# eddwebster/football_analytics

📊⚽  A collection of football analytics projects, data, and analysis by Edd Webster (@eddwebster), including a curated list of publicly available resources published by the football analytics community.

Repository: https://github.com/eddwebster/football_analytics
Canonical: https://ross.abutalabs.com/products/football_analytics
Homepage: https://www.eddwebster.com
Language: Jupyter Notebook
License Family: other
Topics: football, xg, expected-goals, statsbomb, transfermarkt, fbref, soccer, fifa, football-analytics, sports-analytics, football-data, soccer-data, soccer-analytics, sports-stats, awesome, awesome-list, opta, futbol, data-science, analytics
Last push: 2025-10-09T10:51:47+00:00

## Health v2 (maintenance only)
Score: 53/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 46, release rhythm 35, longevity 100
- inputs: {"age_days": 2192, "days_push": 328, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2749, forks 362 (observed 2026-08-28T04:07:17.479011+00:00)

## What it is
A collection of football (soccer) analytics projects, notebooks, and data pipelines by Edd Webster, covering topics like expected goals, xT, VAEP, and tracking data. It also serves as a curated awesome-list of publicly available football analytics resources, libraries, papers, and blogs.

## Use cases
- find data sources for football analytics projects
- learn how to compute expected goals (xG) models
- scrape fbref and transfermarkt football data
- get started with soccer analytics and sports data science
- find football analytics papers, blogs, and libraries
- work with football tracking and event data
- build player recruitment and performance analysis dashboards

## When to choose
- you want a curated starting point for football analytics resources
- you want example notebooks for xG, xT, VAEP, or tracking data analysis
- you need pointers to public football data sources like StatsBomb, FBref, or Transfermarkt

## When to avoid
- you need production-ready, maintained software with a stable API
- you need a licensed, packaged tool rather than notebooks and a resource list
- you work with sports other than football/soccer

## Facets
- artifact type: learning-resource
- maturity: active
- function: data-science, analytics, machine-learning, data-visualization, web-scraping
- domain: sports, data-science, analytics, tutorials, awesome-lists
- platform: python
- tags: football, soccer, sports-analytics, expected-goals, statsbomb, fbref, transfermarkt, curated-resources, jupyter-notebooks

## Member repositories
- eddwebster/football_analytics (main) score 53

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:17.479011+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T08:18:58.645557+00:00, confidence not recorded.
  - readme: https://github.com/eddwebster/football_analytics (fetched 2026-08-28T04:07:17.479011+00:00, sha 62084754b9d0)
  - homepage: https://www.eddwebster.com (fetched 2026-08-29T09:57:00.035551+00:00, sha 7461c92f0a69)
- Data as of 2026-08-30T08:39:29.467469+00:00.