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Couceiro M.S.,Polytechnic Institute of Coimbra | Couceiro M.S.,Ingeniarius Lda. | Clemente F.M.,College of Education of Coimbra | Clemente F.M.,University of Coimbra | And 3 more authors.
Entropy | Year: 2014

The game of football demands new computational approaches to measure individual and collective performance. Understanding the phenomena involved in the game may foster the identification of strengths and weaknesses, not only of each player, but also of the whole team. The development of assertive quantitative methodologies constitutes a key element in sports training. In football, the predictability and stability inherent in the motion of a given player may be seen as one of the most important concepts to fully characterise the variability of the whole team. This paper characterises the predictability and stability levels of players during an official football match. A Fractional Calculus (FC) approach to define a player's trajectory. By applying FC, one can benefit from newly considered modeling perspectives, such as the fractional coefficient, to estimate a player's predictability and stability. This paper also formulates the concept of attraction domain, related to the tactical region of each player, inspired by stability theory principles. To compare the variability inherent in the player's process variables (e.g., distance covered) and to assess his predictability and stability, entropy measures are considered. Experimental results suggest that the most predictable player is the goalkeeper while, conversely, the most unpredictable players are the midfielders. We also conclude that, despite his predictability, the goalkeeper is the most unstable player, while lateral defenders are the most stable during the match. © 2014 by the authors.


Clemente F.M.,University of Coimbra | Clemente F.M.,College of Education of Coimbra | Couceiro M.S.,Polytechnic Institute of Coimbra | Martins F.M.L.,College of Education of Coimbra | And 3 more authors.
International Journal of Performance Analysis in Sport | Year: 2013

The aim of this study was to inspect the influence of each half of match and the ball possession status on the players' spatio-temporal relationships. Three official matches of a professional football team were analysed. From the players' locations were collected the team's wcentroid, wstretch index, surface area and effective area of play at 9218 play instants. The results suggested that the values of teams' dispersion and average position on the field decreases during the 2nd half of the match. In sum, this study showed that the half of match and the ball possession status influenced players' spatio-temporal relationships, in a way that significantly contributes to the collective understanding of football teams.


Clemente F.M.,College of Education of Coimbra | Clemente F.M.,University of Coimbra | Couceiro M.S.,Ingeniarius Lda | Martins F.M.L.,College of Education of Coimbra | And 2 more authors.
Journal of Human Kinetics | Year: 2015

The aim of this study was to propose a set of network methods to measure the specific properties of a team. These metrics were organised at macro-analysis levels. The interactions between teammates were collected and then processed following the analysis levels herein announced. Overall, 577 offensive plays were analysed from five matches. The network density showed an ambiguous relationship among the team, mainly during the 2nd half. The mean values of density for all matches were 0.48 in the 1st half, 0.32 in the 2nd half and 0.34 for the whole match. The heterogeneity coefficient for the overall matches rounded to 0.47 and it was also observed that this increased in all matches in the 2nd half. The centralisation values showed that there was no 'star topology'. The results suggest that each node (i.e., each player) had nearly the same connectivity, mainly in the 1st half. Nevertheless, the values increased in the 2nd half, showing a decreasing participation of all players at the same level. Briefly, these metrics showed that it is possible to identify how players connect with each other and the kind and strength of the connections between them. In summary, it may be concluded that network metrics can be a powerful tool to help coaches understand team's specific properties and support decision-making to improve the sports training process based on match analysis. © Editorial Committee of Journal of Human Kinetics.


Couceiro M.S.,Polytechnic Institute of Coimbra | Dias G.,University of Coimbra | Mendes R.,College of Education of Coimbra | Araujo D.,University of Lisbon | Araujo D.,The Interdisciplinary Center
Journal of Motor Behavior | Year: 2013

The authors present a comparison of the classification accuracy of 5 pattern detection methods in the performance of golf putting. The detection of the position of the golf club was performed using a computer vision technique followed by the estimation algorithm Darwinian particle swarm optimization to obtain a kinematical model of each trial. The estimated parameters of the models were subsequently used as sample of five classification algorithms: (a) linear discriminant analysis, (b) quadratic discriminant analysis, (c) naive Bayes with normal distribution, (d) naive Bayes with kernel smoothing density estimate, and (e) least squares support vector machines. Beyond testing the performance of each classification method, it was also possible to identify a putting signature that characterized each golf player. It may be concluded that these methods can be applied to the study of coordination and motor control on the putting performance, allowing for the analysis of the intra-and interpersonal variability of motor behavior in performance contexts. © 2013 Taylor & Francis Group, LLC.


Dias G.,University of Coimbra | Couceiro M.S.,Polytechnic Institute of Coimbra | Barreiros J.,University of Lisbon | Clemente F.M.,University of Coimbra | And 2 more authors.
Motor Control | Year: 2014

The main objective of this study is to understand the adaptation to external constraints and the effects of variability in a golf putting task. We describe the adaptation of relevant variables of golf putting to the distance to the hole and to the addition of a slope. The sample consisted of 10 adult male (33.80 ± 11.89 years), volunteers, right handed and highly skilled golfers with an average handicap of 10.82. Each player performed 30 putts at distances of 2, 3 and 4 meters (90 trials in Condition 1). The participants also performed 90 trials, at the same distances, with a constraint imposed by a slope (Condition 2). The results indicate that the players change some parameters to adjust to the task constraints, namely the duration of the backswing phase, the speed of the club head and the acceleration at the moment of impact with the ball. The effects of different golf putting distances in the no-slope condition on different kinematic variables suggest a linear adjustment to distance variation that was not observed when in the slope condition. © 2014 Human Kinetics, Inc.


Clemente F.M.,College of Education of Coimbra | Clemente F.M.,Estadio Universitario Of Coimbra | Couceiro M.S.,Polytechnic Institute of Coimbra | Martins F.M.L.,College of Education of Coimbra | And 2 more authors.
Journal of Human Kinetics | Year: 2013

The main objective of this study was to analyse the distance covered and the activity profile that players presented at the FIFA World Cup in 2010. Complementarily, the distance covered by each team within the same competition was analysed. For the purposes of this study 443 players were analysed, of which 35 were goalkeepers, 84 were external defenders, 77 were central defenders, 182 were midfielders, and 65 were forwards. Afterwards, a thorough analysis was performed on 16 teams that reached the group stage, 8 teams that achieved the round of 16, 4 teams that reached the quarter-finals, and 4 teams that qualified for the semi-finals and finals. A comparison of the mean distance covered per minute among the playing positions showed statistically significant differences (F(4,438) = 559.283; p < 0.001; 2 = 0.836; Power = 1.00). A comparison of the activity time among tactical positions also resulted in statistically significant differences, specifically, low activity (F(4,183.371) = 1476.844; p < 0.001; 2 = 0.742; Power = 1.00), medium activity (F(4,183.370) = 1408.106; p < 0.001; 2 = 0.731; Power = 1.00), and high activity (F(4,182.861) = 1152.508; p < 0.001; 2 = 0.703; Power = 1.00). Comparing the mean distance covered by teams, differences that are not statistically significant were observed (F(3,9.651) = 4.337; p < 0.035; 2 = 0.206; Power = 0.541). In conclusion, the tactical positions of the players and their specific tasks influence the activity profile and physical demands during a match. © Editorial Committee of Journal of Human Kinetics.


de Melo R.J.E.S.,College of Education of Coimbra | Gomes R.A.M.,University of Coimbra
Open Sports Sciences Journal | Year: 2016

Although Nature Sports are considered a growing phenomenon around the world, there is a lack of research and data about the organizations that are developing these activities. The purpose of this paper is to characterize the Nature Sports Organizations operating in mainland Portugal. Data was obtained through an online survey questionnaire applied to organizations which promoted Nature Sports in Portugal, both from private and public sectors, and 166 answers were obtained. Three main types of organizations were found based on their legal form and organizational vocation: sport tourism companies, sport clubs, and associations (environmentalists, cultural, sportive, recreational and others) which were further characterized by their organization profile, supply and demand. The results show significant statistical differences between the different types of organizations regarding their age, number of collaborators, and type of activities offered, as also the number and provenience of the practitioners. The data also enclose implications for the Nature Sports policies and Nature Sports Organizations management that will be discussed. © Melo and Gomes; Licensee Bentham Open.


Ghamisi P.,University of Iceland | Couceiro M.S.,University of Coimbra | Couceiro M.S.,Polytechnic Institute of Coimbra | Martins F.M.L.,Polytechnic Institute of Coimbra | And 2 more authors.
IEEE Transactions on Geoscience and Remote Sensing | Year: 2014

Hyperspectral remote sensing images contain hundreds of data channels. Due to the high dimensionality of the hyperspectral data, it is difficult to design accurate and efficient image segmentation algorithms for such imagery. In this paper, a new multilevel thresholding method is introduced for the segmentation of hyperspectral and multispectral images. The new method is based on fractional-order Darwinian particle swarm optimization (FODPSO) which exploits the many swarms of test solutions that may exist at any time. In addition, the concept of fractional derivative is used to control the convergence rate of particles. In this paper, the so-called Otsu problem is solved for each channel of the multispectral and hyperspectral data. Therefore, the problem of n-level thresholding is reduced to an optimization problem in order to search for the thresholds that maximize the between-class variance. Experimental results are favorable for the FODPSO when compared to other bioinspired methods for multilevel segmentation of multispectral and hyperspectral images. The FODPSO presents a statistically significant improvement in terms of both CPU time and fitness value, i.e., the approach is able to find the optimal set of thresholds with a larger between-class variance in less computational time than the other approaches. In addition, a new classification approach based on support vector machine (SVM) and FODPSO is introduced in this paper. Results confirm that the new segmentation method is able to improve upon results obtained with the standard SVM in terms of classification accuracies. © 1980-2012 IEEE.


Couceiro M.S.,University of Coimbra | Martins F.M.L.,College of Education of Coimbra | Rocha R.P.,University of Coimbra | Ferreira N.M.F.,Polytechnic Institute of Coimbra
Journal of Intelligent and Robotic Systems: Theory and Applications | Year: 2014

The Darwinian Particle Swarm Optimization (DPSO) is an evolutionary algorithm that extends the Particle Swarm Optimization (PSO) using natural selection, or survival-of-the-fittest, to enhance the ability to escape from local optima. An extension of the DPSO to multi-robot applications has been recently proposed and denoted as Robotic Darwinian PSO (RDPSO), benefiting from the dynamical partitioning of the whole population of robots. Therefore, the RDPSO decreases the amount of required information exchange among robots, and is scalable to large populations of robots. This paper presents a stability analysis of the RDPSO to better understand the relationship between the algorithm parameters and the robot’s convergence. Moreover, the analysis of the RDPSO is further extended for real robot constraints (e.g., robot dynamics, obstacles and communication constraints) and experimental assessment with physical robots. The optimal parameters are evaluated in groups of physical robots and a larger population of simulated mobile robots for different target distributions within larger scenarios. Experimental results show that robots are able to converge regardless of the RDPSO parameters within the defined attraction domain. However, a more conservative parametrization presents a significant influence on the convergence time. To further evaluate the herein proposed approach, the RDPSO is further compared with four state-of-the-art swarm robotic alternatives under simulation. It is observed that the RDPSO algorithm provably converges to the optimal solution faster and more accurately than the other approaches. © 2014, Springer Science+Business Media Dordrecht.


Clemente F.M.,Polytechnic Institute of Coimbra | Clemente F.M.,College of Education of Coimbra | Couceiro M.S.,University of Coimbra | Martins F.M.L.,Polytechnic Institute of Coimbra | Mendes R.S.,Polytechnic Institute of Coimbra
Motriz. Revista de Educacao Fisica | Year: 2014

The aim of this pilot study was propose a set of network methods to measure the specific properties of football teams. These metrics were organized on "meso" and "micro" analysis levels. Five official matches of the same team on the First Portuguese Football League were analyzed. An overall of 577 offensive plays were analyzed from the five matches. From the adjacency matrices developed per each offensive play it were computed the scaled connectivity, the clustering coefficient and the centroid significance and centroid conformity. Results showed that the highest values of scaled connectivity were found in lateral defenders and central and midfielder players and the lowest values were found in the striker and goalkeeper. The highest values of clustering coefficient were generally found in midfielders and forwards. In addition, the centroid results showed that lateral and central defenders tend to be the centroid players in the attacking process. In sum, this study showed that network metrics can be a powerful tool to help coaches to understanding the specific team's properties, thus supporting decision-making and improving sports training based on match analysis.

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