Analyst path
What a data or video analyst actually does, what a portfolio has to prove, which skills matter and how to read an analyst job advert. Mechanics first.
The job before the job title
Titles in football analysis vary more than the work does. Performance analyst, data analyst, recruitment analyst, video analyst, first-team analyst: the labels differ by club, by country and by how the department was built, but the underlying task is a triangle of question, evidence and decision.
Almost every role sits somewhere on that triangle. One job leans towards collecting and cleaning, another towards modelling, another towards presenting to a coaching staff, and seniority usually means moving closer to the decision rather than closer to the code.
- Framing: turning a vague concern into a question that can be answered with data.
- Collection: getting event, tracking or video data into a usable state.
- Analysis: choosing a method that fits the question and the sample size.
- Communication: presenting a finding so that a coach can act on it.
- Review: checking whether the recommendation worked, and saying so if it did not.
Read a vacancy against that list and the advert becomes much easier to decode. The data analyst role describes where the weight falls in a typical department.
A portfolio has to prove a process, not a result
A dashboard of a major league proves that you can operate a tool. A small project on a question you chose yourself proves that you can think: define a metric, choose a sample, handle its limits, and explain what the answer does not cover.
Recruiters read portfolios looking for evidence of judgement under constraint. That means a short write-up of a modest question usually beats an unfinished attempt at a large one, especially when the write-up states what you would do differently.
Building a portfolio sets out what to include and, more usefully, what to leave out.
The stack: tables, pictures, code
The technical stack is usually described as a list of tools, which misses the point. What matters is which layer of the work each tool serves, because employers hire for the layer, not for the logo.
| Layer | What it is for | What gets checked |
|---|---|---|
| Spreadsheets | Quick checks, reconciliation, shared working files | Whether you can spot a broken join |
| Visualisation | Making a finding legible in one look | Whether the chart answers the question |
| Code | Repeatable pipelines and modelling | Whether the work can be re-run by someone else |
| Writing | Reports, captions and recommendations | Whether a coach understands it without you |
| Domain knowledge | Knowing which questions are worth asking | Whether your analysis survives a coach's scrutiny |
Python and R for football covers the code layer honestly: which tasks belong in each language and which belong in neither.
Reading the advert, then the interview
Adverts are written by committees, so the useful information is usually in the verbs. "Support the coaching staff" means matchday hours and short deadlines; "build and maintain models" means code, validation and documentation; "communicate insights to stakeholders" means reports and meetings, not notebooks.
Reading an analyst job advert turns the phrases into questions you can ask in the interview, which is also the fastest way to find out whether the role is what the title says.
Most processes include a task on unfamiliar data, and the task is rarely scored on the final number. Interviewers watch how you define the metric, how you treat a small or biased sample, and whether you can explain a result in one sentence to someone who will not read the method.
Matchday experience is the other common thread. A candidate who has sat through a matchday as a video analyst knows what a turn-around time feels like, and that usually shows in how they scope the task.
Football data analyst: what the club job really involves
What a football data analyst does in a club: event and tracking data, the reports a coach will read, weekly support for staff and the matchday timeline.
Football analytics portfolio: what gets interviews
What a football analytics portfolio needs: one finished project, written conclusions, a small model that shows method and visuals that survive a second look.
Video analyst in football: the real matchday workflow
How a football video analyst works through a match week: opposition montage, live clipping, the half-time window, the post-match review and the report.
Python or R for football analytics: what to learn first
Why football analysts write code, what Python and R are each good at, and the order to learn data handling, visualisation and modelling without wasting months.
How to read a football analyst job advert properly
Read a football analyst vacancy like an insider: the verbs that describe real work, stack signals, seniority clues, red flags and the questions worth asking.