Typical salaries
Here's a rough guide to what football data analysts and data scientists earn at each stage of their career in the UK. Premier League clubs tend to pay a bit more than these figures.
Football data analyst
| Entry level | £27k |
|---|---|
| Mid level | £40k |
| Senior level | £60k |
| Head level | £100k |
Football data scientist
| Entry level | £35k |
|---|---|
| Mid level | £60k |
| Senior level | £90k |
| Head level | £130k |
Figures are approximate and meant as a guide. Premier League clubs typically pay a little more.
The jobs aren't just in London
In corporate life, most of the well-paid jobs are concentrated in London and thin out as you go further north. Football is different: there are clubs all over the country, so analytics jobs are spread across the UK too.
What affects how much you're paid
The same job title can pay very differently depending on where and for whom you work. The biggest factors are:
- Cost of living. The same role at a London club will usually pay more than one at a club in, say, Scotland.
- The club's league. A Premier League club will usually pay more than a club in the Championship, League One or League Two.
- First team or academy. First-team roles usually pay more, but the league matters too.
An academy analyst at a Premier League club might be paid more than a first-team analyst at a League Two club.
Not all analysts do the same job
"Analyst" covers several quite different roles. Here are the three main ones, what they do, and what you typically need to get in.
Performance analyst
Works most closely with the coaching staff
What they do
- Match analysis for upcoming and completed games
- Analysis of specific players
- Tactics such as set pieces and formations
What you need
- A degree in sports science, sports or performance analysis, or coaching is common but not essential
- Tactical understanding counts, and a UEFA C or B coaching badge helps a lot
- Hands-on skill with video tagging software such as Hudl Sportscode, Nacsport, Wyscout or Metrica
Recruitment analyst
Serves the head of recruitment or sporting director
What they do
- Scouting and squad planning
- Analysing player data ahead of transfer windows
What you need
- Strong knowledge of football data (event data, xG and similar metrics) plus video scouting
- Good SQL, Python or R, and visualisation skills are increasingly expected
- A public portfolio is very influential: recruitment reports, shortlists or analysis posted online
- Scouting qualifications (PFSA or the FA Talent ID courses) help, as does a background in video scouting
Data analyst / data scientist
Serves several areas, e.g. commercial, scouting and performance
What they do
- The most technical of the three roles
- Build dashboards and models, such as xG and player similarity
- Work day to day with Python and SQL
What you need
- A quantitative degree is usual: maths, statistics, computer science, physics or similar. An MSc or PhD is common at top clubs
- Strong Python or R and SQL are required, and modelling and machine learning skills matter for senior roles
- Football knowledge is valued but less critical. Many hires come from tech, betting or finance (Smartodds, Starlizard and the big data providers are common feeders)
- A portfolio of public football analytics projects (blogs, GitHub, StatsBomb open data work) is the standard way to stand out
At a smaller club, you could be doing all three.