The course aims to discuss the knowledge of Sport Performance Analysis considering the data analytics, the notational and video-analysis and the analysis of the complex system in sport science.
During the course the following topics will be discussed:
- Part A – Sport Data Analytics (20 hours): The aim of the module is to introduce fundamental tools and algorithms for extracting relevant information from experimentally collected sport data. Theory underlying such tools and algorithms will be illustrated through direct application to sport data sets collected from a number of case studies including, e.g., (i) the problem of deriving a personalized marathon performance predictor model, and (ii) the problem of on-line estimation of swimming performance parameter during training.
- Part B – Notational & Video-Analysis (20 hours): The aim of this module is to introduce the fundamentals about the sport-specific notation system and the computerized notational analysis. Then it will be discussed the popular use of video with regard to the effects on the skill acquisition process. A practical case of video and notational analysis will be developed in this module.
- Part C – Complex System in Sport Science (10 hours): This module will cover the statistical methods and models able to address complexity in Sport Science. In particular, lectures will focus on the use of Data Analysis and Data Mining techniques, together with algorithmic models from the Machine Learning domain, with the aim of investigating the determinants of sport performance and, among them, identifying the most important ones. Case studies based on the analysis (in the R environment) of real data from different sports will be illustrated.