How whatsapp helps football to learn from AI

Football analysis has taken a long way since the intoxicating days of the first expected goal model.

With progress in event data, data tracking data and even limb-tracking technology, the value of back-to-goal actions and off-ball runs are just as measurable as their target.

From machine learning to neural networks, the newest trend is artificial intelligence (AI). There are many subsections from AI, but the core principle is simply the capacity of a computer to perform tasks that we usually associate with people.

Work in this space has been established for many years. Zone7 is, for example, an AI company that works together with clubs to predict a risk risk using machine learning methods.

On the field, semi-automated exterior is managed by AI-analysis to check the movement of the ball and player to generate his decision.

At club level, Liverpool recently worked with Google DeepMind to create a tacticai platform that improves the strategy for defensive corners.

But the biggest impact of analyzes in football is from a recruitment perspective. Investment has created research teams that operate more on a start-up of Silicon Valley Tech than a club data department.

Unfortunately, not everyone in the football food chain can build infrastructure with a limited financial budget, but does that start to change as AI grows in prominence?

The rise of generative AI thinks that Chatgpt has transformed how many people deal with technology. With the risk of becoming too technical, this method is supported by large language models (LLMS) that are trained on an enormous amount of data to recognize patterns, allowing them to produce content, including text, images or audio.

SOCCERMENSS XVALUE AND SENTIENSPORTS SCOUTGPT are two examples of generative AI models that are used at Scouting Player. Although the statistical analysis in the background can be complex, these platforms can enable users and ask questions about a specific player in simple football language.

For David Sumpter, co-founder of Analytics Company twelve football, the democratization of such platforms means that Data Science is no longer reserved for those who are active at the elite level. In modern times, clubs have the opportunity to chat with the equivalent of a data scientist by simply clicking on an app on their phone.

Some of the largest clubs in the world go together, but it can be used by clubs in the National League of League Two, Sumpter told Athletics. In essence, they can have a Data Science department that is at the level of a Premier League club. That's the dream.

With customers in the top five European competitions, the newest release of Twelves is the AI-driven analysis tool, earphone, delivered via WhatsApp. It enables clubs to explore the strengths and weaknesses of a player, initially without a number in sight.

Although data and visualizations can be questioned at your own discretion, Sumpter spoke about the platform as the wordilization of complex information in a simple message that a Bitesize analysis of a player offers as if you were chatting with a coach or sports director.

The output has already helped clubs, with Sumpter that emphasized the role it played in the transfers of a League One club in January, whose versions have helped the team to take the table in recent weeks. The same applies to player level, with reports that are regularly read after a game by those in the team to assess their match performances.

No matter how simple it sounds, removing obstacles for access is not to be underestimated when considering the limitations with which some clubs are confronted in terms of basic infrastructure.

With several people who worked within the game, there was a unanimous agreement that WhatsApp was the tool that was most used to work and communicate in the football industry.

The apps end-to-end coding can play part, given the confidentiality and high commitment that exist in football. Encryption tracks personal messages and calls between the communication of the parties, which means that no one else cannot even read, listen or share WhatsApp.

A platform that works via WhatsApp may feel that they are afraid of a scout or data scientist on your journey home. The image below shows an example message exchange when searching for a player analysis of Bournemouth left-back Milos Kerkez.

It is incredible how WhatsApp works in football, most people use nothing but that, Sumpter said.

From an early stage we discovered that we had to send match reports on a PDF (document) via WhatsApp. That is the way the coach wants things to communicate, and this is almost for all clubs of Manchester United to be the smallest clubs in the world. A WhatsApp with a report is what people use.

We quickly acknowledged that this is not only the coaches, but also the presidents. Most people in football are not with a laptop because they are on the field, in the stadium, talk to people. So we had to have a solution that really communicated directly with these people.

When Athletics Recently reported, the transformational effects of AI could threaten the future of traditional explorations, with many afraid of losing their jobs.

The skills needed to evaluate a players subjective, qualitative attributes cannot be replaced by a single algorithm, so that scouts cannot be influenced, but can data scientists be replaced?

There are nuances, but we have seen that many EFL clubs have recently hired and said a data scientist or two, let's do that data sciences and see if we can solve everything, Sumpter said.

Those people will like to work in football, but if another company comes that can build a tool that will do data science within football, that can be a big risk for them. Much of their work can be time -consuming tasks, such as Data Engineering or making data pipelines (to help with their workflow) and it is not easy.

Now much of that work can be replaced by these AI systems, where you can bring all data and send it directly to the decision maker. So the chairman or sports director can have equal access to the information about information.

Although these platforms can analyze and present detailed information, an element of caution is still required when considering whether such technology can replace a human analyst.

The soft skills that accompany roles of data science are where analysts really earn their money, the strengths and weaknesses of certain analyzes are evaluated to form their conclusions.

For the reconnaissance department there are numerous limitations why certain players are not viewed, but now the chairman suddenly has 60,000 options of the data using platforms such as 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 is not only to be able to remove a machine-learning model from the shelf, but also to interpret those models and to look at their limitations that become much more important again.

There is a buzz around AI, but those people who can show critical thinking will be appreciated for a premium.

The democratization of data insight is a hugely positive in the wider football landscape, but data departments should not yet fear for their work.

(Top photos getty images)