Statistics in Sports and Health

Group profile

The Statistics in Sports and Health group (SSH group in short), led by Dr Ioannis Kosmidis and based in the UCL Department of Statistical Science, encompasses both methodological and applied research activity for the development and use of statistical methods in sports and health applications.

The SSH group caters for the steadily increasing requirement for sophisticated statistical and machine learning methods to analyze the unprecedented volume and multiple sources of information from the observation and monitoring of sports and fitness-related activities, and from the frequent tracking of overall health. Due to the diverse nature of such information, the research carried out in the group naturally contributes to and is supported by methodological advances in a range of areas in Statistics (e.g. experimental design, regularized/penalized regression methods, functional data analysis, clustering and classification).

The group comprises of professors, lecturers, post-docs and PhD students (see members) and research activity involves both academic and non-academic, industrial collaborations. Examples of active research topics include:

  • human behavior, health and fitness prediction from movement, physiology, strength and overall health data, from wearable, GPS-enabled, tracking and monitoring systems.
  • investigations on the strong statistical and structural interdependence between health, training, fatigue, and performance in sports.
  • statistical squad optimization algorithms and prediction of injury in team sports.
  • prediction of match evolution from within-match, high-frequency event data in team sports.

The projects page provides details on available PhD, MSc and BSc projects.

The group news page provides information on recent and future activities of the group and its members.