Browsing by Author "Afonso, Pedro"
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- Analyzing Key Factors on Training Days within a Standard Microcycle for Young Sub-Elite Football Players: A Principal Component ApproachPublication . Teixeira, José Eduardo; Branquinho, Luís; Ferraz, Ricardo; Morgans, Ryland; Encarnação, Samuel; Ribeiro, Joana; Afonso, Pedro; Ruzmetov, Nemat; Barbosa, Tiago M.; Monteiro, A.M.; Forte, PedroUtilizing techniques for reducing multivariate data is essential for comprehensively understanding the variations and relationships within both biomechanical and physiological datasets in the context of youth football training. Therefore, the objective of this study was to identify the primary factors influencing training sessions within a standard microcycle among young sub-elite football players. A total of 60 male Portuguese youth sub-elite footballers (15.19 1.75 years) were continuous monitored across six weeks during the 2019–2020 in-season, comprising the training days from match day minus (MD-) 3, MD-2, and MD-1. The weekly training load was collected by an 18 Hz global positioning system (GPS), 1 Hz heart rate (HR) monitors, the perceived exertion (RPE) and the total quality recovery (TQR). A principal component approach (PCA) coupled with a Monte Carlo parallel analysis was applied to the training datasets. The training datasets were condensed into three to five principal components, explaining between 37.0% and 83.5% of the explained variance (proportion and cumulative) according to the training day (p < 0.001). Notably, the eigenvalue for this study ranged from 1.20% to 5.21% within the overall training data. The PCA analysis of the standard microcycle in youth sub-elite football identified that, across MD-3, MD-2, and MD-1, the first was dominated by the covered distances and sprinting variables, while the second component focused on HR measures and training impulse (TRIMP). For the weekly microcycle, the first component continued to emphasize distance and intensity variables, with the ACC and DEC being particularly influential, whereas the second and subsequent components included HR measures and perceived exertion. On the three training days analyzed, the first component primarily consisted of variables related to the distance covered, running speed, high metabolic load, sprinting, dynamic stress load, accelerations, and decelerations. The high intensity demands have a high relative weight throughout the standard microcycle, which means that the training load needs to be carefully monitored and managed.
- Comparative Efficacy of Bodyweight and Free Weights Training on Shooting Strength in Roller HockeyPublication . Paiva, Eduardo; Afonso, Pedro; Leite, Luciano Bernardes; Teixeira, José Eduardo; Forte, Pedro; Rodrigues, Pedro M.This study evaluated the impact of an 8-week training program on two groups of players, one performing free weights training and the other bodyweight training. The sample consisted of 14 athletes with a mean age of 22.6 years. Assessments of shooting strength were conducted before and after the program, measuring shot speed, acceleration, and strength. The free weights training included exercises with dumbbells and barbells, while the bodyweight training included squats, push- ups, and planks. Sessions occurred twice a week, with gradual progress in the number of sets and repetitions. Statistical analyses were performed using GraphPad Prism software, with significance set at p<0.05. Data distribution was tested using the Shapiro-Wilk test, and comparisons between pre- and post-intervention assessments were made with paired t- tests. Results showed significant improvements in shot speed, acceleration, and strength in the free weights training group, while the bodyweight training group showed no significant changes. It was concluded that free weights training is more effective for improving shooting strength in roller hockey players.
- Data Mining Paths for Standard Weekly Training Load in Sub-Elite Young Football Players: A Machine Learning ApproachPublication . Teixeira, José Eduardo; Encarnação, Samuel; Branquinho, Luís; Morgans, Ryland; Afonso, Pedro; Rocha, João Pedro da Silva; Graça, Francisco M.; Barbosa, Tiago M.; Monteiro, A.M.; Ferraz, Ricardo; Forte, PedroThe aim of this study was to test a machine learning (ML) model to predict high-intensity actions and body impacts during youth football training. Sixty under-15, -17, and -19 sub-elite Portuguese football players were monitored over a 6-week period. External training load data were collected from the target variables of accelerations (ACCs), decelerations (DECs), and dynamic stress load (DSL) using an 18 Hz global positioning system (GPS). Additionally, we monitored the perceived exertion and biological characteristics using total quality recovery (TQR), rating of perceived exertion (RPE), session RPE (sRPE), chronological age, maturation offset (MO), and age at peak height velocity (APHV). The ML model was computed by a feature selection process with a linear regression forecast and bootstrap method. The predictive analysis revealed that the players’ MO demonstrated varying degrees of effectiveness in predicting their DEC and ACC across different ranges of IQR. After predictive analysis, the following performance values were observed: DEC (xpredicted = 41, β = 3.24, intercept = 37.0), lower IQR (IQRpredicted = 36.6, β = 3.24, intercept = 37.0), and upper IQR (IQRpredicted = 46 decelerations, β = 3.24, intercept = 37.0). The player’s MO also demonstrated the ability to predict their upper IQR (IQRpredicted = 51, β = 3.8, intercept = 40.62), lower IQR (IQRpredicted = 40, β = 3.8, intercept = 40.62), and ACC (xpredicted = 46 accelerations, β = 3.8, intercept = 40.62). The ML model showed poor performance in predicting the players’ ACC and DEC using MO (MSE = 2.47–4.76; RMSE = 1.57–2.18: R2 = −0.78–0.02). Maturational concerns are prevalent in football performance and should be regularly checked, as the current ML model treated MO as the sole variable for ACC, DEC, and DSL. Applying ML models to assess automated tracking data can be an effective strategy, particularly in the context of forecasting peak ACC, DEC, and bodily effects in sub-elite youth football training.
- Hierarchical clustering of the pre-exam anxiety levels in physically inactive and active adolescent students from 56 countries: an observational study using PISA program dataPublication . Encarnação, Samuel; Teixeira, José Eduardo; Forte, Pedro; Leite, Luciano Bernardes; Sortwell, Andrew; Branquinho, Luís; Ferraz, Ricardo; Afonso, Pedro; Vaz, Paula Marisa Fortunato; Monteiro, António M.The relationship between physical activity and anxiety among students has been extensively studied, with research highlighting the protective effects of physical activity on mental well-being. Methods: This article synthesizes existing literature on the topic and presents a novel analysis of pre-exam anxiety rates among physically inactive high school students from 56 countries. Using data from the Programme for International Student Assessment (PISA) 2018, a hierarchical clustering method was applied to identify four clusters based on strati ed country groups by the students pre-exam anxiety levels. Results: The results indicated ve clusters for low physically active students (three with higher anxiety rates and two with lower levels of the condition) and four clusters for the low physically active individuals (two for higher anxiety rates and two for lower levels). Furthermore, the hierarchical model worked with good precision in the clustering task. In conclusion, considering the low physically active students, Brazil (82%) and the Dominican Republic (81%) recorded the highest pre-exam anxiety levels, while the Czech Republic (35%) had the lowest. Among the physically active students, Malaysia (82%), Brazil (81%), and Costa Rica (81%) recorded the highest anxiety levels, whereas again, the Czech Republic (35%) had the lowest. Discussion: These ndings emphasize that although physical activity generally relates to reduced anxiety, this association varies across cultural and educational contexts.
- Match-to-Match Variation on High-Intensity Demands in a Portuguese Professional Football TeamPublication . Teixeira, José Eduardo; Branquinho, Luís; Leal, Miguel; Morgans, Ryland; Sortwell, Andrew; Barbosa, Tiago M.; Monteiro, A.M.; Afonso, Pedro; Machado, Guilherme; Encarnação, Samuel; Ferraz, Ricardo; Forte, PedroThe aim of this study was to analyze the match-to-match variation in high-intensity demands from one Portuguese professional football team according to playing positions. Twentythree male outfield professional football players were observed during eighteen matches of the Portuguese Second League. Time–motion data were collected using Global Positioning System (GPS) technology. Match running performance was analyzed based on the following three playing positions: defenders (DF), midfielders (MF), and forwards (FW). Repeated measures ANOVA was utilized to compare match running performance within each position role, and seasonal running variation. Practical differences were assessed using the smallest worthwhile change (SWC), coefficient of variation (CV), and twice the coefficient of variation (2CV). Significant differences were found among playing positions in total distance covered (F = 15.45, p < 0.001, η2 = 0.33), average speed (F = 12.79, p < 0.001, η2 = 0.29), high-speed running (F = 16.93, p < 0.001, η2 = 0.36), sprinting (F = 13.49, p < 0.001, η2 = 0.31), accelerations (F = 4.69, p = 0.001, η2 = 0.132), and decelerations (F = 12.21, p < 0.001, η2 = 0.284). The match-to-match running performance encompassed TD (6.59%), AvS (8.67%), HSRr (37.83%), SPR (34.82%), ACC (26.92%), and DEC (27.85%). CV values for total distance covered ranged from 4.87–6.82%, with forwards and midfielders exhibiting the greatest and smallest variation, respectively. Midfielders demonstrated the highest match-to-match variation for all other analyzed variables (8.12–69.17%). All playing positions showed significant variation in high-demanding variables (26.94–37.83%). This study presents the initial analysis of match-tomatch variation in high-intensity demands within a Portuguese professional football team. Thus, the position’s specificity and context can provide a helpful strategy for evaluating match-to-match running performance, and for recommending individualized training exercises based on the peak and high-intensity demands for each player’s role within the game.
- Player Tracking Data and Psychophysiological Features Associated with Mental Fatigue in U15, U17, and U19 Male Football Players: A Machine Learning ApproachPublication . Teixeira, José Eduardo; Afonso, Pedro; Schneider, André; Branquinho, Luís; Maio, Eduardo; Ferraz, Ricardo; Nascimento, Rafael; Morgans, Ryland; Barbosa, Tiago M.; Monteiro, António M.; Forte, PedroOptimizing recovery is crucial for maintaining performance and reducing fatigue and injury risk in youth football players. This study applied machine learning (ML) models to classify mental fatigue in U15, U17, and U19 male players using wearable signals, tracking data, and psychophysiological features. Over six weeks, training loads were monitored via GPS, psychophysiological scales, and heart rate sensors, analyzing variables such as total distance, high-speed running, recovery state, and perceived exertion. The data preparation process involved managing absent values, applying normalization techniques, and selecting relevant features. A total of five ML models were evaluated: K-Nearest Neighbors (KNN), Gradient Boosting (XGBoost), Support Vector Machine (SVM), Random Forest (RF), and Decision Tree (DT). XGBoost, RF, and DT achieved high accuracy, while KNN underperformed. Using a correlation matrix, average speed (AvS) was the only variable significantly correlated with the rating of perceived exertion (RPE) (r = 0.142; p = 0.010). After dimensionality reduction, ML models were re-evaluated, with RF and DT performing best, followed by XGBoost and SVM. These findings confirm that tracking and wearable-derived data are effectively useful for predicting RPE, providing valuable insights for workload management and personalized recovery strategies. Future research should integrate psychological and interpersonal factors to enhance predictive modeling in the individual long-term health and performance of young football players.
- Tracking the Prevalence of Obesity in Portuguese School-Aged Children: What Future to Expect?Publication . Valente, Nelson; Forte, Pedro; Teixeira, José Eduardo; Afonso, Pedro; Ferreira, Sérgio; Marinho, D.A.; Mendes, Pedro Duarte; Ferraz, Ricardo; Branquinho, LuísChildhood obesity presents a significant public health concern globally, with implications for cardiovascular health and metabolic syndrome. In Portugal, approximately 31.6% of children are affected, highlighting the urgency for intervention strategies. This study aimed to assess the prevalence of overweight and obesity in Portuguese school-aged children, with a focus on sex and age differences. Methods: Anthropometric measurements were conducted on 1564 children aged 6–10 years, including weight, height, and skinfold thickness. Body Mass Index (BMI) and the percentage of body fat were calculated using established methods. Results: The results revealed significant differences in BMI (≤0.001) and body fat percentage (≤0.001) among different BMI categories, with a notable prevalence of overweight and obesity, particularly among boys. A total of 37% of the studied population is overweight or obese, among which 40.1% and 33.9% are boys and girls, respectively. Conclusions: This study highlights statistically significant differences in BMI and body fat percentage for both sexes in different BMI categories. A large proportion of the population is overweight or obese, with a greater prevalence in boys. In short, childhood obesity has a negative impact on body composition and is associated with significant differences in anthropometric parameters, emphasizing the importance of preventative and intervention strategies to address this health problem.