Search Results (30)

Corner kicks are one of the most frequent and potentially decisive set pieces in soccer, occurring approximately ten times per match. Aim: This systematic review aimed to synthesize the existing evidence on the technical–tactical execution of corner kicks in male soccer, assess the methodological quality of published studies, and provide practical recommendations for coaching staff. Methodology: Following PRISMA guidelines, a systematic search was conducted on 2 March 2025, in the Web of Science and Scopus databases. Studies were included if they focused on the technical–tactical analysis of corner kicks in male soccer, published in peer-reviewed journals or conferences, and written in English. A total of 21 eligible studies were identified. Each study was assessed for quality using a 13-item checklist, and a qualitative synthesis was performed based on key tactical, contextual, and methodological dimensions. Results: The included studies showed that most corners were delivered to the central area between the six-yard box and penalty spot. Dynamic attacking organizations involving 3–4 players and indirect deliveries to the far post were associated with higher probabilities of shots on target. Defensively, mixed marking strategies with players covering the near post yielded lower concession rates. Methodological quality was generally moderate to high. Inconsistencies in zone division and limited reporting of contextual variables were common limitations. Only two studies examined the transition phase after ball loss. Conclusions: Despite their strategic importance, corner kicks remain understudied in certain aspects. There is a need for standardized frameworks in zone division and a greater focus on contextual and transitional elements. This review provides evidence-based recommendations for optimizing set-piece strategy and highlights key areas for future research, including the systematic integration of transition phases and meta-analytical synthesis of performance indicators. Full article

This study presents a comprehensive bibliometric analysis of growth and maturation (GAM) research in youth basketball. A systematic search of Web of Science (up to August 2024) identified 1160 records; after screening per bibliometric review guidelines, 141 relevant studies were selected. Descriptive analysis indicates an 11.59% annual increase in GAM publications since 2003, underscoring significant expansion of this field. The 576 authors contributing to these studies show a high degree of collaboration, averaging 5.42 co-authors per paper, and 52.60% of publications involve international partnerships. Citation network analysis reveals that GAM research on basketball players predominantly addresses sports performance, strength, and injuries. Core themes (e.g., maturity/maturation) are well integrated, while foundational topics such as growth, strength, and age, although central to the field, remain underexplored. These gaps highlight the need for more targeted investigations. Practically, the findings guide coaches, trainers, and sports administrators in designing developmentally appropriate training programs, implementing targeted injury-prevention strategies, and refining talent identification initiatives. By identifying key areas for further inquiry, this study seeks to strengthen youth basketball programs through growth-stage-specific training methods, optimized injury-prevention protocols, and a holistic approach to athlete development. Full article

This study aimed to analyze the incidence, affected areas, and types of injuries sustained during training among youth field hockey players to identify key characteristics. A survey was conducted with 374 youth field hockey players (236 males, 138 females) from middle and high school teams registered with the Korea Hockey Association in 2024. Data were collected on injury status, training hours, injury sites, and prevention methods. Chi-square tests, independent t-tests, and frequency analyses were performed to assess differences in injury incidence based on gender and school level. The analysis revealed no significant gender differences in training-related injury experiences, with 17.2% of male athletes and 10.2% of female athletes reporting injuries during training. Similarly, no significant difference was found between middle and high school athletes, although high school athletes had a significantly lower injury incidence than middle school athletes (1.54 vs. 2.28 per 1000 h, p < 0.05). The most common injury sites were the ankle and knee, with muscle injuries being the most frequent among males and ligament injuries among females. Additionally, male and high school athletes more frequently reported engaging in warm-up and cool-down exercises. There was no significant difference in injury rates between genders during training, but high school athletes tended to experience fewer injuries than middle school athletes. Ankle injuries were the most common, with muscle and ligament damage being the primary types of injuries. While warm-up exercises were commonly practiced, further research is needed to determine their actual effectiveness in injury prevention. Full article

Background/Objectives: The integration of Augmented Reality (AR) and Artificial Intelligence (AI) in educational applications presents an opportunity to enhance learning outcomes in young users. This study focuses on ARFood, a serious game designed to teach Generation Alpha about nutritional health and environmental sustainability. The objective is to evaluate and improve the effectiveness of the app’s AI-driven feedback mechanisms in achieving specific educational goals in these domains. Methods: ARFood features two AI-powered Non-Player Characters (NPCs), each programmed to evaluate virtual shopping carts created by users. The nutritional NPC provides feedback on dietary choices, while the sustainability NPC assesses environmental impacts. Ninety-three participants were involved, generating 83 virtual carts that were evaluated by both NPCs. Each NPC’s feedback was assessed for alignment with five predefined educational objectives per theme using a zero-shot RoBERTa classifier. An iterative process was employed to refine the NPC prompts, increase the weight of underrepresented objectives, and re-evaluate virtual carts until all objectives were satisfactorily addressed. Results: Initial evaluations revealed uneven alignment across educational objectives, particularly in areas such as resource conservation and balanced diet planning. Prompt refinement led to a significant improvement in feedback quality, with the final iterations demonstrating comprehensive coverage of all educational objectives. Conclusions: This study highlights the potential of AR and AI in creating adaptive educational tools. Iterative prompt optimization, supported by zero-shot classification, was effective in enhancing the app’s ability to deliver balanced, goal-oriented feedback. Future applications can leverage this approach to improve educational outcomes across various domains. Full article

Machine learning (ML) has revolutionized resource management in agriculture by analyzing vast amounts of data and creating precise predictive models. Precision agriculture improves agricultural productivity and profitability while reducing costs and environmental impact. However, ML implementation faces challenges such as managing large volumes of data and adequate infrastructure. Despite significant advances in ML applications in sustainable agriculture, there is still a lack of deep and systematic understanding in several areas. Challenges include integrating data sources and adapting models to local conditions. This research aims to identify research trends and key players associated with ML use in sustainable agriculture. A systematic review was conducted using the PRISMA methodology by a bibliometric analysis to capture relevant studies from the Scopus and Web of Science databases. The study analyzed the ML literature in sustainable agriculture between 2007 and 2025, identifying 124 articles that meet the criteria for certainty assessment. The findings show a quadratic polynomial growth in the publication of articles on ML in sustainable agriculture, with a notable increase of up to 91% per year. The most productive years were 2024, 2022, and 2023, demonstrating a growing interest in the field. The study highlights the importance of integrating data from multiple sources for improved decision making, soil health monitoring, and understanding the interaction between climate, topography, and soil properties with agricultural land use and crop patterns. Furthermore, ML in sustainable agriculture has evolved from understanding weather data to integrating advanced technologies like the Internet of Things, remote sensing, and smart farming. Finally, the research agenda highlights the need for the deepening and expansion of predominant concepts, such as deep learning and smart farming, to develop more detailed and specialized studies and explore new applications to maximize the benefits of ML in agricultural sustainability. Full article

(1) Background: The kick of the ball in soccer is considered one of the most important technical gestures in soccer. Despite this, there is little evidence on ball-striking performance factors in base soccer. The main objectives of the present study were to identify the potential factors of long-ball kicking (LBK) performance and to determine the target training cut-off for LBK performance in young soccer players. (2) Methods: A cross-sectional observational study was conducted with 31 soccer players, with ages ranging from 12 to 18 years. Age, anthropometric data, sport experience, range of motion (ROM) and maximal isometric strength (MIS) of the lower limb were noted. Kick-of-the-ball performance was assessed by maximum ball displacement per kick. A k-mean cluster analysis determined two groups according to ball-kicking performance: low group (LPG-LBK) and high group (HPG-LBK). (3) Results: Differences were found between both groups in age, body mass, body mass index, leg length and knee flexion ROM (BF10 ≤ 6.33; δ ≥ 0.86 (moderate or higher)). Among the factors discussed above, age was the strongest predictor of ball-striking performance (odds ratio = 2.867; p = 0.003). The optimal cut-off for age predicting those players most likely to have a higher ball-striking performance was determined to be 13.5 years (p = 0.001; area under the curve = 85.3%). (4) Conclusions: Age over 13.5 increases the chances of a higher optimal ball-striking performance. The flexibility (knee flexion ROM) and strength (knee flexors) must be specifically trained in soccer players beginning at an early age. Full article

Introduction: Football analysis is an applied research area that has seen a huge upsurge in recent years. More complex analysis to understand the soccer players’ or teams’ performances during matches is required. The objective of this study was to prove the usefulness of the expected goals on target (xGOT) metric, as a good indicator of a soccer team’s performance in professional Spanish football leagues, both in the women’s and men’s categories. Method: The data for the Spanish teams were collected from the statistical website Football Reference. The 2023/24 season was analyzed for Spanish leagues, both in the women’s and men’s categories (LigaF and LaLiga, respectively). For all teams, the following variables were calculated: goals, possession value (PV), expected goals (xG) and xGOT. All data obtained for each variable were normalized by match (90 min). A descriptive and correlational statistical analysis was carried out. Results: In the men’s league, this study found a high correlation between goals per match and xGOT (R² = 0.9248) while in the women’s league, there was a high correlation between goals per match (R² = 0.9820) and xG and between goals per match and xGOT (R² = 0.9574). Conclusions: In the LaLiga, the xGOT was the best metric that represented the match result while in the LigaF, the xG and the xGOT were the best metrics that represented the match score. Full article

The aim of this research is to shed light on the complex interactions between player workload, traits, match-related factors, football performance, and injuries in the English Premier League. Using a range of statistical and machine learning techniques, this study analyzed a comprehensive dataset that included variables such as player workload, personal traits, and match statistics. The dataset comprises information on 532 players across 20 football clubs for the 2020–2021 English Premier League season. Key findings suggest that data, age, average minutes played per game, and club affiliations are significant indicators of both performance and injury incidence. The most effective model for predicting performance was Ridge Regression, whereas Extreme Gradient Boosting (XGBoost) was superior for predicting injuries. These insights are invaluable for data-driven decision-making in sports science and football teams, aiding in injury prevention and performance enhancement. The study’s methodology and results have broad applications, extending beyond football to impact other areas of sports analytics and contributing to a flexible framework designed to enhance individual performance and fitness. Full article

Objective: To determine the match injury incidence for a New Zealand amateur domestic female soccer team over two consecutive seasons. Methods: A descriptive, epidemiological observational study was conducted to determine match injury incidence for 49 players over two domestic seasons. Match exposure and injury burden were calculated. Results: A total of 84 match-related injuries resulted in a match injury incidence of 145.5 (95% confidence interval (CI): 117.4 to 180.1) per 1000 match h. Attackers had a higher incidence of injuries for total (200.0 per 1000 match h) and missed matches (152.4 per 1000 match h). The lower limbs had the highest injury incidence (105.6 per 1000 match h), with ankle injury being the most reported (43.3 per 1000 match h) lower limb injury. Over three quarters (75.3%) of the injuries recorded were missed match injuries. Sprains/strains were the most recorded total (86.6 per 1000 match h) injury type. Fractures were recorded as having the highest mean injury burden (68.7 ± 70.4 days). Discussion: Historically, there was a paucity of injury burden data for female football; however, the data presented within this study can be utilised to support the identification of injury patterns and areas to be included within injury reduction programmes. Full article

This research paper examines Sports Analytics, focusing on injury patterns in the National Basketball Association (NBA) and their impact on players’ performance. It employs a unique dataset to identify common NBA injuries, determine the most affected anatomical areas, and analyze how these injuries influence players’ post-recovery performance. This study’s novelty lies in its integrative approach that combines injury data with performance metrics and salary data, providing new insights into the relationship between injuries and economic and on-court performance. It investigates the periodicity and seasonality of injuries, seeking patterns related to time and external factors. Additionally, it examines the effect of specific injuries on players’ per-match analytics and performance, offering perspectives on the implications of injury rehabilitation for player performance. This paper contributes significantly to sports analytics, assisting coaches, sports medicine professionals, and team management in developing injury prevention strategies, optimizing player rotations, and creating targeted rehabilitation plans. Its findings illuminate the interplay between injuries, salaries, and performance in the NBA, aiming to enhance player welfare and the league’s overall competitiveness. With a comprehensive and sophisticated analysis, this research offers unprecedented insights into the dynamics of injuries and their long-term effects on athletes. Full article

SDGs are playing an increasing role in defining sustainability paths for energy-intensive sectors. In particular, the steel sector is promoting several parallel initiatives as a key player sector in the European process industry. This work describes the major focal trends related to the sustainability of steel and presents the principal EU approaches and initiatives linked with the ESTEP action area. The core sustainability issues related to SDGs in the EU steel sector are presented with a particular focus on the quantification approaches. Then, the paper presents different areas for SDG implementation by single organizations in the EU context. Such areas provide an operational path for managing and implementing SDGs. In particular, the key areas include: (1) roadmapping initiatives with a focus on specific sustainability targets; (2) eco-labelling trends with reference to usage per label typology; (3) reporting initiatives by single organizations with a focus on specific SDGs; and (4) representative EU steel R&D projects related to selected sustainability targets. The discussion part focuses on a critical review of all presented areas to summarise the main paths in adopting SDGs targeted at the EU steel sector level. As the final outcome, prime emerging barriers are suggested as well as critical issues in implementing SDG-based sustainability targets. Full article

The aims of this study were to (i) analyze the physical and physiological responses of four matches competition and (ii) to investigate the relationships among three different pitch dimensions of small-sided game (SSG) on the youth soccer players. Fifteen male U19 soccer players (age 17.3 ± 0.5 years, height 175.7 ± 5.6 cm, weight 68.5 ± 8.6 kg, playing experience 7.8 ± 1.4 years) were randomly assigned to three play areas: small (50 m²), medium (SSG-m, 150 m²) and large (SSG-l, 250 m²) area per player including goalkeeper. During the 4-week intervention, both groups performed three sets of 8 min with a passive rest period of 5 min between games. Differences in time-motion characteristics of players were measured with the Global Positioning System and assessed using a repeated measures ANOVA to compare the three game conditions and the magnitude-based inference to evaluate the pairwise comparison effects. The results showed that only the variables distance covered between 7.0–12.9 km·h⁻¹ was not statistically significantly different among game conditions (p < 0.05; η = 0.21; small) and physiological response (i.e., hear rate of playing time spent 85–89% HR_max) also showed differences (p < 0.05; η = 0.25; small). The responses in SSG-m and SSG-l established them ass the format sizes ideal for replicating the physical responses during match competition. These findings could provide relevant information for coaches for use adequate pitch size (areas of 150 m² and 250 m²) to reach the match-play scenarios found in match competition. Full article

Background: the main aim of this study was to analyze the relationship between sole pattern parameters of football boots with the frequency of injuries that occur in semiprofessional and amateur footballers. Methods: The study sample was composed of 77 male football players. All were at least 18 years old, played at least 10 h per week, gave signed informed consent to take part and properly completed the Visual Analogue Scale. This study analysed data from each player’s medical history, including age, injuries, years of practice, field type and surface condition information. Results: The visual analogic score in semiprofessional players was higher (2.05 ± 2.43) than in amateur players (1.00 ± 1.1). A total of 141 lesions were collected, equivalent to 1.81 injuries for each football player studied (n = 77). The result of the ROC curve indicated that the player’s years of practice could predict significantly (p < 0.05) the presence of lower limb injuries, with an area under the curve of 0.714. Conclusions: This study described the predictive capacity of sole pattern characteristics concerning lower limb injuries in amateur and semiprofessional footballers. Football boot variables associated with the number of studs were associated with foot and ankle overload injuries. Full article

Although performance analysis in padel represents a useful process to gain references about players’ technical and tactical behavior, most of the research was conducted in elite compared to the sub-elite competitions. Therefore, this study aimed to describe sub-elite competitions in order to enhance scientific knowledge for sub-elite athletes and technical staff. 4287 shots were analyzed within five areas (time-motion analysis, shots characteristics, errors, serve and points won). Effective playing time and work-to-rest ratio were lower than in elite competitions, while strokes per minute and total match duration were in line with it. Shots were mainly forehand volleys performed under the head, while volleys and smashes were more likely to end with a point in comparison with ground or wall shots. However, sub-elite winning pairs performed fewer volleys than the losing side and fewer errors on volleys. One serve out of five ended in errors (almost half were net errors); fewer errors during serve return shots represented an advantage for the winning pairs. Finally, 65% of the points scored were caused by unforced errors of opponents. This knowledge should help technical staff design specific training programs for sub-elite padel players. Full article

Large-sided games (LSG) are commonly used in the training contexts for providing either technical/tactical or locomotor/physiological stimuli. Despite natural similarities with the official match, the locomotor profile seems to be different, which must be considered by the coaches to identify compensatory strategies for achieving the ideal dose of training. The aim of this study was two-fold: (1) to investigate the locomotor demands imposed by LSGs and the official matches; and (2) to compare the effect of different pitch sizes’ LSG conditions in the locomotor demands. This study followed an observational design. Sixteen professional football players from the same team (26.3 ± 3.0 years old) were included. The study was conducted over four weeks. The same GK + 10 × 10 + GK play format with different pitch sizes (i.e., area per player ranging between 195 m² to 291 m²) was analyzed. Three official matches were also collected in which the 10 most demanding minutes were considered for further comparisons. Only the same players who participated in matches were considered in comparison with the LSG. The data were obtained using a 10-Hz global positioning system technology. Total distance (TD) and mechanical work (MW) scores increased 20% and 23%, respectively, between the smallest and biggest pitch sizes (p < 0.001). There was a significant difference in locomotor intensity metrics between opponents from different positions on the table (p = 0.001). The biggest LSG (i.e., 291 m² per player) was the only one that required similar levels of locomotor intensity as required in the official full match. The present study demonstrates that LSG pitch size variation requires different locomotor intensities. Bigger pitch sizes cause an increase in TD and MW. In addition, considering the position on the table, the level of opponents induces different TD covered. Finally, the largest LSG simulates the official match more accurately. Full article