In elite sport, data scientists and sports scientists operate as a team within the team.  It is this partnership, this teamwork and this blending of Sports and Data Science, that is the key to success.   Data in elite sports are typically used for training, tactics and transfers.  John Newell of NUI Galway is involved in using data to help athletes train smarter and recover more quickly.

For example, in soccer there is a fine balance when optimising training load to maximise performance while minimising injury.  As a funded PI in Insight at NUI Galway John Newell led three projects in the use of data in the English Premier League (EPL) to achieve these aims.  The first involved the use of GPS data to help inform training load, the second looked at the role of biomarker testing in terms of player health, recovery and adaptation while the third compared marker and markerless motion capture systems in an EPL youth academy.

Accurate prediction of individual training loads for a planned training session is clearly beneficial.   In conjunction with Dr Andrew Simpkin (Insight Funded PI) and Dr Kenny McMillan (Aspire Academy, Doha) the team used statistical modelling to build a predictive planner for training sessions using historical GPS workload data.  The model accounts for the large variety of training drill types, duration ranges and order.  This tool allows a football coach to obtain instant predictions of the physiological workload for their prescribed training session and to identify players that will find the prescribed session too easy or too difficult.  This work was presented at the Barca Innovation Hub Sports Analytics Conference 2020 as a finalist in the research papers competition. (https://barcainnovationhub.com/sports-tomorrow-day-4/).