Relationships between training load, peak height velocity, muscle soreness and fatigue status in elite-level young soccer players: a competition season study.

BACKGROUND: This study aimed to compare training load parameters, delayed onset muscle soreness (DOMS), and fatigue status between season periods (1st and 2nd halves) in U14 soccer players and to analyze the relationships between training load parameters based on season periods (1st and 2nd halves) with peak height velocity (PHV), DOMS, and fatigue status in under-14 (U14) young elite soccer players. Additionally, it was intended to analyze if fatigue, DOMS and PHV could explain training load parameters across the season. METHODS: Twenty U14 players that competed in the national league participated in this study. The players were monitored during the whole season (26 weeks), and evaluations were carried out at the end of the in-season. Anthropometric and body composition parameters and the maturity offset of each player were utilized to compute each player's age at PHV. Players reported their levels of DOMS and fatigue status using Hooper index questionnaires. The internal load was monitored using the rating of perceived exertion (RPE). Acute weekly internal load (AW), chronic weekly internal load (CW), acute: chronic workload ratio (ACWR), training monotony (TM), and training strain (TS) were also obtained. RESULTS: The main results showed that TM was higher in the 2nd half, while CW, AW and DOMS were higher in the 1st half of the season. Moreover, the main correlations showed a positive correlation between PHV and TS (2nd half of the season) and between fatigue and TM (1st half of the season). CONCLUSION: In conclusion, variations in well-being status and PHV cannot explain the variations in internal training loads in elite U14 soccer players. In addition, internal training load indices during the first half of the competitive season can promote a fundamental base for progression loads during the second period of the competitive season.

Predicting functional movement capacity in adults: the effect of range of motion and isometric strength.

The aim of the study was to determine the role of isometric strength and range of motion in predicting Functional Movement Screen (FMS) scores of adults. A total of 120 participants (age = 34.62 ± 11.82 years; height = 170.56 ± 9.63 cm; weight = 73.62 ± 15.39 kg) volunteered to participate in the study. Anthropometric measurements were performed, including height, body weight, muscle mass, and body fat. Following this, the ranges of motion of the shoulder, hip, knee, and ankle joints were measured sequentially. Isometric strength and FMS tests were then performed. Hip extension isometric strength explained 23% of the variation in FMStotal. The common effect of knee flexion, shoulder flexion, and dorsiflexion joint range of motion explained 34% of the change in FMStotal (F (3-116) = 20.375, p < 0.001). A significant relationship (R = 0.658, R2 = 0.413) was found between hip extension isometric strength, knee flexion, shoulder flexion, and dorsiflexion range of motion and FMStotal (F (4-115) = 21.952, p < 0.001). The common effect of all these variables explains 43% of the change in FMStotal. The results indicate that the FMS test scores, which are utilized to evaluate the risk of injury in sedentary adults, can be significantly predicted by the effect of hip extension isometric strength and parameters related to knee flexion, shoulder flexion, and dorsiflexion joint range of motion. At this time, it is advised that range of motion and isometric strength be taken into account when determining a person's functional movement capacity.

Weekly variations of accelerometer variables and workload of professional soccer players from different positions throughout a season.

The current study aimed to analyze, using accelerometer-based activity, acute workload, chronic workload, acutechronic workloads ratio, training-monotony and training-strain throughout a competitive soccer-season and to compare these variables between players from different playing positions. Twenty-one professional soccer-players were monitored during the 48 weeks of the season. Players were grouped according to their position. Four lateral-defenders and four winger-players formed LDW group, four central-defenders and four forwards formed CDF group, and six midfielder-players formed MDF group. Accelerometer-based variables were collected during training and match contexts and were used to generate indicators of weekly acute and chronic workload, training monotony, training strain and metabolic power. A one-way ANOVA compared all dependent variables between groups, and effect sizes for pairwise comparisons were calculated. Results revealed variations in the weekly load throughout the season, which demands caution from coaches to avoid injuries. There were no differences in weekly-loads for all dependent variables (P > 0.05, small-to-moderate effects). We conclude that the weekly-load is not constant during a competitive season and players from different positions have similar weekly-loads. Therefore, previously reported in the literature, possible match-related positional differences might be compensated by differences in training-related loads, leading to a similar profile when considering the whole week.

Estimation of Obesity Levels through the Proposed Predictive Approach Based on Physical Activity and Nutritional Habits.

Obesity is the excessive accumulation of adipose tissue in the body that leads to health risks. The study aimed to classify obesity levels using a tree-based machine-learning approach considering physical activity and nutritional habits. Methods: The current study employed an observational design, collecting data from a public dataset via a web-based survey to assess eating habits and physical activity levels. The data included gender, age, height, weight, family history of being overweight, dietary patterns, physical activity frequency, and more. Data preprocessing involved addressing class imbalance using Synthetic Minority Over-sampling TEchnique-Nominal Continuous (SMOTE-NC) and feature selection using Recursive Feature Elimination (RFE). Three classification algorithms (logistic regression (LR), random forest (RF), and Extreme Gradient Boosting (XGBoost)) were used for obesity level prediction, and Bayesian optimization was employed for hyperparameter tuning. The performance of different models was evaluated using metrics such as accuracy, recall, precision, F1-score, area under the curve (AUC), and precision-recall curve. The LR model showed the best performance across most metrics, followed by RF and XGBoost. Feature selection improved the performance of LR and RF models, while XGBoost's performance was mixed. The study contributes to the understanding of obesity classification using machine-learning techniques based on physical activity and nutritional habits. The LR model demonstrated the most robust performance, and feature selection was shown to enhance model efficiency. The findings underscore the importance of considering both physical activity and nutritional habits in addressing the obesity epidemic.

Variations in Accumulated-Training Load Parameters and Locomotor Demand with Consideration of Puberty in Elite Young Soccer Players.

The study's purposes were to examine the associations of training load parameters with locomotor demand and puberty status in elite young soccer players and to predict the percentage of changes in their performance ability with adjustments to the training load parameters, using multivariate regression analysis, while considering PHV and maturity offset. Seventeen male players (15−16 years old) participated in this study. Anthropometrics, body composition, maximal oxygen consumption (VO2max), and puberty status (for calculating PHV) and maturity offset were assessed. The results demonstrated substantial differences between the PHV, VO2max, and load parameters (acute and chronic workload (CWL)) over a soccer season. A substantial relationship existed between the workload parameters (VO2max, CWL, and training monotony (TM)) and maturity offset. All of the variables, except for training strain, demonstrated significant variances in relation to the differences between the first and second halves (p < 0.05). Aerobic performance can be estimated using the CWL, TM, and maturity offset values (R2 = 0.46). On the contrary, aerobic power performance can be explained using the acute:chronic workload, TM, and PHV values (R2 = 0.40). In conclusion, the biological maturity state of young soccer players has a substantial impact on their functional potential. Variations in accumulated load contribute significantly to aerobic resistance, whereas weight and height contribute significantly to sprint and vertical-jump performance, respectively.