ABSTRACT
With large amounts of high-quality performance data readily available, soccer coaches and analysts are faced with the task of interpreting and utilising it. This can be a major challenge for those analysts working in professional soccer, who are confronted daily with masses of complex performance data collected from the training ground or during matches. Not only do they have to correctly interpret this data, but they also have to communicate their results to management in such a way that effective interventions can be made, which will improve team performance. One useful tool that can be used to interpret such data is linear regression, which is a widely used technique for explaining relationships in data, and also for making predictions. This technique can be particularly helpful when analysing performance data in soccer, because many of the relationships encountered are linear. In this chapter, we show how linear regression can be performed using R to identify key performance metrics that influence the success of soccer teams on the pitch.
