15 February 2020

The network secret behind Barcelona’s greatest football team

Guardiola’s 2009 F.C. Barcelona. Messi, Xavi, Iniesta, Busquets, Henry and Puyol. Possibly the best team in history. Is such greatness magic or could it be backed by network science? Could the same tools we use to understand organizations be also used to decipher the utter dominance of Guardiola and Messi’s Barcelona?

Photo: Source = http://www.flickr.com/photos/globalite/6625827591/ 

 

Simply the best

Anyone taking the 2008-09 Champions League Final and Barcelona’s humiliating crushing of Manchester United, understood that they had witnessed a new and winning way of playing the game. Pep Guardiola’s Barcelona side of the 2008-9-10 seasons won an unprecedented six buckets, including La Liga and Champions League. And they did it in dominating fashion. Guardiola’s team revolutionized the game with its possession-oriented game, short and quick passes between players that were situated very closely together, with immediate pressure on the opposition when they lost the ball. This tiki-taka football was the antithesis to Jose Mourinho’s defensive teams (Inter won the Champions League the following season) and an inspiration to a new generation of managers.

 


Photo: Tsutomu Takasu, Flickr CC

 

Though leader. Pep Guardiola built on Barcelona’s culture to build a one-of-a-kind network – and win 6 trophies in one year. If there’s any means to crack the Barcelona signature style and go beyond traditional metrics such as shots and passes, it must be the network analysis. Network science is methodology of how any entity – good or bad – spreads between nodes in a network. It can be applied to diverse problems such as the spread of a pandemic, war, fake news, forest fires and financial panics, but also the inner mechanics of success. In a paper published in Nature, Spanish scientists Buldú, Busquets, Echegoyen & Seirul.lo, explain how F.C. Barcelona team came to be so dominant. Being network leadership enthusiasts ourselves, we bring you the conclusions of that article.

 

The network of Xavi

Each player is represented by a node. A link is created every time players pass the ball, and becomes thicker with every pass. You can also see the player’s position on the field. By isolating groups of 50 passes, the analysis uncovers how the game evolves. Certain players are more ‘central’. And certain patterns of play can be found more common. Barcelona’s famous passing triangles are examples of those patterns. Beldú and colleagues began by generated passing networks for every team in the 380 games played in the 2009-10 La Liga season. The paper explains how network measures such as the clustering coefficient could determine that triplets of players pass the ball far better in Barcelona than in any other team. The average shortest pass through the team is shorter and the strength of the network (the so-called eigenvalue of the connectivity network) is much higher. By analyzing the evolving 50-pass networks you can see how the team’s centroid – its average field position – changes during the game, with Barcelona’s higher up the pitch and much more stable than the competition’s. Barcelona’s ratio of advance – the likelihood of the team’s passing direction – shows a much higher likelihood of horizontal passes. Meaning they pass the ball back and forth looking for attacking opportunities. Xavi, the brilliant midfielder, had the highest centrality of any player.

 


 

Greatness as a network. The researchers found the network metrics that enhance the probability of scoring/receiving a goal, showing that not all teams behave in the same way and how the organization Guardiola’s F.C. Barcelona is different from the rest – including its clustering coefficient, shortest-path length, largest eigenvalue of the adjacency matrix, algebraic connectivity and centrality distribution. We have added a small company network to connect the Barcelona approach to business. An organization that supports other organizations with digitalization. Xavi’s centrality in Barcelona is parallel to CEO’s centrality in a company.

 


 

Reasons for that may be similar to Xavi’s playmaking, but are often more linked with the need to control everything, which is why CEOs are more likely to be blockers than playmakers.

 

Can the network analysis identify footballing weaknesses?

«The likelihood that Barcelona will concede a goal increases with the dispersion of players around the team’s centroid – in other words, goals happen when the players spread out. That suggests an Achilles’ heel that other teams could attempt to exploit», Technology Review states. The fact is other teams behave very differently, meaning network analysis cannot be used to copy Barcelona’s strategy and success. Like in any network, understanding culture and implementation are crucial. It is easy to imagine the many ways network analysis can add interesting dimensions to sports analysis, for instance, to discover how single players influence a game or how changing positions can influence a player’s performance. The new Netflix series «The Last Dance» about Michael Jordan’s great Chicago Bulls teams of the Nineties, centers for a while around coach Phil Jackson’s famous triangles. It would be interesting to see network analysis applied to the NBA. Meanwhile, Network Leadership is continuing to show leaders and employees how to view their organizations as a mix of the formal and informal ties that make the organization tick and create the occasional Barcelona magic.

 

Sources:
– Defining a historic football team, Nature article
– Network science reveals the secrets of the world’s best soccer team, MIT Technology Review
– How Network Theory Is Revealing Unknown Patterns in Sports, MIT Technology Review