https://dialnet.unirioja.es/descarga/articulo/4511387.pdf

The origins of order. Self-organization and selection in evolution

The purpose of this study was to evaluate the physical demands of English Football Association (FA) Premier League soccer of three different positional classifications (defender, midfielder and striker). Computerised time-motion video-analysis using the Bloomfield Movement Classification was undertaken on the purposeful movement (PM) performed by 55 players. Recognition of PM had a good inter-tester reliability strength of agreement (κ = 0.7277). Players spent 40.6 ± 10.0% of the match performing PM. Position had a significant influence on %PM time spent sprinting, running, shuffling, skipping and standing still (p 0.05). Players spent 48.7 ± 9.2% of PM time moving in a directly forward direction, 20.6 ± 6.8% not moving in any direction and the remainder of PM time moving backward, lateral, diagonal and arced directions. The players performed the equivalent of 726 ± 203 turns during the match; 609 ± 193 of these being of 0° to 90° to the left or right. Players were involved in the equivalent of 111 ± 77 on the ball movement activities per match with no significant differences between the positions for total involvement in on the ball activity (p > 0.05). This study has provided an indication of the different physical demands of different playing positions in FA Premier League match-play through assessment of movements performed by players.

Physical demands of different positions in FA Premier League soccer

A new statistic has been developed to quantify the amount of regularity in data. This statistic, ApEn (approximate entropy), appears to have potential application throughout medicine, notably in electrocardiogram and related heart rate data analyses and in the analysis of endocrine hormone release pulsatility. The focus of this article is ApEn. We commence with a simple example of what we are trying to discern. We then discuss exact regularity statistics and practical difficulties of using them in data analysis. The mathematic formula development for ApEn concludes the Solution section. We next discuss the two key input requirements, followed by an account of a pilot study successfully applying ApEn to neonatal heart rate analysis. We conclude with the important topic of ApEn as a relative (not absolute) measure, potential applications, and some caveats about appropriate usage of ApEn. Appendix A provides example ApEn and entropy computations to develop intuition about these measures. Appendix B contains a Fortran program for computing ApEn. This article can be read from at least three viewpoints. The practitioner who wishes to use a "black box" to measure regularity should concentrate on the exact formula, choices for the two input variables, potential applications, and caveats about appropriate usage. The physician who wishes to apply ApEn to heart rate analysis should particularly note the pilot study discussion. The more mathematically inclined reader will benefit from discussions of the relative (comparative) property of ApEn and from Appendix A.

A regularity statistic for medical data analysis

New updated! The latest book from a very famous author finally comes out. Book of handbook of individual differences learning and instruction, as an amazing reference becomes what you need to get. What's for is this book? Are you still thinking for what the book is? Well, this is what you probably will get. You should have made proper choices for your better life. Book, as a source that may involve the facts, opinion, literature, religion, and many others are the great friends to join with.

/pdf/handbook-of-individual-differences-learning-and-instruction-3z4xw1epjn.pdf

Handbook of individual differences, learning, and instruction.

Previous studies have been unable to characterise the association between physical activity and obesity, possibly because most relied on inaccurate measures of physical activity and obesity. We carried out a cross sectional analysis on 5,500 12-year-old children enrolled in the Avon Longitudinal Study of Parents and Children. Total physical activity and minutes of moderate and vigorous physical activity (MVPA) were measured using the Actigraph accelerometer. Fat mass and obesity (defined as the top decile of fat mass) were measured using the Lunar Prodigy dual x-ray emission absorptiometry scanner. We found strong negative associations between MVPA and fat mass that were unaltered after adjustment for total physical activity. We found a strong negative dose-response association between MVPA and obesity. The odds ratio for obesity in adjusted models between top and the bottom quintiles of minutes of MVPA was 0.03 (95% confidence interval [CI] 0.01-0.13, p-value for trend <0.0001) in boys and 0.36 (95% CI 0.17-0.74, p-value for trend = 0.006) in girls. We demonstrated a strong graded inverse association between physical activity and obesity that was stronger in boys. Our data suggest that higher intensity physical activity may be more important than total activity.

/pdf/objectively-measured-physical-activity-and-fat-mass-in-a-2pwl134tvf.pdf

Objectively Measured Physical Activity and Fat Mass in a Large Cohort of Children

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 perfor...

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

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.

https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0152516&type=printable

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

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.

/pdf/using-network-metrics-in-soccer-a-macro-analysis-ntidxlpb58.pdf

Using network metrics in soccer: a macro-analysis.

The specificity of collective sports training has evolved to adapt according to ecology stimuli inherent to the sport. In this sense, the coaches have adopted exercises based on the game, designated by small-sided games. In football practice this type of exercises triggers very receptivity on the part of coaches. In this sense, this paper analyzes the relevance of this type of exercise and as may be appropriate depending on the specific needs of the players. Task constraints as field dimensions, number of players for exercises or objectives of the task showed effects on physiological and technical variables of the players. Consequently this article will examine through a literature review, the effects related to the task constraints in order to emphasize the massive relevance of small-sided soccer games. Key words: Small-sided games, training, task constraints, soccer. Introduction Physiological, social, psychological, technical and tactical factors can influence the performance of soccer players (Bagsbo, 1994),

The usefulness of small-sided games on soccer training

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(-1)min(-1)VO2max) 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.

Rui Sousa Mendes

Papers

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

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

Using network metrics in soccer: a macro-analysis.

The usefulness of small-sided games on soccer training

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