How AI and WhatsApp Are Changing the Game
Football analysis has undergone a dramatic transformation, evolving far beyond the early days of expected goals models. With the advent of advanced data collection methods, including event data, player-tracking data, and even limb-tracking technology, the value of aspects like a striker’s back-to-goal actions is now quantifiable.
At the forefront of this evolution is artificial intelligence (AI). AI, in its simplest form, is the ability of a computer to execute tasks that were once exclusively associated with human capabilities. The application of AI in football has been underway for years.
For instance, Zone7 is an AI company helping clubs predict injury risk by using machine-learning methods. On the field, AI analysis manages semi-automated offsides calls. Even at a club level, Liverpool collaborated with Google DeepMind to build “TacticAI”, a platform to enhance strategy for defensive corners. Yet the greatest impact of analytics in football is from a recruitment perspective through the creation of dedicated research teams.
Unfortunately, not every team can afford an infrastructure like this. However, is that beginning to change as AI grows in prominence?
Generative AI, along the lines of ChatGPT, has transformed how many people engage with technology. This method uses large language models (LLMs) trained on an enormous volume of data to discern patterns, permitting them to create content that includes text, images, and audio.
Soccerment’s xvalue and SentientSport’s ScoutGPT are two examples of generative AI models being used in player scouting. While their statistical background might be complex, these platforms allow users to engage with the data and ask questions about specific players, using a simplified football language.
David Sumpter, co-founder of analytics company Twelve Football, feels this democratization of data science means it is no longer exclusively the domain of elite clubs. Now, clubs have the opportunity to message what is effectively a data scientist with a tap on their phones.
“Some of the biggest clubs in the world engage with this, but it can be used by clubs in the National League or League Two,” Sumpter told The Athletic. “Essentially, they can have a data science department that is on the level of a Premier League club. That’s the dream.”
Twelve’s latest release is the AI-powered analytics tool, Earpiece, delivered via WhatsApp, with clients throughout the top five European leagues. It enables clubs to explore a player’s strengths and weaknesses, initially without seeing any numbers.
While data and visualizations can be interrogated at the user’s discretion, Sumpter calls the platform “wordilisation” of complex information into a straightforward message. It provides a bite-size analysis of a player as though you were conversing with a coach or sporting director.
This has already been valuable to clubs. Sumpter highlighted the tool’s contribution to the January transfers of a League One club whose performance has improved since then. The same is true for players, with reports regularly read by the squad to assess their match performances.
Removing barriers to access is significant when you consider the limitations some clubs have regarding their infrastructure. Most people in the industry agreed that WhatsApp is the most widely used tool for communication. The app’s end-to-end encryption might play a part, given the confidentiality and high stakes in football. Encryption secures communications, so only the parties communicating can read, listen, or share them.
A platform that functions via WhatsApp provides the feeling of messaging a scout or data scientist on your commute. Below is an example conversation looking for an analysis of Bournemouth left-back Milos Kerkez.
“It’s incredible how WhatsApp works in football — most people don’t use anything other than that,” Sumpter said. “From an early stage, we found that we needed to send match reports on a PDF (document) via WhatsApp. That is the way that the coach wants things communicated, and this is pretty much across all clubs — from Manchester United to the smallest clubs in the world. A WhatsApp with a report is what people use.
“We recognised quickly that this is not just the coaches, but the chairmen too. Most people in football don’t sit with a laptop because they are out on the pitch, at the stadium, talking to people. So we have had to have a solution that really communicated directly with these people.”
As The Athletic recently reported, AI’s transformational effects could threaten traditional scouting and some scouts fear job losses. The skills to evaluate subjective, qualitative attributes of a player can’t be replaced by a single algorithm, so scouts shouldn’t be too affected, but could the same be said for data scientists?
“There are nuances to it, but we have seen that many EFL clubs have recently hired a data scientist or two and said, ‘Let’s do data science and see if we can solve everything’,” Sumpter said. “Those people will be happy working in football, but if another company comes along that can build a tool that will do data science within football, that can be a big risk for them. A lot of their job might be time-consuming tasks like data engineering or creating data pipelines (to help with their workflow) and it is not easy.
“Now, a lot of that work can be replaced by these AI systems, where you can bring in all the data and send it directly to the decision-maker. So the chairman or sporting director can have equal access to the information at hand.”
Though platforms can analyze and present detailed information, a measure of caution is still required when considering whether such technology can overshadow human analysts. The soft skills possessed by those in data science roles are where analysts truly add value, evaluating the strengths and weaknesses of certain analyses to make informed conclusions.
“For the scouting department, there are plenty of restraints as to why certain players are not being looked at, but now suddenly the chairman has 60,000 options from the data using platforms like this, so you have to get that balance right,” Sumpter said. “It is still important to have a data scientist in the club who can offer that experience or balance. It’s not just about being able to pull a machine-learning model off the shelf, but being able to interpret those models and look at their limitations — those skills are going to become much more important again. There is a buzz around AI, but those people who can show critical thinking will be valued at a premium.”
The democratization of data insight is a significant positive in the broader football landscape, but data departments have time to be ready for what’s coming.
Mark Carey is a Data Analyst for The Athletic. With his background in research and analytics, he provides data-driven insight across the football world. Follow Mark on Twitter @MarkCarey93
