Rui Sousa Mendes

Acute Effects of the Number of Players and Scoring Method on Physiological, Physical, and Technical Performance in Small-sided Soccer Games

This study aims to examine the effect of differences in the number of players and scoring method on heart rate responses, time–motion characteristics, and technical/tactical performance during small-sided soccer games. Ten male amateur soccer players (26.4 ± 5.3 years old, 8.4 ± 3.2 years of practice, 179.3 ± 5.2 cm body height, 71.2 ± 7.1 kg body weight, 45.8 ± 2.6 ml.kg–1min–1VO2max) from the Portuguese regional league played nine different small-sided games (i.e., 3 formats × 3 scoring methods). The study used two-way MANOVA, two-away ANOVA, and one-way ANOVA, depending on the specific procedure for the analysis. Compared with other formats, 2v2 induced significantly greater values of technical/tactical indexes (p = 0.001), 3v3 induced significantly higher %HRreserve values (p = 0.001), and 4v4 led to significantly greater distance coverage and speed (p = 0.001). The study provided evidence for coaches to set different small-sided game conditions depending on the training purpose in terms of physiological, physical, and technical performance.

Using network metrics in soccer: a macro-analysis.

Abstract 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.

Activity Profiles of Soccer Players During the 2010 World Cup

Abstract 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.

Measuring Tactical Behaviour Using Technological Metrics: Case Study of a Football Game

In football, the tactical behaviour of a team is related to the state of ball possession, i.e., the defensive and offensive phases. The aim of this study was to measure the tactical responses of two opposing teams in the moments with and without ball possession, thus trying to identify differences in results arising from tactical metrics such as weighted centroid position, weighted stretch index, surface area and effective area of play. The herein presented results show statistical differences in both teams, either with or without the ball possession, for the -axis centroid (p-value ≤ 0.001), -axis centroid (p-value ≤ 0.001), stretch index (p-value ≤ 0.001), surface area (p-value ≤ 0.001) and effective area of play (p-value ≤ 0.001). Such results confirm that teams react depending upon balls possession, respecting the tactical principles of width and length, as well as the unit in the offensive phase with ball possession, and also the concentration and defensive unit in the moments without ball possession.

Measuring Collective Behaviour in Football Teams: Inspecting the impact of each half of the match on ball possession

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.

General network analysis of national soccer teams in FIFA World Cup 2014

This study analyzed the network characteristics of successful and unsuccessful national teams that participated in FIFA World Cup 2014. The relationship between the variables of overall team performance and the network characteristics measured on the basis of the passes between teammates was also investigated. A dataset of 37,864 passes between teammates in 64 soccer matches enabled the study on network structure and team performance of 32 national soccer teams. Our results showed significant differences in the dependent variables of network density (F4,123 = 2.72; p = 0.03; η2p = 0.04; small effect size) and total links (F4,123 = 2.73; p = 0.03; η2p = 0.04; small effect size) between the teams that reached the later stages of the tournament. Goals scored presented a small positive correlation with total links (r = 0.24; p = 0.001), network density (r = 0.24; p = 0.001), and clustering coefficient (r = 0.17; p > 0.050). High levels of goals scored were associated with high levels of total links, network density, and clustering coefficient. This study showed that successful teams have a high level of network density, total links, and clustering coefficient. Thus, large values of connectivity between teammates are associated with better overall team performance.

Developing Aerobic and Anaerobic Fitness Using Small-Sided Soccer Games: Methodological Proposals

ABSTRACT SOCCER COACHES HAVE BEEN INCREASING THE USE OF SMALL-SIDED GAMES IN SOCCER TRAINING. THESE SMALL-SIDED GAMES SHOW A SIMILAR EFFICIENCY AS TRADITIONAL RUNNING METHODS (WITHOUT THE USE OF A BALL) IN DEVELOPING PHYSICAL FITNESS IN SOCCER PLAYERS. MOREOVER, SMALL-SIDED GAMES ENABLE THE DEVELOPMENT OF BOTH TECHNICAL SKILLS AND TACTICAL ACTIONS. HOWEVER, THERE IS LITTLE KNOWLEDGE ABOUT THE PROPER ORGANIZATION THAT IS NECESSARY FOR SMALL-SIDED GAMES TO ACHIEVE THE DESIRED EFFECTS IN SOCCER PLAYERS. THIS REVIEW AIMS TO SUMMARIZE THE PHYSIOLOGICAL EFFECTS ON SOCCER PLAYERS PROMOTED BY SMALL-SIDED GAMES AND TO DEVELOP A METHODOLOGICAL SCHEMATIZATION FOR ORGANIZING SMALL-SIDED GAMES.

Physical Activity Patterns in University Students: Do They Follow the Public Health Guidelines?

Physical activity is associated with health. The aim of this study was (a) to access if Portuguese university students meet the public health recommendations for physical activity and (b) the effect of gender and day of the week on daily PA levels of university students. This observational cross-sectional study involved 126 (73 women) healthy Portuguese university students aged 18–23 years old. Participants wore the ActiGraph wGT3X-BT accelerometer for seven consecutive days. Number of steps, time spent sedentary and in light, moderate and vigorous physical activity were recorded. The two-way MANOVA revealed that gender (p-value = 0.001; η2 = 0.038; minimum effect) and day of the week (p-value = 0.001; η2 = 0.174; minimum effect) had significant main effects on the physical activity variables. It was shown that during weekdays, male students walked more steps (65.14%), spent less time sedentary (6.77%) and in light activities (3.11%) and spent more time in moderate (136.67%) and vigorous activity (171.29%) in comparison with weekend days (p < 0.05). The descriptive analysis revealed that female students walked more steps (51.18%) and spent more time in moderate (125.70%) and vigorous (124.16%) activities during weekdays than in weekend days (p < 0.05). Women students did not achieve the recommended 10,000 steps/day on average during weekdays and weekend days. Only male students achieved this recommendation during weekdays. In summary, this study showed a high incidence of sedentary time in university students, mainly on weekend days. New strategies must be adopted to promote physical activity in this population, focusing on the change of sedentary behaviour.

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.

Midfielder as the prominent participant in the building attack: A network analysis of national teams in FIFA World Cup 2014

This study aimed to analyze the most prominent players’ positions that contributed to the build of attack in football during FIFA World Cup 2014. The connections among teammates in all matches of the tournament were analyzed, and the tactical lineup and players’ positions of players were codified as independent variables. Four centrality network metrics were used to identify the pertinence of each players’ position. A total of 37,864 passes between teammates were recorded. Each national team was analyzed in terms of all their matches, thus all 64 matches from the FIFA World Cup 2014 tournament were analyzed and codified in this study. A total of 128 adjacency matrices and corresponding network graphs were generated and used to compute the centrality metrics. Results revealed that the players’ position (p = 0.001; η2p = 0.143; Power = 1.00; moderate effect size) showed significant main effects on centrality measures. The central midfielders possessed the main values in all centrality measures in the majority of analyzed tactical lineups. Therefore, this study showed that independent of the team strategy, the players’ position of a central midfielder significantly contributed to the build of attack in football, for example, greater cooperation and activity profile.