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Research / Football practice / Careers

Football corners.

African talent, Nordic football, and the decisions that connect them. Explore player pathways, recruitment trade-offs, coaching, and the evidence behind team performance.

Find your corner ↗

The data systems column

Football data systems

Build the records, models, and release controls behind a report people can trust. Architecture and operating practice for analysts, engineers, and club leaders.

Ideas to put into practice.

14 guides

Club leaders / Community & partners

A donated pitch needs an operating plan

A partnership’s value depends on usable football provision, including the costs and responsibilities that recur.

Original reporting and analysis, with publication dates and sources. Worked examples are labelled separately from observed player data; individual pathways do not stand for an entire league.

Explore player pathways, scouting, and sustainable football ↗

Career pathways / Start with practice

Two roles. A shared understanding of football.

Build football knowledge, technical skills, and the ability to work with people. These suggested pathways help you choose a first project and see how the roles connect.

Football analyst

Turn football evidence into decisions.

  1. Understand the game

    Choose a match question and the person who needs the answer.

  2. Learn the essentials

    Practise with a spreadsheet, basic statistics, and Python or R.

  3. Connect evidence

    Combine relevant data with structured match observations.

  4. Make a useful report

    Explain the finding, context, and next step in plain language.

  5. Review your work

    Seek feedback, refine a portfolio, and explore suitable roles.

Data engineer

Make football information dependable and accessible.

  1. Understand the users

    Learn what analysts and coaches need from the data.

  2. Learn the essentials

    Practise SQL, Python, data structures, and version control.

  3. Build the process

    Import a permitted source and document identifiers and transformations.

  4. Check reliability

    Test missing values, duplicates, freshness, and repeatable updates.

  5. Deliver and maintain

    Document the dataset, support its users, and improve the process.

Developed from our reading and listening, including McKay Johns on analytics and engineering, Kaustubh Kapoor on production pipelines, and Beggs on analytical practice. Roles and entry routes vary by organisation.