Gonçalo Dias

Network analysis and intra-team activity in attacking phases of professional football

In this study we sought to verify whether network analyses could be used to identify key players in attacking phases of a professional football match and establish the main interactions and preferential linkages between attacking teammates during competitive performance. For this purpose, we examined circulation of the ball on field during randomly selected attacking phases of play in a video-taped Portuguese Premier League match. We observed six matches and notated 1488 collective attacking actions, including: passes completed, passes received, and crosses involving a total of 4126 intra-team interactions (eg., 2063 passes and crosses performed and 2063 passes and crosses received). We used Amisco® software to perform quantitative and qualitative analyses of the attacking actions. Results indicated how key individual players are instrumental in orchestrating team performance, exerting a powerful influence in creating attacking patterns of play. Our findings may help coaches and sports scientists quantify the contributions and interactions of individual team members through analysis of their relevant actions in team sports like football.

Accuracy of Pattern Detection Methods in the Performance of Golf Putting

ABSTRACT 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.

A methodology for detection and estimation in the analysis of golf putting

This paper presents a methodology for visual detection and parameter estimation to analyze the effects of the variability in the performance of golf putting. A digital camera was used in each trial to track the putt gesture. The detection of the horizontal position of the golf club was performed using a computer vision technique, followed by an estimation algorithm divided in two different stages. On a first stage, diverse nonlinear estimation techniques were used and evaluated to extract a sinusoidal model of each trial. Secondly, several expert golf player trials were analyzed and, based on the results of the first stage, the Darwinian particle swarm optimization (DPSO) technique was employed to obtain a complete kinematical analysis and a characterization of each player’s putting technique. In this work, it is intended not only to test the performance of the DPSO method, but also to present a novel study in this field by identifying a putting “signature” of each player.

Distance and Slope Constraints: Adaptation and Variability in Golf Putting

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.

The ARCANE Project: How an Ecological Dynamics Framework Can Enhance Performance Assessment and Prediction in Football.

This paper discusses how an ecological dynamics framework can be implemented to interpret data, design practice tasks and interpret athletic performance in collective sports, exemplified here by research ideas within the Augmented peRCeption ANalysis framEwork for Football (ARCANE) project promoting an augmented perception of football teams for scientists and practitioners. An ecological dynamics rationale can provide an interpretation of athletes’ positional and physiological data during performance, using new methods to assess athletes’ behaviours in real-time and, to some extent, predict health and performance outcomes. The proposed approach signals practical applications for coaches, sports analysts, exercise physiologists and practitioners through merging a large volume of data into a smaller set of variables, resulting in a deeper analysis than typical measures of performance outcomes of competitive games.

Interpersonal dynamics: 1v1 sub-phase at sub-18 football players.

The performance of football players within game context can be analyzed based on their ability to break or (re)balance the attacker-defender dyad. In this context, the analysis of each sub-phase (e.g., 1v1, 2v2) presents a feature that needs to be taken into account in sports analysis. This study aims to investigate the interpersonal dynamics dyad formed by the attacker and the defender in 1v1 situations with a goalkeeper. A sample of 11 football male players (age: 17.91 ± 1.04 years) with 8.6 ± 1.52 years of practice experience participated in the study. Analyzing the 1v1 sub-phase, results show that the distance, speed and angular amplitude between the attacker and the defender increases, especially when the attacker attempts to overtake the defender (i.e., score a goal). We conclude that decision-making emerges from the perception that players draw from the action, actively and consistently interacting to find solutions to emerging problems within the game context

The effect of artificial side wind on the serve of competitive tennis players

In tennis, the serve is the shot of greatest importance. The serve depends mainly on the player’s technique, however, environmental factors can influence the accuracy of the serve. This study highlights the effect of side wind on the serve of 12 experienced tennis players. The players were asked to hit the intersection point between the central and the service line at maximum speed while a wind effect was artificially generated by a ventilator setup with various speed of Induced Aerodynamic Flow (IAF). Each player’s serve was then analyzed using error ellipses as a statistical measure. This method allowed us to evaluate the effect of “random wind” in comparison to “constant wind” on the accuracy of the serves. The truncated Fourier series analysis showed that there was an adaptive pattern in the accuracy of the serve depending on the random wind. However in four players, the more unpredictable the impact of the wind the more accurate they became with the serve. The fact that there was not a linear trend in the accuracy of serves when IAF increased shows that each player adapts differently to the wind influence.

Effects of long-term multicomponent exercise on health-related quality of life in older adults with type 2 diabetes: evidence from a cohort study

PurposeTo establish the effect of a long-term multicomponent exercise (LTMEX) intervention (24 months) on health-related quality of life (HRQoL), in older adults with type 2 diabetes (T2D).MethodsThis longitudinal retrospective cohort study analyzes the effects of a supervised LTMEX program on HRQoL in older adults with T2D (n = 279). Participants underwent one of two conditions: LTMEX (n = 241) trained three times per week; and unchanged lifestyle—the control group (CO; n = 38). Participants completed baseline, and 2-year follow-up evaluations including the Short Form Health Survey 36 (SF-36), anthropometric, hemodynamic components, and cardiorespiratory fitness (VO2 peak).ResultsLTMEX improves HRQoL, specifically physical functioning (P < 0.001), general health (P < 0.05), vitality (P < 0.001), mental health (MH; P < 0.05), physical component score (P < 0.001), mental component score (P < 0.001), and total SF-36 (P < 0.001). LTMEX group also decreased body weight (BW; P < 0.005), waist circumference (WC; P < 0.001), waist-to-hip ratio (WHR; P < 0.001), and systolic blood pressure (SBP; P < 0.001), and increased VO2 peak (P < 0.001). CO group increased WC (P = 0.012), BMI (P = 0.024), waist-to-hip ratio (WHR; P = 0.003) and SBP (P < 0.001), and decreased vitality (P < 0.001) and MH (P < 0.05).ConclusionsA LTMEX intervention improves physical and mental HRQoL in older adults with T2D, and also anthropometric, hemodynamic profile, and cardiorespiratory fitness.

Perception of Creativity and Game Intelligence in Soccer

A questionnaire was used to investigate the perception of creativity and game intelligence of coaches (n = 34, mean age 28.6 with an average of 14.3 years of experience) and players (n = 118, belonging to the ranks U-15 and U-19). Analyses indicated that there were statistically significant differences in most creative concepts inherent in the perception of creativity on the part of coaches. The results for the perception of the players showed that there were statistically significant differences in the importance attached to creativity and game intelligence. Apparently coaches mostly associate the creativity in soccer to a kind of magical thinking, adding also the game intelligence to the ability of rationality, problem solving, and decision. There was a strong correlation between creativity and game intelligence for the players.

Comparison of Classification Methods for Golf Putting Performance Analysis

This paper presents a comparative case study on the classification accuracy between five methods for golf putting performance analysis. In a previous work, a digital camera was used to capture 30 trials of 6 expert golf players. The detection of the horizontal position of the golf club was performed using a computer vision technique followed by the estimation algorithm Darwinian Particle Swarm Optimization (DPSO) in order to obtain a kinematical model of each trial. In this paper, the estimated parameters of the models are used as sample and training data of five classification algorithms: (1) Linear Discriminant Analysis (LDA); (2) Quadratic Discriminant Analysis (QDA); (3) Naive Bayes with Normal (Gaussian) distribution (NV); (4) Naive Bayes with Kernel Smoothing Density Estimate (NVK) and (5) Least Squares Support Vector Machines with Radial Basis Function Kernel (LS-SVM). The five classification methods are then compared through the analysis of the confusion matrix and the area under the Receiver Operating Characteristic curve (AUC).