A neural network model approach to athlete selection

Adam Maszczyk 0 1 2 Adam Zajac 0 1 2 Igor Rygua 0 1 2 0 Present Address: A. Maszczyk A. Zajac Szeroka 21/11 street, 40-231 Katowice, Poland 1 A. Maszczyk (&) A. Zajac Chair of Sports Theory and Practice, Department of Methodology and Statistics, Academy of Physical Education , 72A Mikolowska str., 40-065 Katowice, Poland 2 I. Rygua Department of System Analysis in Sport, Academy of Physical Education , 1 Kazimierza Gorskiego str, 80-336 Gdansk, Poland In order to determine the usefulness of neural models in optimisation of recruitment processes, statistical analyses were carried out on measured results of javelin throwers using a full take off. A group of 140 Polish junior javelin throwers took part in the research. In order to choose the optimum combination of model parameters the Hellwig method was used. Linear and multilayer perceptron neural models were constructed and used to calculate combinations of variables. Statistical analysis of the results showed that the linear model was not able to describe precisely the relationship between the dependent variable and independent variables for the investigated group of young javelin throwers. For the investigated group, the perceptron network with a 4-3-2-1 structure gave the best predictive relationship for sports results of the javelin throwers. 1 Introduction Instruments which would allow the determination of personal predispositions for achieving high sport performance have been sought for many years. One approach is the application of successive phases of training with different selection criteria, to determine the contestants chances of achieving high performance [18]. Statistical and mathematical forecasting methods [19] are becoming more and more significant in this area. These methods include multidimensional exploration techniques, which have only been sporadically used in the area of sport science. These methods are mainly applied to recognition of objects and their grouping [27]; concentration analysis; factor analysis; and discriminatory analysis [30]. In the opinion of many researchers, a system of organisational-methodical methods, having complex character uniting pedagogical, sociological, psychological and medicalbiological methods of research should be used for the purpose of construction of a model in the definite discipline or in the group of disciplines of sport [14, 17, 19]. Based on this, Naclerio [18] showed the necessity of filling the gap existing between pedagogical theories, the practice of the sports-training and the competitive model approach in order to create this link. The foundation of this linked approach needs to consider development of competitors in terms of achieved results in comparison with the model criteria. This has become possible as a result of the mathematical formalisation of this problem by authors such as Haykin [10], Tidow [24, 25], Naclerio [18] and Hatton [9]. The use of multidimensional exploration techniques for optimising the recruitment process should allow groups of objects or qualities to be grouped together. Regarding qualities, subsets representing homogeneous taxonomic units can contain similar information on contestants. This allows the possibility of identifying certain types of contestants, who have greater potential. This may lead to the optimisation of recruitment and the definition of different training loads [29]. The occurrence of linear and non-linear relationships between variables has led to the development of artificial neural networks (ANNs) for modelling and prediction [2, 7, 10, 14, 15, 20, 23, 28]. Previous research [1, 3, 4, 9, 12, 13, 16, 17] has covered many aspects of sports result for javelin throwers. Some of this work has shown the greater usefulness of non-linear neural models compared with regression models for prediction [1, 17] with these studies showing that, in most cases, the simplest networks give the best generalisation. Analyses, model construction and experimentally determined results indicate that the quality of prediction of neural models is comparable to that of regression analysis and regression models. At this moment it is important to draw attention to the fact that in further research over the construction of neural models optimising the sports, selection and the prediction of the results of competitors in the javelin throw, more independent variables should be taken into consideration than were covered in this earlier research. Namely the characteristics of the biomechanical analysis of the javelin throw such as speed and angle of the throw out, angle of the attack and characteristics of the postural muscle [24, 25]. Some characteristics directly related to the techniques of the throw such as the degree of muscle stretching before contraction and various start positions were also omitted [4]. The objectives of this research are to cover some of the aspects noted earlier, namely. Will linear neural models be able to describe precisely the relationship between given input and output data in the investigated group of young javelin throwers? Will research results show the possibility of using of MLP networks in predicting sports results? What structure of neural model will be able to describe precisely the prediction of the sports result? The aim of this study was to determine whether there is a possibility that the ANNs may be applied to assist in the process of recruiting athletes and prediction for javelin throwing. 2 Materials, methods and study tools 2.1 Participants In order to verify the formulated hypothesis, statistical analysis of measured results for junior javelin throwers was carried out. The measured results from a group of 55 (preliminary modelling) and 85 (new learning cases) junior category javelin throwers formed the initial dataset. The measurements were carried out on the ground of sports facilities of Sports-Schools in Dabrowa Gornicza, facilities of Sports-School in Mysowice, Schoolboy Athletic Club Tornado of Elementary School 31 in Katowice, sports facilities of Interschool Sports Centre in Katowice, facilities of Athletic Club Pogon Ruda S laska, sports facilities of Athletic Club Pomien Sosnowiec and in the laboratory of Chair of System Analyses in Sport in Academy of Physical Education in Katowice. Participants were selected at random from candidates with less than 2 years experience in javelin throwing. The basic criteria of the selection were the period of training (approaching 2 years of the throwing training from 2002) and their informed consent and active engagement in the training process. The intensity of training in terms of number of sessions per week that each competitor undertook was an experimental variable due to different methods of training used in the individual centres. 2.2 Data collection and tools of the statistical analyses The characteristics of the first group of 55 16- to 17-year-old javelin throwers were used to build the neural models and were measured t (...truncated)