Locomotor performance parameters as predictors of high-performing male soccer teams. A multiple-season study on professional soccer.

This study aims to explore the interplay between locomotor demands and goal differentials to better understand their combined influence on overall success. Spanning three competitive seasons within the male Turkish Super League, this study analyzed all participating teams across 124 matches. Locomotor demands, including total distance (m) covered (TD), distances covered (m) at different speed thresholds (0.

Assessing physical fitness adaptations in collegiate male soccer players through training load parameters: a two-arm randomized study on combined small-sided games and running-based high-intensity interval training.

Objective: To evaluate the effects of a 4-week intervention combining small-sided games (SSGs) and high-intensity interval training (HIIT) on physical fitness in collegiate male soccer players.

Methods: Twenty-one soccer players were randomly assigned to either the HIIT + SSGs group (n = 11) or a control group (n = 10). Physical fitness was assessed at baseline and 1-week post-intervention, including countermovement jump (CMJ), change of direction (COD) test, sprint test, repeated sprint ability (RSA) test, and 30-15 Intermittent Fitness Test (30-15IFT).

Comparing locomotor intensity indicators in soccer training and competition across contextual factors: a study of replaced coaches in a Portuguese professional 1st league team.

This study aims to examine, for each head coach (HC) replaced, the association between training intensity and physical performances obtained in games. Furthermore, the study investigated how contextual factors influence locomotor and mechanical performance association. External load variables were collected using Global Positioning System (GPS) devices across the 4 weeks and 4 games before and after the replacement in a professional adult male soccer team.

Patterns in assignment submission times: Analysis of factors contributing to undergraduate students' commitment to core-curriculum related course.

Co-curricular activities equip students with essential skills and knowledge for personal and professional growth. Despite their importance, many students exert minimal effort to complete the assigned tasks. Instructors perceive that the lack of emphasis on final exams in co-curricular subjects reduces student effort and commitment.

Disciplinary measures defining referee activity in top-European football leagues: A cross-sectional investigation.

The success and enjoyment of a football match depend heavily on referees and their ability to ensure fair play and uphold the rules of the game. However, there is limited research investigating the disciplinary measures and booking activities of referees in top European football leagues. In the current investigation, we explored the disciplinary measures and booking activities of top-European football league referees.

Psychometric properties and gender invariance of the 8-item emotion regulation questionnaire (ERQ-8) among Chinese university students.

Background: To assess emotion regulation strategies in a clear and direct manner, Emotion Regulation Questionnaire (ERQ) was developed based on the process model of emotion regulation. ERQ primarily assesses an individual's propensity for reappraisal (a cognitive change in the individual's psychological state in specific situations) and expressive suppression (a regulatory response where an individual alters their emotional response after the onset of an emotional reaction). Recent studies have suggested that the abbreviated 8-item version of the ERQ exhibits comparable model fit to the original version.

Physical predictors for retention and dismissal of professional soccer head coaches: an analysis of locomotor variables using logistic regression pipeline.

Introduction: Soccer has enormous global popularity, increasing pressure on clubs to optimize performance. In failure, the tendency is to replace the Head coach (HC). This study aimed to check the physical effects of mid-season replacements of HCs, investigating which external load variables can predict retention or dismissal.

A longitudinal analysis of injury characteristics among elite and amateur tennis players at different tournaments from electronic newspaper reports.

The non-complexity of tennis, coupled with its health benefits, renders it appealing and encourages varying competitions at different levels of age, gender, and expertise. However, the rapid increase in the participation rates witnesses a surge in injury occurrences, prompting the need for in-depth analysis to facilitate immediate intervention. We employed a media content analysis technique in which tennis-associated articles published in the last 5 years were examined.

Design and Validation of a Virtual Physical Education and Sport Science-Related Course: A Learner's Engagement Approach.

Learners’ engagement is shown to be a major predictor of learning, performance, and course completion as well as course satisfaction. It is easier to engage learners in a face-to-face teaching and learning format since the teacher can observe and interpret the learner’s facial expression and body language. However, in a virtual setting with the students sitting behind cameras, it is difficult to ascertain engagement as the students might be absent-mindedly attending the class.

Association of Physical Activity with Anthropometrics Variables and Health-Related Risks in Healthy Male Smokers.

Anthropometric variables (AV) are shown to be essential in assessing health status and to serve as markers for evaluating health-related risks in different populations. Studying the impact of physical activity (PA) on AV and its relationship with smoking is a non-trivial task from a public health perspective. In this study, a total of 107 healthy male smokers (37 ± 9.

Factorial validity and measurement invariance of the psychological need satisfaction in exercise scale across gender.

Background: Based on the self-determination theory, the psychological requirements for competence, autonomy, and relatedness boost beneficial exercise behaviour for healthy living. However, there is no valid, reliable Malay version scale to investigate the extent to which these psychological needs are met. The main purpose of this study was to examine the psychometric properties of a Malay version of the Psychological Need Satisfaction in Exercise (PNSE-M) scale.

Surveillance of Injury Types, Locations, and Intensities in Male and Female Tennis Players: A Content Analysis of Online Newspaper Reports.

The popularity of modern tennis has contributed to the increasing number of participants at both recreational and competitive levels. The influx of numerous tennis participants has resulted in a wave of injury occurrences of different types and magnitudes across both male and female players. Since tennis injury harms both players' economic and career development, a better understanding of its epidemiology could potentially curtail its prevalence and occurrences.

The classification of skateboarding tricks transfer learning pipelines.

This study aims at classifying flat ground tricks, namely Ollie, Kickflip, Shove-it, Nollie and Frontside 180, through the identification of significant input image transformation on different transfer learning models with optimized Support Vector Machine (SVM) classifier. A total of six amateur skateboarders (20 ± 7 years of age with at least 5.0 years of experience) executed five tricks for each type of trick repeatedly on a customized ORY skateboard (IMU sensor fused) on a cemented ground.

A real-time approach of diagnosing rice leaf disease using deep learning-based faster R-CNN framework.

The rice leaves related diseases often pose threats to the sustainable production of rice affecting many farmers around the world. Early diagnosis and appropriate remedy of the rice leaf infection is crucial in facilitating healthy growth of the rice plants to ensure adequate supply and food security to the rapidly increasing population. Therefore, machine-driven disease diagnosis systems could mitigate the limitations of the conventional methods for leaf disease diagnosis techniques that is often time-consuming, inaccurate, and expensive.

The classification of EEG-based winking signals: a transfer learning and random forest pipeline.

Brain Computer-Interface (BCI) technology plays a considerable role in the control of rehabilitation or peripheral devices for stroke patients. This is particularly due to their inability to control such devices from their inherent physical limitations after such an attack. More often than not, the control of such devices exploits electroencephalogram (EEG) signals.

The classification of motor imagery response: an accuracy enhancement through the ensemble of random subspace k-NN.

Brain-computer interface (BCI) is a viable alternative communication strategy for patients of neurological disorders as it facilitates the translation of human intent into device commands. The performance of BCIs primarily depends on the efficacy of the feature extraction and feature selection techniques, as well as the classification algorithms employed. More often than not, high dimensional feature set contains redundant features that may degrade a given classifier's performance.

Kids motor performances datasets.

These datasets described the data of the Motor Performance Index for 7 years old kids in Malaysia based on Malaysia's physical fitness test SEGAK. This database has been designed and created with data analysis to create the index from the factor and variable of the test and the test was conducted in the majority of the national primary school in Malaysia. Gender, state of origin, and residential location of the school were the factors used to categorize the participant of the test.

Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review.

Brain-Computer Interface (BCI), in essence, aims at controlling different assistive devices through the utilization of brain waves. It is worth noting that the application of BCI is not limited to medical applications, and hence, the research in this field has gained due attention. Moreover, the significant number of related publications over the past two decades further indicates the consistent improvements and breakthroughs that have been made in this particular field.

Technical and tactical performance indicators discriminating winning and losing team in elite Asian beach soccer tournament.

The present study aims to identify the essential technical and tactical performance indicators that could differentiate winning and losing performance in the Asian elite beach soccer competition. A set of 20 technical and tactical performance indicators namely; shot back-third, shot mid-third, shot front-third, pass back-third, pass mid-third, pass front-third, shot in box, shot outbox, chances created, interception, turnover, goals scored 1st period, goals scored 2nd period, goals scored 3rd period, goals scored extra time, tackling, fouls committed, complete save, incomplete save and passing error were observed during the beach soccer Asian Football Confederation tournament 2017 held in Malaysia. A total of 23 matches from 12 teams were notated using StatWatch application in real-time.

A machine learning approach of predicting high potential archers by means of physical fitness indicators.

k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. However, the application of k-NN for prediction and classification in specific sport is still in its infancy. The present study classified and predicted high and low potential archers from a set of physical fitness variables trained on a variation of k-NN algorithms and logistic regression.

The identification of high potential archers based on fitness and motor ability variables: A Support Vector Machine approach.

Support Vector Machine (SVM) has been shown to be an effective learning algorithm for classification and prediction. However, the application of SVM for prediction and classification in specific sport has rarely been used to quantify/discriminate low and high-performance athletes. The present study classified and predicted high and low-potential archers from a set of fitness and motor ability variables trained on different SVMs kernel algorithms.