The World Football Summit hosted its fourth edition of the Football Innovation Forum around the final of the UEFA Champions League 2024 in London. At Tottenham Hotspur’s impressive new stadium, experts from a wide range of football industries came together to discuss the sport and its technological development.
The topics of the conference were obvious. Digitalisation, big data, artificial intelligence – but how are they actually applied in clubs, leagues and associations? Representatives from all over Europe provided exciting insights, opened up new perspectives and confirmed many of my impressions from numerous discussions over the past weeks and months.
Javier Tebas, President of La Liga, has described just how extensively AI is already being used in one of Europe’s top leagues. Machine learning and other tools have already been used in Spain’s top flight for seven years. A separate department within the league is now responsible for ensuring that AI is used consistently in the various organisational units. Tebas therefore speaks of a kind of AI police force that also organises training sessions for the various tools, from ChatGPT to Copilot, and checks the skills of employees. ‘It’s about changing the mindset,’ he says.
The diverse use cases for AI solutions within a football league are remarkable. Tebas spoke of ‘knowledge of prediction’ and also addressed specific solutions. In TV broadcasts of matches, AI solutions provide advanced statistics that predict moves and tactics. AI tools help to predict suitable kick-off times in the planning of the match schedule, for example by predicting spectator behaviour in remote markets such as Asia. In order to improve the fan experience in the stadium, La Liga is also working on providing individual fans with even more targeted and personalised information and encouraging them to buy tickets or shop online. However, the quality of the data is crucial, emphasises Tebas.
From a sports perspective, he sees many benefits for teams and coaches in particular that will only be realised in the coming years. He spoke about predicting injuries or suggesting player substitutions during a match. ‘The game will never be completely predictable, but we can improve the game and make players more efficient,’ says Tebas.
Reporting on data, forecasts and development, Beri Pardo and Neil Cuijvers also had plenty to say. Pardo is the sporting director of Hull City, where they are preparing to return to the Premier League after difficult years in League One and the Championship. There was a clear approach at the beginning of the development. ‘The clearer you are about your style of play and your club philosophy, the easier it will be to find what you’re looking for.’ A sentence that sounds familiar. Especially when you look at the recent development of Bayer Leverkusen under Xabi Alonso in Germany or that of SK Sturm Graz under Andreas Schicker or Christian Ilzer in Austria.
With a clear plan, you can also find the best players for the job, emphasises Pardo. There are countless scouting tools to help with the search. Hull City used one to discover Jaden Philogene, even though the left winger has been no stranger to English football in recent years. Pardo recognised his potential, which he was unable to exploit at Aston Villa or Cardiff City: ‘We look at players based on their potential and their potential with us. To do this, we look at certain data depending on the position and compare it with our ideas in our team.’ In order to know exactly which player profile you would like to have, you also need precise data from your own existing team, he emphasises. Data that our partners continuously collect in the skills.lab Arena and thereby not only improve their own players, but also have precise player profiles. This also gives the clubs a decisive advantage when scouting potential new players.
The development of KVC Westerlo, which chief scout Cuijvers reported on at the Football Innovation Forum, is similarly successful. ‘We deliberately look at underrated leagues and follow predefined KPIs. For example, if a young striker in South Africa scores in his first match or a right-back in Canada makes five progressive runs in a game, we receive an alert via the Real Metric Analytics platform,’ said the 37-year-old. These alerts lead to specific scouting, the specific scouting leads to a comparison with the data of the existing players in the team and then hopefully to the perfect transfer. A principle to which we have also committed ourselves in a similar form at skills.lab. Our partners collect objective data on the technical and cognitive performance of players in Arena, Studio and Cube, which they then use for transparent player comparisons. Especially in the youth sector, the data that leads to these alerts via scouting platforms is often not available. The skills.lab systems create this data by making it possible to measure talents individually and holistically based on their abilities.
Major topics such as AI and big data in football require clear awareness and concrete action – this became clear to me once again in discussions with people from various areas of professional football at the Football Innovation Forum in London. You have to know the right data and be able to contextualise it in order to gain something from it. Out of countless AI tools, you have to find the ones that you can customise for yourself and make you more efficient in your daily work. This is the only way anyone, whether a company, association or club, can make sustainable improvements.
