CAN DATA & ANALYTICS DELIVER WORLD CUP GLORY?

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Posting date: 6/18/2018 10:07 AM
We are living in an era consumed by Data and Technology. Companies of all sizes are putting analytics at the forefront of their businesses to understand their data and be one step ahead of their competitors, and sport is no exception to this trend. 

Within the last decade sports clubs of all kinds have been investing in analytics to provide insights focused around the development of training programmes, injury prevention, recruitment and the big one - competitor analysis and predictability. Whilst many of us I’m sure are intrigued to know about how data is used in the more unlikely sports like kayaking or swimming, the hot topic at the moment is the FIFA World Cup. 

With the World Cup underway team analysts will be bumping up the overtime hours with last minute panic requests from Managers. This is the moment everyone’s hard work comes into question and those pre-match reports that have been worked on for months in advance are finally being used. 

Taking a look inside the minds of the likes of Gareth Southgate, Joachim Löw and up until a few days ago Julen Lopetegui, we can take a good guess at how they are using big data to make their lives a little easier when preparing for the forthcoming matches. 

The crucial piece to the puzzle is the opposition report. In addition to stalking the profiles of each and every player, manager and referee that the team could possibly encounter in the tournament, the analysts will scrutinise hundreds of thousands of pieces of KPI data to investigate trends and make comparisons to counteract their opponent’s tactics. A key method of research that is making its way into the world of Sports Performance Analysis is the theory and application of Network Analysis. 

Network Analysis is the dream for big data and machine learning enthusiasts as it uses algorithms to provide statistical outputs relating to the relationship between players, based on their passing matrix, and contains thousands of pieces of passing data. It is a great way to determine the key playmaker within a team, passing patterns and can help to confirm style of play. For example, if there is a strong passing connection between the central defender and the striker, it is very unlikely that the team will focus on applying a possession style of football to their game. 

If we take a look back to Spain’s team data and network diagram from the 2010 World Cup we can distinguish that their number 8, Xavi, was the key playmaker who a lot of the players relied on. From determining this, coaches can now look further into why this is the case and how to prevent passes being received by Xavi in order to put the team out of their comfort zones.

Filipe Manuel Clemente and his team are key researchers within Sports Analysis and used a network analysis approach to characterise elements of successful and unsuccessful teams. Their findings from their 2014 World Cup study suggested that teams who adopt a possessive style of play with a higher network density and number of links, were more likely to be successful and score more goals. Further research into the German team during the 2014 World Cup revealed their approach of attack, as well as highlighting the prominent players within the team – a key bit of information for the manager when planning his tactics! 

A lot can change within four years so it’s not just about looking at old World Cup data, analysts will be drawing on data from every friendly game, tournament and league fixture from the last couple of years that they can get their hands on. The insights that the sporting world can gain from their data is immense and it is the primary way to eliminate subjectivity and emotion from an industry that is full of passion. 

Network analysis is one of the many elements that will be considered in the pre-match preparation for world cup teams. It will be interesting to see how many teams stick to their history and follow their trends and how many surprise us and break out into a new style of play. 

If you are interested in a job as a Data Analyst then discover more and start applying here.

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