The role of data and analytics within football has grown demonstrably in recent years. Clubs like Brentford and Barnsley have been able to punch above their weight thanks to progressive data-driven recruitment and performance strategies. Meanwhile, metrics such as Expected Goals (xG) have become a key part of mainstream football parlance, regularly used on flagship shows like Match of the Day. Just ten years ago, the data used by clubs was pretty basic, limited to stats on goals, shots, number of shots, possession etc.; now, teams benefit from a far wider, more detailed, and more useful pool of data.
As a result, work opportunities within this side of the game continue to grow. Many professional clubs are looking to expand their analytics departments, while sports analytics companies such as InStat, Scisports and Opta Sports provide an alternative route into football data work. Unfortunately, there's a lot of competition for roles in this area. So how do you get ahead of the game? And what are the best ways to build experience and hone your skill set? In this article, we'll take you through 7 easy steps to get started in football data and analytics.
If you're new to the world of sports analytics, one of the best things you can do is immerse yourself in reading material about the subject. There are numerous books, articles and publications dedicated to the role of data and analytics within football, and as the game continues to develop, this library will only grow. For shorter digital content, check out the work of writers like Tom Worville and Jonathan Wilson, who regularly integrate complex tactical analysis into their pieces.
If you're after longer reads dedicated to the history, development, and deployment of data in football, there are loads of great books to dive into. Some highlights include Simon Kuper and Stefan Szymanski's Soccernomics, Christoph Bermann's Football Hackers: The Science and Art of a Data Revolution, and James Tippet's The Expected Goals Philosophy, which has birthed a popular Twitter page dedicated solely to xG geekery.
If you want to get into this line of work, it's likely that you already watch a lot of football. It's also probable that much of the time you get sucked into a game, enjoying the atmosphere and following the various narratives rather than closely tracking different movements and tactical plays — and that's absolutely fine! It's important to remember that the beautiful game is there to be enjoyed, and we should appreciate the glory of upsets, comebacks and wondershots. But if you want to develop a career within data and analytics, then you need to start watching matches in a certain kind of way. Here are a few tips for watching football analytically:
There are lots of things to consider when you're watching football in an analytical way, so if it seems a bit overwhelming, try to focus on a couple of key aspects of their play that you want to understand. Once you've got to grips with observing football in this way, it will gradually become your natural way of viewing matches, and your confidence when it comes to identifying tactical decisions will only increase.
There is an extremely strong community of football data and analytics fanatics on Twitter, waiting for you to join them. According to remote Dundee scout Ashwin Raman, "There's lots of collaboration, in terms of ideas. I learnt everything I know about tactics and analytics from people inside the community." Former Sutton United analyst Russell Pope concurs, claiming "It feels like a community. If someone with a small profile asks me to retweet their work, I'm more than happy to do that, because I got that in the first instance." And professional clubs are looking to Football Twitter more and more.
There are a lot of knowledgeable, tactically astute people posting content on the social media site, and it's becoming increasingly common for clubs to recruit scouts or analysts from Twitter. The luxury of being able to work, network and develop a portfolio all from the luxury of your own home is an opportunity that shouldn't be missed.
This one relates pretty closely to the last point, but it's worth drilling into it in a little detail anyway. If you're looking to build your knowledge of the game and work out the best route into football data and analytics, spend some time finding people who are currently working in positions that appeal to you. They could be club performance analysts, recruitment specialists, or freelance video analysts (more on this later). What matters is finding someone working in a role which excites and interests you, and speaking to them. Find out how they started out. Ask them which tools they use, or whether they have any software recommendations. Do they advise that you watch any particular videos or films, or read certain books? Having these conversations with people in the industry will be immensely helpful, and you'll often find that the football data and analytics community are more than willing to give you a hand.
If you want to increase your chances of getting help from someone more experienced, see if there's any way you can help them! This will make you stand out from everyone else who is asking for help.
This is a big one. The idea of learning how to code might seem intimidating and alien to you, but it will give you huge advantages in the world of football data. In fact, these days it's more or less essential. The good thing is, there are loads of (often free) online resources for learning how to code.
There are two main coding languages associated with sports analytics; R and Python. Online resources and sites such as FC Python and FC RStats, Friends of Tracking, and Ahmad Lala's Python course can provide useful support in this area. And while coding may seem a tad overwhelming to begin with, most analytics fans say that it's not as difficult as they initially thought during their first experiences with it. For an easy introduction, play around with tables, graphs and data presentations on Excel; this can give you a good foundation from which to learn coding. If you then pick the right educational resources and spend some time absorbing them, you'll likely pick things up quickly. For more on the role of coding in football, check out our interview with smarterscout founder Dan Altman.
Profile of Real Sociedad's Alexander Isak (Source: smarterscout.com)
It's important to remember that there are a wide variety of different job types available within the world of football analytics, all requiring slightly different qualities and interests. For those with mathematics backgrounds and a number-driven mentality, hard data analyst roles could be best, while people who are better at examining match footage and identifying tactical trends and strategies from them could be well suited to video analyst work. Both these roles can be done remotely and on a freelance or ad-hoc basis, but plenty of clubs also like to have in-house specialists in staff too — you can check out such opportunities here.
Data and analytics employees don't always work for clubs either; companies and data suppliers such as StatsBomb, Wyscout and Sportradar employ people in a variety of roles, while sports publications such as The Athletic regularly advertise opportunities within their data team. Keep your eyes peeled, and read as much as you can about the wide range of football analytics positions out there. There's something for everyone, as long as you're passionate enough.
Our last point is pretty simple, but it's something that holds many people back. Just get started! Write scout reports, come up with player profiles, analyse statistics, be creative and post your own research and content as regularly as you can. The first data and analytics work you do will be far from your best, but the longer you wait, the longer it will take for you to progress. Ultimately, the more you write, the better you'll get at it — it doesn't matter how big the audience is, or whether you have an audience at all. Just get started!
Hopefully, this article has given you a better idea of how to get started in the world of football data and analytics. It can seem a super complicated field at first, particularly given the importance of coding and data to most analytics jobs. However, there are a wide variety of tools and resources available for those interested in exploring this interest. Read books and articles, watch videos, listen to podcasts, learn to code, speak to experts and peers, and most importantly, just get started! Once you get into your stride, you'll find there are a wealth of opportunities out there.
If you decide you want to jump in with both feet and invest in a Football Analytics course, join our Football Education Hub and access the largest database of analytics courses on the market and make sure you get the course that’s right for you.
Want to find out more about how to get a job working in football? Check out our 11 tips to get started in the football industry.
Fred Garratt-Stanley is a freelance writer and long-suffering Norwich City fan with experience reporting on football for a number of titles. He also has a background in music and culture journalism, with bylines in NME, The Quietus, Resident Advisor and more. Currently, he's working as a content writer for a variety of online health and fitness publications.