New project on the use of data in the sports sector
Data analytics has seen a sharp rise in its prominence and place in society, especially since 2017 where it was labelled by Forbes as ‘the most valuable’ commodity in today’s business world. When looking at the analytical approaches used by businesses such as Amazon, Tesla and Facebook, there are huge data driven processes that allow for multi-faceted benefits, ranging from increased profitability to waste reduction. Combine this data-driven approach with a data-rich business such as sport, and the potential for improvement regarding on the pitch results and off pitch operations is great. For example, the famous Oakland Athletics whose ‘Moneyball’ approach using data allowed them to beat teams higher in the US baseball league and who had far greater resources. The term Moneyball refers specifically to Oakland’s approach to player recruitment, where the use of differing statistics and data identified under-valued players in the transfer market, to help build a low cost but high performing team.
Unfortunately, however, within sports such as football (soccer), data is still not fully operationalised to its full potential. The potential for making greater use of data analytics has been demonstrated by traditionally smaller clubs such as Brentford FC making a meteoric rise from League One to the Premier League within 10 years using a Moneyball approach. This suggests that other clubs are not optimising their data to its full potential.
The Business Transformations Research Centre at Manchester Metropolitan University is providing support for a new research project to find out how is data operationalised in sport and how can it be leveraged more effectively. The literature has shown an enormous research focus around technology innovation, but that attempting to capture data points has until now been difficult to achieve. The existing evidence base has focused on how we can transform and make sense of sports data through a quicker, more automated process.
However, whilst important, this topic area is yet to find itself as a mainstay in a sports club’s tool kit. Why is this? This appears to be particular to the nature of sport in general and to so-called ‘elite’ sport. Naturally highly competitive and reluctant to share trade secrets and knowledge transfer, elite clubs are effectively closed off from research. They do not appear to contribute to–nor draw from– an established collective evidence base of best practice.
The project seeks to address this omission and is led by Tom Mitchell, Researcher at Manchester Metropolitan University, and conducted in collaboration with Manchester Met colleagues Dr Marina Papalexi, Dr Iain Reid, and Professor David Bamford. The research will help to bridge the gap between laboratory research and the real sporting environment. In creating a tangible strategy and application model for how data analytics can be implemented into systems, it will provide wider impact by showing how current research can be added to football club systems and infrastructure to incorporate a more data-driven approach.
