Data Analytics in Football
- footballytics
- 19. Feb. 2022
- 8 Min. Lesezeit
Aktualisiert: 24. Apr.
You are probably reading one of the most visited Data Sports Analytics blog with over 900 reads per month. Smart and successful use of data goes far beyond simply buying tools.
We have many years of experience in football coaching, game development, game analysis and datascouting. We also bring business innovation, design thinking and product development expertise to the table. We support you in exploring and utilizing the full potential of data.
Digital transformation is one of the great challenges of our time. On a smaller scale, this also affects sports and football. Advancing technology development and digitalization have led to a rapid increase in measuring devices, data collection, data volumes and possibilities. Meanwhile, a separate industry has been established dedicated to the collection, analysis, interpretation and marketing of performance and match data.
The world's major data companies, IBM, Intel, SAP and Microsoft, are competing for the best data analytics tools and also using sports as a demonstration domain for the power of their brand & products. Various data providers such as Wyscout, Opta, StatsBomb, Skillcorner and more are offering ever more comprehensive and better data.
Analytics in football is not such a young discipline. Already after the Second World War, people started to collect data about football matches and to "play" with it. Of course, this was done with pencil and paper. It wasn't until the publication of "Moneyball" in 2003 : The Art of Winning an Unfair Game' that sports analytics in baseball was actually introduced to a wider audience.
„It’s about getting things down to one number. Using stats the way we read them, we’ll find value in players that no one else can see.” Billy Beane
"Everything is a number" Valeri Lobanovsky
Data Analytics in football Quantitative Analysis (Simple Stats Data)
A decade or so ago, the available data was limited to very basic statistics on goals, shots, number of corners, possession, passes, etc. That's when you can talk about the era of Quantitative Analysis. This data has limited value to the coaching staff. While it may be concerning if a team concedes too many shots or has too little possession. However, knowing this fact does not provide unexpected insights to get better and win more games.
Performance Analysis
The second phase came in the form of performance data. This involves the use of various tracking technologies. Athletes wear a transponder that sends a specific signal to base stations around the field. The data received is then analyzed in real time. Among other things, running performance, sprints and speed are evaluated. This performance data is aimed at improving sports performance in competition. Training sessions are also analyzed, with continuous monitoring of players also used for performance management and injury prevention.
Statistical data (Advanced)
Meanwhile, numerous advanced statistical data are collected for each game and for each player. Wyscout, for example, offers an inexpensive platform with worldwide data including video.
More than 100 individual metrics are recorded for each player. This data, such as goals, shots, duels, passes, success rates, etc., can be used to create detailed analyses, especially for performance evaluation and scouting.
Examples using advanced statistical data:
Data profiles are used by clubs and agencies for a qualitative and quick initial player assessment or the definition of development priorities. You can order all player profiles from any league at affordable prices.
Advanced Metrics: Expected Goals, PPDA, xT an more
The Expected goals (xG) metric (origin is disputed) marked a quantum leap in data analysis. Football is and remains a sport with few goals. That is why the result often does not correspond to the actual course of the game or the chances played out. Expected Goals makes the performance of teams and players more comparable by measuring the number and quality of scoring chances per player. This was followed by many other metrics that we will discuss in later posts. These include, Expected Assists (xA), Expected Threat (xT), Expected Goal Chains(xGC), Expected Threat (xT) and Passes Allowed per Defensive Action (PPDA) and a few more.
Match Events (Event Data)
Another quantum leap in data collection has been match event data. Specialized companies categorize and quantify thousands and thousands of events per match, with a great deal of manual work. For each game event, the associated (x,y) coordinates are also recorded. Several thousand events are thus recorded per game. This event data is valuable for the clubs, because in addition to the quantitative aspect for each action, space gain and importance of the action can be included in the analysis. The interpretation of the analysis is used in match analysis, opponent analysis, scouting and coach scouting. Thus, with data analytics, one is able to analyze thousands and thousands of games simultaneously at the push of a button.
Examples using event data:
Example articles based on event data :
Tracking data
Tracking data is the ultimate in data. In contrast to event data, which includes all ball actions, tracking data includes the position data of ALL players and the ball. This data is captured several times per second (usually 10 to 25 frames per second or more) and provides continuous information about the position of individual players and the ball.
High-resolution cameras around the stadium record the movements of the players and the ball. Image processing software processes this data to track positions in real time.
Because we have information on all players at all times, in-depth, almost unlimited analysis is possible in terms of running routes, speed, spaces and player positioning, player lines and movement patterns.
The disadvantages are the large amount of data and the limited availability.
Resistance in football
Until a few years ago, football was thought to be immune to this trend. Those in charge initially remained very skeptical, even dismissive. Most thought that football was different from American sports and that it would be pointless to analyze match data. But a few dreamers disagreed and set out on their journey despite doubts and rebukes.
90% of the decision makers in football are not data driven
Let's debunk the myth that data or artificial intelligence will replace scouts; instead, let's advocate for scouts using data or artificial intelligence.
Meanwhile, data analytics "early adopters" are reaping the competitive advantage that investment in people and data analytics is beginning to give them: Liverpool, Midtjylland, AZ Alkmaar or Brentford are just a few in the fast growing list. In my opinion, clubs that don't jump on the bandwagon run the risk of falling behind.
Systematic data analysis allows clubs to make better decisions in scouting and match analysis based on data. As for many companies, digital transformation is a major challenge for many soccer clubs. Before you can realize the great potential, you need time and investment in technology, processes and culture.
I recently saw the first 360-degree data cockpit from a La Liga club that provides data for the first team, youth team, medical department, marketing and finance in one place within the club.
Data does not include results
Whether you are a football club or a company from another industry, the same principles apply. Data alone is not enough to discover new things. Data does not automatically lead to insights. Analyzing and interpreting data is hard work.
The challenge is to interpret the data correctly. And this is not about technology, processes and methods, but primarily about football know-how, openness and curiosity. To gain real and valuable insights, it takes numerous iterations between soccer knowhow and data knowhow.
Data itself is not valuable to people. Its the ability to use data who generates insights about things the people care about.
"True discovery consists not in finding new territory, but in seeing things with new eyes." Marcel Proust
Copernicus had the same data as everyone else, he saw, heard and learned the same things as his contemporaries. But he came to completely different conclusions. Because he questioned assumptions that were not up for discussion for everyone else.
You need people, competent people, who can ask the right questions, develop hypotheses and validate them in the data. On the one hand as validation of one's own hypotheses, but also to gain new insights that have not yet been thought of, which in turn raise new exciting questions. Data helps to see things that remain hidden to our mind and eye.
Distortion of Perception
When interpreting data, we often have to dribble out our own perceptions as well. The Confirmation bias is a distortion of perception. The human mind tends to uncritically look for evidence that confirms its worldview. The few salient events tend to be overrated, but are less meaningful than the many many other events. We also often forget to look for evidence that disproves our hypothesis.
You only see what you know
Full article: Cognitive biases in football
Future of Data Analytics in football
We are only at the beginning of the data analytics evolution. What is considered "state of the art" today will be the standard in a few years. But we are far away from algorithms deciding which game system is used, which player is signed, who is substituted out and in. And we should not strive to get there either. Football know-how is and will remain at the center.
It's not just about having the most sophisticated tools or the most accurate data, but also about creating the right processes and fostering a culture that believes in the benefits of using data. Without this foundation, even the most advanced technology cannot deliver real benefits.
Data analysis is accused of taking the beauty and magic away from football. I believe the opposite is true. A better understanding of the game leads to a much richer appreciation of its beauty.
Data Analytics Best Practices
Using data successfully is much more than just using tools. Invest in people and knowhow and not only tools.
Systematically promote and integrate the data view for important decisions. Build a data culture cross your company.
We recommend starting a data project with experts in which you can explore the potential of using data on your own terrain.
Data Driven Scouting
There are no more hidden talents. With the help of data, you can track down and discover players in every corner of the world within a few minutes.
Meanwhile, we scout data for numerous clubs in various European leagues. All clubs now use data to compare and scout players. But only a few clubs exploit the full potential in terms of know-how, skills and process.
It is not possible, nor does it make sense, to try to find the best player with data. Data helps to identify the 50 most suitable players out of tens of thousands (pre-#scouting), among which the best 10 are very likely to be included. Determining the very best from the candidates remains the task of the club scouts with their expertise and experience.
Define specific target player attributes. Identify potential leagues where the kind of player that you are looking for can be found at the right price. Find the the most suitable and best players with smart algorithms. Here the concept of our diversified Datascouting:
Special Offer:
For new clubs or agencies we provide a one-time data scouting for a position or vacancy of your choice. Using advanced algorithms and over 20 fine-tuned position profiles, we identify suitable players worldwide whose strengths and playing style perfectly match your needs.
Compare our results with your own data scouting—or simply experience the quality of our service. Get in touch today!
Here a nice quote from former Liverpool Head of Research & Analytics Ian Graham
New footballytics AI Podcasts
Since October 2024 we have also automatically AI-generated short and compact podcasts full of know-how and do-how in the field of Data Analytics in Football. Listen to our podcasts
Our skills and experience combine deep tactical knowledge with proven innovation methods such as design thinking and systemic approach. This unique blend enables targeted tactical improvements, smart reinterpretations and even entirely new developments.
Editorial: Change the game - Innovation on the pitch
footballytics - we know how to make the data talk
We combine the competences of football tactics, scouting and data analytics and support clubs in interpreting and using data to make better decisions in scouting and match analysis based on data validation.
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