How to get started in data and the football industry (2024)

I’m starting to get messages regularly asking about starting in data analysis, what software I use for data visuals, and how to get a job in the football industry. So I thought I would write an article on it.

Just a disclaimer that I am not an expert, there are far more qualified people out there to help you with your journey. But I thought I’d share what knowledge I have learnt along the way so far.

There are a lot of people out there who want a job in football, but don’t actually know what it is they want to do. This is fine, especially for younger people who are still studying. I know so many people who did sports degrees and didn’t know what they wanted to do after them.

Having broader horizons and experiences can only be a good thing. I was fortunate enough to start coaching at the age of 16, and subsequently complete my coaching qualifications. I also studied a broad Sports Coaching degree which covered a multitude of areas including: practical coaching, performance analysis, psychology, paediatric physiology and many others.

You’ll notice more on job adverts now that football clubs see coaching qualifications or backgrounds as very desirable. If you’re able to have an appreciation and understanding of the technical, tactical, physical and psychological demands of the game, you’re only going to be a better analyst.

My point is, whilst clubs do want people with experience — it’s not a deal-breaker. If you can use and relate your experience, be-it from the football or sports industry, or even from a different industry, you will be off to a great start. Specifically in analysis, we’re seeing more people with non-sporting backgrounds move into the industry due to their technical skills, but also their transferrable skills. Different experiences are a massive bonus.

Key takeaway: If possible, get some experience in coaching, if that is completing your Level 1 or 2 qualifications, that would be ideal. If not, volunteering with a local side to begin to understand the coaching side of the game. The knowledge gained from coaching is hugely beneficial.

Also on a side note: regardless of what industry you are hoping to secure a job in, companies want applicants with soft skills, growth mindset and self-awareness.

Well, starting with data all depends on what you’re wanting to do and look at. If you’re wanting to create some data visuals or analysis using player or team data(shots, aerial duels, dribbles, interceptions ect) then you have a few options.

FBref — This website has all the event data you could need for the top five major European leagues. It’s completely free, and uses data from Statsbomb, which is great for data reliability.

Wyscout — If you’re wanting data form a massive pool of leagues, Wyscout is worth the investment. It’s approx £210 for the year, and includes all EFL Leagues, National League, Belgian First division and many more. Admittedly, the data is not as reliable as Statsbomb or OPTA. But given it covers a vast amount of leagues, and you get 70mins of video per month, it’s certainly value for money. I wouldn’t be able to do a lot of my work without Wyscout.

There are other free sources of data as well: OPTA’s interactive season dashboards, whoscored, soccerstats and many more.

My advice would be if you’re just starting and don’t know whether to invest in Wyscout, have a play with the free sources of data, sign up for a trial on Wyscout and take it from there.

If you’re wanting event level data such as shot and tackle locations using X, Y coordinates, again there are some different options. Edd Webester has put together an unbelievable resource, I’d recommend going through his data sources as it’s far more comprehensive that I could ever explain myself.

Key takeaway: Go through Edd Webster’s Repository (link above). It’s a great resource and starting point for all things data. We’ll refer back to this when we talk about different software and tutorials.

This will vary depending again on what it is you’re wanting to do, and also your experience of using different programs. I was blown away when I first started as to how people made their data visuals. I just assumed everyone was using excel!

Tableau Public

If you’re just starting out then Tableau Public is your best friend. It’s easy to use, there are plenty of tutorials and it’s quite intuitive. You can quickly get to grips with creating scatter plots and bar charts along with a host of other things.

I’d highly recommend Ninad Barbadikar tableau tunnel series, it consists of very easy to follow tutorials to create some great data visuals.

There are others who have put out some great work, again these are cited in Edd Webster’s repository.

Coding — Python and R

I’m still very much an amateur in the world of coding. I personally use Python, but there isn’t much of a difference between that and R. They’re both coding languages that you can use to create data visuals.

I personally found McKay Johns’ youtube tutorials incredibly helpful when starting with Python.

There are others who have put out some excellent tutorials and guides for Python and R. So once again I will link you with Edd Webster’s repository.

Twitter is a brilliant. I’ve largely only got great things to say about the platform. It’s a great place to share your thoughts, analysis and insight.

If you’re regularly sharing your work on the platform, it acts as a portfolio. It also tracks your growth and development as you continue to learn more and improve your ability.

Twitter also provides a platform to follow and interact with industry experts, knowledgeable people and the general football fans. If you’re regularly engaging in conversation and creating these connections, you can get some really valuable feedback and ideas about what’s great about your work, and where you can improve.

The football analytics community on twitter are also incredibly helpful. If you ever need help, or don’t understand anything there is normally always someone who will be able to help or share some advice. I personally don’t think I would know half as much as I do now without the insight, help and guidance from others.

You also never know who is looking at your work on twitter, I have had loads of potential opportunities and conversations about working in football. These have all come from people seeing or sharing my work on twitter. If you put out regular, quality content, people will see you and you will get opportunities.

In regards to opportunities, in my view, the best place to see potential jobs is on twitter. If you follow the right people they will normally be circulated. Specifically though, Training Ground Guru and Josb4Football are the best accounts to follow for job adverts.

Key takeaway: I’d highly recommend joining the football in numbers discord server. There are loads of chats for discussions around analysis, sharing your work and dedicated channels to ask for help with tableau, python and R. It’s a must join. There is also a chat specifically for people to shared live job adverts in football.

As with most things in life, you need to find your own niche to be successful. The reality is there are loads of people out there sharing some excellent work and analysis, so what separates you from everyone else?

Now I can’t tell you what your niche is. Find something you enjoy, and go from there. My twitter page started looking specifically at Nottingham Forest, the team I support — but I’ve branched out into hopefully being an interesting EFL account.

Whatever you do make sure you enjoy it. If you’re going to use your free time outside of work, university or college, enjoy it. If you don’t, what is the point in doing it?

Key takeaway: Find your niche and run with it. It might be a twitter account on your local team, it might be being an U23s scouting account, just please make sure it is something you enjoy if you’re investing a lot of your personal time into it.

I personally feel the idea of working in football can sometimes be better than reality. Working with likeminded individuals, in an industry you love sounds great, and it is for a lot of people. But the truth is you normally have to work a lot of hours in football, typically the pay isn’t the best unless you’re in a higher or more senior role and as a result your work-life balance could suffer. This isn’t to put anyone off wanting to work in football, it’s just the reality of it sometimes.

My advice would be, don’t rush into a role or an opportunity just because its the first, or one of a few which have come up. Make sure it is the right opportunity for you. Will you be supported by the people you’re working for/with? Are you going to learn and develop in the role? Are you going to be able to maintain a good work-life balance? Most importantly, are you going to enjoy the role?

Working in football seems like the job of all jobs, but it’s not the be all and end all. I’ll go back to what I said earlier, find something you enjoy doing, whatever that may be.

Key takeaway: Working in football can be great, but it can sometimes be hard and challenging. Whatever you do, before accepting any opportunity, make sure it is right for you, and that you’re going to be able to get what you want from it.

Hopefully if you’ve got this far you have found this piece somewhat insightful. I hope this will be able to help you in what it is you’re trying to achieve.

If you have any questions on the back of this feel free to drop me a message on twitter.

How to get started in data and the football industry (2024)

FAQs

How to start football data analysis? ›

Internships are a great starting point. Many professional analysts, even those working at top clubs, started their careers as interns. An internship gives you the chance to find out how analysis at a football club works in practice and allows you to learn from the experience of the analysts already in the department.

How do I get started in sports data analytics? ›

The primary qualifications for a sports data analyst position are a bachelor's degree in a related field and experience with predictive modeling, trend analysis, and other statistical information techniques. Employers prefer applicants who have some experience, but this isn't mandatory for most roles.

What skills do you need to be a data analyst in football? ›

Strong knowledge and expertise with R or Python for data ingestion, processing, and analysis. Experience with data visualisation tools such as Tableau or other software libraries. Strong experience with relational databases and SQL. Excellent organisational skills with the ability to work with total discretion.

How can data be used in football? ›

How Analytics is used in Football? There are many ways that analytics is used in football, but some of the most common include: Player Performance Analysis: By tracking data on players' movements and actions on the field, teams can gain insights into a player's strengths and weaknesses.

What software do football analysts use? ›

Catapult Pro Video sets the standard in Football Video Analysis Software, offering a comprehensive suite of tools tailored for every performance analysis workflow in football. Integrating the forefront of football video technology, this platform provides an in-depth, visual exploration of games and training sessions.

How do I start a data analysis field? ›

How do I become a data analyst? A step-by-step guide
  1. Get a foundational education. ...
  2. Build your technical skills. ...
  3. Work on projects with real data. ...
  4. Develop a portfolio of your work. ...
  5. Practice presenting your findings. ...
  6. Get an entry-level data analyst job. ...
  7. Consider certification or an advanced degree.
Apr 19, 2024

How to be a good football analyst? ›

Requirements and Qualifications

Excellent analytical and statistical skills with the ability to interpret complex data. Strong attention to detail and ability to spot patterns and trends. Effective communication skills, both written and verbal. Ability to work collaboratively with coaching staff and other analysts.

How much does a data analyst for an NFL team make? ›

While ZipRecruiter is seeing annual salaries as high as $179,000 and as low as $64,500, the majority of Nfl Analytics salaries currently range between $100,000 (25th percentile) to $149,000 (75th percentile) with top earners (90th percentile) making $165,000 annually across the United States.

How do I become a game data analyst? ›

Fundamental skills of a game analyst, commonly outlined in any job description, include a passion for games, proficiency in SQL (above average), the ability to effectively visualize data and reports, familiarity with R or Python (though not mandatory), and critical thinking paired with the capability to filter and ...

How is football data collected? ›

Collection of positional data To collect the positional data (x-y coordinates) of all players, the referees and the ball, an optical tracking system will be installed in all ten stadiums. The optical tracking system is able to capture player positioning multiple times per second..

How do NFL teams use data analytics? ›

Over the last several years, analytics have enabled NFL teams to evaluate players in ways not possible before — for example, assessing a defender's ability to create tackling opportunities, not just completed tackles. Coaches use the metrics to streamline game preparation.

What is data analytics in the football industry? ›

The Impact of Data Analytics

One of the key advantages of data analytics in football is its ability to provide teams with in-depth insights into their opponents' playing styles and strategies. By analyzing past matches and collecting real-time data, teams can predict the tactics their rivals are likely to employ.

How to do analysis in football? ›

An analysis is studying or examining something in detail and drawing a conclusion. In football terms watching a game and drawing conclusions from what you see. When looking to analyse a team's tactics these are the three things/steps you should look to implement/look at Pre-Game, Shape/Set-Up & Tactics.

How do you start a data analysis report? ›

How to Write a Data Analysis Report? 9 Simple Steps
  1. Start with an Outline.
  2. Make a Selection of Vital KPIs.
  3. Pick the Right Charts for Appealing Design.
  4. Use a Narrative.
  5. Organize the Information.
  6. Include a Summary.
  7. Careful with Your Recommendations.
  8. Double-Check Everything.
Nov 30, 2023

What is the data analytics of football? ›

Football analytics by definition is the breakdown of football-related data from matches and players, and analysis of that data to create a strategy to counter or improve the particular player/team on whom/which the data has been collected.

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