PlaymakerAI: Maximising The Benefits of Football Data Analytics
This interview is featured in the global magazine fc business.
Ola Lidmark Eriksson lecturing during his Masterclass: "Data-driven success for football leaders" at the Thinking Football Summit in Porto, Portugal. September 2024.
Ola Lidmark Eriksson, the founder of PlaymakerAI, stands as one of the most influential pioneers in football data analytics. In this interview he shares insights on how clubs can maximise their use of football data for scouting and analysis.
In a world where football data is becoming increasingly central to a club’s success, Ola Lidmark Eriksson, the founder of PlaymakerAI, stands as one of the most influential pioneers. With nearly a decade of experience in football data analysis, Ola has played a crucial role in transforming how we understand and utilise data in the sport. From his early collaborations with the Swedish club Östersunds FK (at that time coached by Graham Potter) to his groundbreaking work as the first TV studio expert focusing on football data, Ola has consistently been at the forefront. At PlaymakerAI, he has been the mastermind behind the development of a revolutionary platform that gives coaches, scouts, analysts and agents the freedom to craft tailored analyses based on their own football philosophies.
Which cases have you seen where the use of football data has created the most impact in the football world?
In my daily work at PlaymakerAI, I regularly hear success stories from our clients, such as when they have signed a player that was scouted through our platform, identified a weakness in an upcoming opponent through analysis in our platform, or having made progress in player development using data in the process. But to answer your question, use of football data makes the most impact when it is an integrated part of the club’s way of working. For example, integrating use of data as an integral part of the club’s scouting process, will not only make the club more successful on the transfer market, but also make the process more efficient – for example the club will not have to allocate as much money to the budget for onsite scouting travels. Another example could be a club where even higher decision-makers work with data-driven decision-making, which can lead to more long-term decisions regarding, for instance, whether or not to retain the coach.
Having been in the industry for so long, you have surely seen a development in how data is used over time. Do you think football clubs today are maximising the opportunities available with data analysis or is there more to be done?
Short answer: There is definitely more to be done for most clubs!
The range in usage is, of course, large – from some major clubs with large, dedicated analysis departments to several elite clubs in Europe that at most look at data in Wyscout occasionally. Regardless of where the club falls on that scale, there are some general areas where I think the use of football data can be developed.
I still see that – even in many of the clubs that invest resources in football data – the use of data doesn’t make any real difference in reality on the football field or in the scouting process. Often, I think this is because the gap is too large between those who develop the analysis tools and analysts versus the actual sports decision-makers, the coach and the sports director. At PlaymakerAI, we place great importance on making data comprehensible and usable, and on working very closely with our customers to continuously receive feedback on how our products are used in the football reality. The fact that we have several team members with player and coaching backgrounds also contributes to creating value that can actually be utilised on the football field.
Football is a complex sport, which means that the analysis is also complex. Furthermore, football data analysis fundamentally requires a statistical understanding. I believe this is an explanation for the gap between analysts and sports decision-makers – it has been challenging to communicate football data-based insights in an understandable way. We at PlaymakerAI are now in the process of developing a chatbot – going forward, it will be possible to talk to our platform as if you were talking to a human. We believe this will revolutionise the usability of football data in the future!
Finally, I believe that decision-makers need courage. Even if they embrace insights from football data, they also need to dare to change their way of working. For example, we might not need to send a scout too early in the process to watch a player on-site if we have solid data showing that the player matches the profile we are looking for.
As you mentioned, some major clubs invest significant resources in analysis and have their own data departments. Is this something more clubs should follow?
If you have ample resources, you naturally want the analysis of football data to provide as much value as possible for your own club. If you have your own data department, you can create analyses tailored entirely to your club’s football philosophy. As a big club, if you can maximise the use of football data, there are obviously significant economic benefits to be gained—every successful transfer and every point earned is worth a lot of money. I can therefore understand why these clubs invest heavily in building their own data departments.
However, I must point out that I question whether it is part of a club’s core business to hire, for example, data engineers. I have more than once seen clubs totally reinventing the wheel, basically trying to build a “killer app” but from a tech perspective it is extremely naive to believe that it will be up to par with the best tools on the market. I may be biased, but in my view, it is companies like ours, with 10 years’ experience and an extremely specialised team that have the opportunity to constantly stay at the forefront of developing football data products. Clubs should, in my opinion, instead focus their resources on becoming really good at understanding how to use football data, how their processes should be influenced by football data, and how football data can make a real difference on the football field.
The need to be able to create customised analyses entirely based on each club’s way of working and football philosophy is a key factor for any club. In the analysis platform that we at PlaymakerAI launched just under a year ago, there is precisely the opportunity to completely customise your analyses based on your own football philosophy. Through this platform, the club gains access to advanced data analysis of large amounts of football data, fully tailored to its own club, in a very simple way.
So my answer to the question is: No, you do not need to hire data engineers and create your own data analysis department. Whether you are a big club or a smaller club, you can, through a platform like PlaymakerAI, get as effective a data department as the big clubs. Once you have access to a platform like PlaymakerAI, then invest your resources in understanding how football data can give you the greatest advantage. Educate your analysts, scouts, sports directors and coaches in data analysis. In this way, you can make football data a real success factor in your club!
And, finally, what is your favourite metric/KPI?
The actual answer to that is a bit unexciting—it depends on the purpose of using the metric. Our platform allows for the analysis of around four hundred different KPIs, and each has its purpose in the right context. But of course, I have to mention the KPI that I named myself—the Lidmark Index. It is a KPI that measures a player’s consistency over time. Apart from that I myself am a bit lazy and like the “meta” KPIs. The ones with one number that tell the same story that perhaps 10 others do more or less the same. Action Value, Expected Threat and our Transfer Index are examples of that.
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