How to Deal with Sports Activity Datasets for Data Mining and Analysis: Some Tips and Future Challenges

How to Deal with Sports Activity Datasets for Data Mining and Analysis: Some Tips and Future Challenges

Samo Rauter (Faculty of Sport, University of Ljubljana, Ljubljana, Slovenia), Iztok Fister (Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia) and Iztok Fister Jr. (Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia)
DOI: 10.4018/IJAPUC.2015040103
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Abstract

The aim of this paper is to briefly present the fundamentals of sports training to computational intelligence community and present a short description on recently released sport activity datasets for data mining and data analysis. Training plan for professional mountainbiker is presented in details. Moreover, tools for parsing sport activities files are discussed. Finally, tips and open challenges are exposed that refer to the data analysis and data mining of the proposed sports activity datasets.
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2. Fundamentals Of Contemporary Sports Training

As mentioned earlier, sports applications can analyze the data of our training sessions, organize virtual competitions or even help us in sports training advertising. However, the main question is how sport applications can contribute in the more effective process of sport training (Rauter, 2014).

The definition of sports training is based on the scientific and pedagogical principles of the planned systematic activities or processes in order to obtain the highest achievements of the trained in the particular sports discipline (Ušaj, 2003). The final effect of the systematic training process can be manifested as:

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