video files. - Source: dev.to / 2 months ago
n8n and similar visual workflow tools were on the list for one specific reason: leadership likes seeing the boxes-and-arrows. But the LLM nodes aren't first-class โ you'd be wrapping every model call in HTTP, and the graph is in a database, not in code that's reviewable in a PR. Auditability and reproducibility are both worse than the LangGraph + bus path. (n8n is a great fit for non-LLM SOAR-style automations,... - Source: dev.to / 2 months ago
Sign up at n8n.io (free cloud version is perfect to learn). - Source: dev.to / 2 months ago
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