Recently, Neymar switched clubs for the astronomical amount of 263 million dollars. With this, he is considered to be one of the best football players in the world at the moment.
In 2013, I organized a seminar about entrepreneurship where I met Giels Brouwer, current CEO and founder of Scisports. The organization is involved in the combination of data and football, a field that seems very interesting with the current developments in artificial intelligence.
The current use of data in football
SciSports assisted in the transfer of Memphis Depay from Manchester United to Olympique Lyon. Based on a matching principle between the player’s preferences and the characteristics of the French league and its clubs, the transfer became reality.
Looking at Manchester City, a club in the English league, we can see a different use of data. The club uses machine learning to improve its performance. It analyses thousands of matches and individual player statistics to improve the individuals within the team, e.g. to prevent injuries and come up with the best game plans.
Robots vs. humans
A more extreme form of artificial intelligence and football is robotics and football. In 2013, the organizer of Robocup Soccer, an international football tournament for robots, predicted that robots will be able to defeat humans by 2050. However, in 2016 this was already done in a 5 vs. 5 match. Though these were definitely not the world’s best football players, it sets the tone for the developments going on at the moment.
The future of football and its players
Combining the two – earlier mentioned – developments of artificial intelligence within the world of football, it is unsure what the future will look like; will humans be replaced by robots or will we use the tools available to improve our humans? In other words, will the next $263 million dollars be spend on a player or would it be better for a club to invest this amount of money in a machine learning tool to train its current players and make them the best ones on the planet?
– https://www.cnbc.com/2017/08/17/what-neymars-263-million-transfer-fee-means-for-the-future-of-soccer.html
– https://www.linkedin.com/in/giels/?ppe=1
– http://www.scisports.com/news/2017/scisports-aided-in-memphis-move-to-olympique-lyon
– http://www.silicon.co.uk/data-storage/bigdata/man-city-digital-tech-football-201114/2?inf_by=59ba9a65681db84c3b8b46f0
– http://www.ibtimes.com/man-vs-machine-face-soccer-field-2050-robocup-soccer-hopes-so-1329033
– http://www.dailymail.co.uk/news/article-3563052/They-ball-Scientists-engineer-robots-BEAT-humans-football.html
– http://www.silicon.co.uk/data-storage/bigdata/machine-learning-data-206762?inf_by=59ba9a65681db84c3b8b46f0
Interesting thoughts Bart. With all the data being collected on football, do you think machine-learning could effectively be used for sports-betting? By assessing thousands of games, you could potentially bet on teams based on how they match up on certain statistics (passes completed on other teams half, shots taken on average, etc).