During last years the use of new technologies, become crucial to define physical performance, tactics, and technique in football. The physical performance during matches is detected, using video-analysis or GPS system. The aim of this study was to compare external load performance from matches between young professional players (U-21) and professional players from European leagues. Data from U-21 was collected using K-Sport 10 Hz GPS (K-Sport Universal, Italy) using as a sample of three Italian youth teams. Data from professional players are taken from video-analysis gathered from the literature. Were analysed 10 games for each youth teams from Italian Primavera Championship 2016/2017. For every game was used one 10 Hz GPS (K-Sport Universal, Italy) for each player, except goalkeeper and were recorded only data from players that perform all the game.

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Abstract:The athletic component in football is nowadays one of the most important factor to determinate the performance. This consideration is part of our study, which aims to evaluate and quantify the difference between the workload of an amateur footballer and an elite one. All this is allowed by match analysis made by GPS evaluation method for amateur and video tracking for elite. The examined teams were playing in 7th Italian league, and we used 10 GPS to track 6 games, 5 for each team. For every team and every game were analysed a forward, a central midfielder, a wide midfielder, a central defender and a full back (Age 25.3 ± 4.2, Weight 74.5 Kg ± 5.3, Height 1.76 cm ± 5.2). In our study, we used a 20 Hz GPS (thanks to Advanced Research Group in Sport, School of Health and Sport Science with K-Sport Universal, Italy) to detect performance data, and then we compared the outcome with matches performance data from elite players gather from scientific literature. Data analysis shows that elite players reach higher values in almost all parameters taken into account. In particular, they obtained higher value in meters per minutes, High Speed Distance (> 16 Km/h), High Metabolic Power Distance (> 20 W/Kg) and in high and very high and acceleration (2 m/s, 3 m/s, > 3 m/s) and deceleration (-2 m/s, -3 m/s, > -3 m/s). This study can be useful to select and catalogue player performance model, in order to better understand the real value of a player, and to help coaches and teams to identify talent, at least in physical values.

In this paper, we present a data-analysis rank-size approach to assess the features of soccer competitions and competitors. We investigate the championships rankings and the teams’ final scores in the most relevant Italian league, the “Serie A”, between 1930 and 2020. We use the final rankings and the teams’ scores to explore the presence of rank-size regimes in the various yearly championships. Besides, we analyse the teams one by one, ranking their performance over the years and using the rank-size law’s parameters to compare their performances across the tournaments. We chose to do so via the Discrete Generalised Beta Distribution, a three-parameter rank-size function. We offer a cluster analysis of the rank-size law parameters based on a k-means algorithm to provide additional insights and capture similarities and deviations among championships and teams. Concluding, we propose a measure of competitiveness within championships and per team. The best fit results are statistically outstanding, and the cluster analysis presents two main clusters capturing teams’ performances and years in which they have competed in the “Serie A”. The competitiveness analysis shows that the teams at the bottom of the championships ranking have obtained decreasing scores in recent years.

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