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Review

Exploring the Structure of Growth and Maturation Research Among Basketball Players Using R Tools †

by
Ximing Shang
1,2,
Jorge Arede
1,2,3 and
Nuno Leite
1,2,*
1
Department of Sports, Exercise and Health Sciences, University of Trás-os-Montes and Alto Douro, 5000-801 Vila Real, Portugal
2
Research Center in Sport, Health, and Human Development (CIDESD), 5000-558 Vila Real, Portugal
3
School of Education, Polytechnic Institute of Viseu, 3504-501 Viseu, Portugal
*
Author to whom correspondence should be addressed.
†
This paper is an extended version of a paper presented at the XII Iberian Basketball Congress, Castelo Branco, Portugal, 7–9 November 2024.
Appl. Sci. 2025, 15(8), 4411; https://doi.org/10.3390/app15084411
Submission received: 16 January 2025 / Revised: 2 April 2025 / Accepted: 12 April 2025 / Published: 16 April 2025
(This article belongs to the Special Issue Science and Basketball: Recent Advances and Practical Applications)
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Abstract

:
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.

1. Introduction

In recent years, with the development trend of the commercialization and globalization of sports, athletes’ identification and high-quality development have become particularly important [1]. In this context, the attention of academia on the growth and maturation (GAM) of young athletes has continued to rise. The identification and development of young sports talent involve many factors, and GAM, as a dynamic process, is believed to have an important impact on young athletes’ short-term and long-term sports performance, mental health, and even future sports participation [2,3,4]. Based on the above concepts, practitioners have emphasized in the long-term athlete development model (LTAD) proposed at an early stage that the development of young athletes should emphasize the matching of different training stages with varying states of personal growth and maturity and make full use of the ‘window of opportunity’ in the natural growth and maturation process to enhance the benefits of training [5]. Although the ‘window of opportunity’ is currently controversial, the introduction and application of the LTAD model illustrates the importance of understanding the growth principles and biological maturity differences of children and adolescents when training young athletes [1]. This is reflected to varying degrees in other athlete development models, including the Developmental Model of Sport and the Youth Physical Development model [6]. Therefore, a comprehensive and multidimensional understanding of the growth and maturation of adolescent athletes is not only critical for understanding the physiological and psychological evolution of adolescent athletes [7,8]. A comprehensive understanding of the GAM process is also positive for refining teaching strategies for young athletes, developing injury prevention programs [9], ensuring physical and mental health [10], and guiding the development of elite athletes through tailored training programs [11]. This, in turn, benefits the identification and development of talent in athletes.
Basketball, as a complex team sport that combines speed, strength, and technique, is popular worldwide for its competitiveness and spectacle. It is one of the most participatory sports and there are a large number of young athletes [12]. Identifying and developing talented young basketball players has become a priority for professional clubs, academies, and national associations [13]. As organizations invest more resources in the talent identification and development process, practitioners have become increasingly interested in the growth and maturation process of young basketball players and the potential impacts.
In an era of rapidly increasing academic publications [14], tracking all published content is becoming increasingly impractical, especially when an emphasis on empirical contributions leads to a large and dispersed stream of research in a contentious field. In this sense, the utility of Citation Network Analysis as a methodological tool to collect, analyze, and figure out enormous amounts of data becomes important [15]. And the combination of Citation Network Analysis and bibliometric review (Biblio) has been applied in various fields [16], including climate change [17], patent mining [18], and sports [19,20,21]. This analytical approach offers a structured means to dissect the expansive corpus of literature, drawing out pivotal trends, thematic evolutions, and seminal contributions that shape the discourse in specific academic terrains [14,22,23]. And it could provide a periodic knowledge synthesis that could help researchers understand and more organized the structure of a research field, as there are several hundred research outcomes across different disciplines and decades [24,25]. In our investigation, we utilized R tools, which are recognized for their adaptability and effectiveness in data analysis, alongside advanced bibliometric review procedures.
Research has shown that there is a selection bias in the identification of young basketball talent and that maturity differences caused by the different rates of development among young players are considered to be one of the reasons for this phenomenon [26,27]. Specifically, young players of the same chronological age may have a 3–6-year difference in biological maturity [28]. This imbalance in physiological development means that early maturing players generally have certain advantages in physical indicators such as height, weight, and bone density compared to late maturing players, and these physical advantages will translate into advantages in sports performance in training and competition environments, making it easier for early maturing players to stand out in the same age group selection and have the opportunity to develop in high-level teams [29,30]. Currently, practitioners have adopted the methods of biological banding and numbered tags in order to minimize the bias caused by differences, with some success [31].
Meanwhile, the growth process is accompanied not only by selection bias caused by individual differences in maturity but also by a relatively higher risk of sports injuries in youth athletes compared to adults, particularly during the peak height velocity (PHV) phase [32,33]. Research indicates that among every 100 youth basketball players, approximately 22.7 to 33.1 individuals experience sports injuries. When calculated based on participation time, an estimated 2.64 to 4.03 injury incidents occur per 1000 h of basketball play [34]. Common injury sites for youth basketball players include the ankle and knee, with a particularly high likelihood of recurrent ankle injuries [35]. The heightened injury risk in youth athletes can be attributed to the rapid physiological changes driven by the increased secretion of growth hormones during this developmental phase. These changes result in alterations in limb length, muscle mass, moment of inertia, and neuromuscular control capabilities. However, these developmental changes are often not synchronized, leading to a temporary decline in motor control known as the ‘adolescent awkwardness’ phase that sees a temporary decline in coordination and movement efficiency that occurs during rapid growth phases, often leading to clumsiness in motor tasks such as running or jumping. And that also significantly increases the likelihood of injuries during physical activities [36,37]. To accurately assess the maturation status of youth athletes, researchers commonly employ methods such as bone age assessment, secondary sexual characteristic evaluation, maturity offset calculation, and predicted adult height percentage estimation [38,39]. These approaches provide valuable insights for talent identification and injury prevention. However, each method has its own limitations in terms of adaptability. For instance, bone age assessment and secondary sexual characteristic evaluation are considered invasive, while calculations like maturity offset and predicted adult height percentage have been deemed insufficiently accurate in certain studies [40]. Therefore, continuous optimization of these assessment methods is necessary to meet the varying demands of different sports contexts and environments. Such advancements will help clarify the dynamic characteristics of the growth and maturation (GAM) process in youth athletes, offering more precise guidance for both scientific research and practical applications [41,42].
The field of growth and maturation (GAM) research in youth basketball has evolved over the years, yet the literature remains highly fragmented across disciplines, methodologies, and theoretical perspectives. This fragmentation poses challenges for researchers, coaches, and sports practitioners in synthesizing findings and applying them effectively to athlete development. Bibliometric analysis serves as a powerful tool to address this issue, offering a systematic method to map research trends, identify influential works, and uncover collaboration patterns. By applying bibliometric mapping, this study provides a structured synthesis of GAM research, clarifying how different areas of inquiry interconnect and evolve over time. Through this approach, we aim to facilitate a clearer understanding of the research landscape and support evidence-based decision-making in youth basketball training and talent development. In this context, this study aims to employ citation analysis to systematically explore the research network and trends related to youth basketball GAM. Specifically, our objectives are as follows: (1) mapping GAM literature in basketball by analyzing the influence of various nations, organizations, writers, journals, and terms using the Biblioshinny in the present study; (2) quantitatively evaluate the most prominent contributors and the interconnectedness of GAM research in basketball based on published research articles; and (3) examine the structure of the GAM research field and identify subgroups within specific areas of GAM literature in basketball. This study reveals the structure of research in the field of youth athletic maturity and sophistication through bibliometric methods, providing scholars with a systematic map of research and identifying possible future breakthroughs. In addition, this study helps to optimize the application of youth sports maturity assessment methods and provides a scientific basis for practice. This paper extends our earlier work presented at the XII Iberian Basketball Congress, 7–9 November 2024; Castelo Branco, Portugal [43].

2. Methods

The search strategy was designed to encompass various aspects of growth and maturation among youth involved in basketball because the collective nature of such activities amplifies the implications of maturation differences, influencing training programs, competition outcomes, and player development. And we employed a comprehensive and methodical search strategy within the Web of Science Core Collection (WoS; Clarivate Analytics, Philadelphia, PA, USA), an internationally recognized database known for its credibility [44] and relevance in bibliometric research [45]. Web of Science was selected as the sole database due to its well-documented strengths in citation network analysis and its structured metadata, which enable reliable bibliometric mapping. Although other databases such as Scopus and PubMed contain relevant literature, their differing citation indexing systems and metadata structures could introduce inconsistencies when constructing citation networks. The choice of Web of Science ensures a standardized dataset for analyzing citation relationships, thematic structures, and research trends in the field.
The search was conducted in August 2024 and strategically designed to capture a broad range of research focusing on growth, maturation, and the physical development of youth in the context of basketball. To define the temporal scope, we set the inclusion period from 2003 to 2024. This decision was informed by bibliometric indicators showing a significant increase in research output on growth and maturation in youth sports starting in the early 2000s. This trend aligns with the rise of systematic investigations into long-term athlete development (LTAD) and the increasing application of biological maturation assessments in sports science.
As shown in Figure 1, the screening process adhered to the guidelines for reporting Biblio and the citation network analysis [46], focusing on titles and abstracts to filter the records according to predefined inclusion and exclusion criteria. Two independent researchers reviewed the titles and abstracts of all retrieved records. Any disagreements between the reviewers were resolved through discussion, and if consensus could not be reached, a third senior researcher provided the final decision. To assess the reliability of the screening process, inter-rater agreement was calculated using Cohen’s kappa coefficient (k = 0.993), which exceeds the commonly accepted threshold for reliability (k > 0.6), demonstrating a very high level of consistency between the reviewers. This multi-step process ensured that the final dataset comprised studies directly relevant to growth and maturation research in youth basketball players.

2.1. Source of Data and Search Strategy

The terms used were TS (“growth” OR “maturation” OR “maturity” OR “physical development” OR “pubertal development” OR “biological maturity”) AND (“adolescents” OR “youth” OR “teen*” OR “juniors”) AND (“sport”).
A total of 1160 records were retrieved and continued to process selection with the criteria of inclusion and exclusion.

2.2. Inclusion and Exclusion Criteria

The inclusion criteria were as follows:
  • Articles designed to investigate issues related to the growth and maturation within basketball.
  • Only articles written in English were considered eligible.
The exclusion criteria were as follows:
  • Articles that do not relate to investigating issues related to the growth and maturation within basketball. Examples include studies focusing solely on other team sports, or those that do not emphasize basketball players.
  • Records related to announcements and book reviews were excluded, focusing solely on published research papers. For example, an announcement about an upcoming conference or a book review discussing the contents of a newly published book was excluded.
  • The paper time span was set from 1 January 2003 to 31 August 2024 to examine the trend over the past years. Any papers published outside this period were excluded.
And we found 141 included research articles in the final selection for Biblio reviewing.

2.3. Analytical Methods

This study employed RStudio software (RStudio Integrated Development Environment (IDE), Version 4.3.3, Release Date: 29 February 2024; RStudio, Inc., Boston, MA, USA) [47] for bibliometric analysis. The Bibliometrix (Version 4.4.2, Release Date: 15 November 2023) and Biblioshinny (Version 4.3.0, Release Date: 1 July 2024) packages were used for data processing and visualization [48]. Additionally, Python (Version 3.10.8, Release Date: 4 October 2023, Python Software Foundation, Wilmington, DE, USA) and Excel (Version 2411 Build 16.0.18227.20082, Release Date: 8 November 2024, Microsoft Corporation, Redmond, WA, USA) were employed to visualize the analysis results as tables, charts, and network diagrams.
In the realm of academic research, the employment of RStudio software to analyze timeline diagrams has emerged as an efficacious means of visualizing the intricate distribution and dynamic evolution of research keywords. This approach is not only innovative but also highly practical in the context of modern research landscapes.
As elaborated by Gupta (2019) [48] in a comprehensive study, this methodology is deeply rooted in lifecycle theory. By leveraging this well-established theoretical framework, researchers are able to categorize research directions in a systematic manner. The categorization is carried out according to two fundamental dimensions: the development degree, which can be effectively represented by density, and the relevance degree, often denoted by centrality (Table 1). The development degree (density) reflects how well-developed a particular research area is. A high density might indicate a mature research topic with a large body of literature, while a low density could suggest a relatively nascent area with limited exploration. On the other hand, the relevance degree (centrality) measures the importance of a research direction within the broader research field. A highly central topic is likely to be interconnected with many other areas of study, having a significant impact on the overall research ecosystem. By segmenting research themes into four categories, this approach offers a temporal perspective on hotspots and trends within the field (Figure 2).
For the research themes map and research themes evaluation, we set a parameter threshold such that only topics with a minimum of six citations are included in the Thematic Evaluation and Thematic Map. This criterion ensures that only topics with sufficient impact are visualized, thereby enhancing the robustness and interpretability of our analysis.

3. Results

3.1. General Overview

As shown in Table 2, we analyzed 141 GAM articles with basketball players found in Web of Science that were published before 2023. The dataset, spanning from 2003 to 2024, comprises 141 documents sourced from 68 journals and other publications. The production annual growth rate exhibits a strong rate of 11.59%. A substantial number of authors (576) contribute to the field, with an average of 5.42 co-authors per document, signifying a highly collaborative research landscape. Notably, international collaborations account for 52.60% of publications.

3.2. Publications Analysis Considering Contributions of the Main Authors

As shown in Table 3, the number of articles published by different countries is presented alongside the counts for single-author papers (SCPs), multi-author papers (MCPs), publication frequency (Freq), and the ratio of multi-author papers (MCP_Ratio) [49,50].
Portugal leads the field with 31 articles, of which 8 are single-author papers and 23 are multi-author papers, reflecting a multi-author paper ratio (MCP_Ratio) of about 74.19%. Brazil and Spain follow with 24 and 20 articles, respectively. Notably, Portugal exhibits the highest MCP_Ratio, highlighting a strong emphasis on collaborative research.

3.3. Evolutionary Path Analysis Based on Timeline Diagrams

3.3.1. Timeline Analysis of Research Themes

The timeline diagrams framework divides keywords into the following themes:
Basic Themes: Themes such as growth, ‘strength’, and ‘age’ fall into this category. These themes are characterized by high centrality but low density, indicating their broad relevance and foundational importance within the field. The prominence of ‘age’ and ‘strength’ reflects that the researchers keep a significant interest in the influence of age and the result of strength during the GAM of basketball players. The foundational nature of these themes underscores their critical role in shaping future research and practical applications in the GAM of youth basketball.
Motor Themes: Themes like performance, ‘maturity’, and ‘maturation’ are classified as motor themes. These themes are essential for understanding the performance and the GAM metrics of young athletes. Research in these areas focuses on both physical and psychological development during the GAM. Developing effective training programs and interventions to improve these attributes is a key research focus, significantly contributing to the overall development of youth.
Niche Themes: Themes such as ‘injury’, and ‘knee’ are categorized as niche themes. These highly specialized themes have lower centrality but are crucial within their specific areas. Research is more targeted and detailed, aiming to identify risk factors for common sports injuries and develop mitigation strategies. This specialized knowledge is vital for ensuring young athletes’ safety and well-being, minimizing injury incidence, and enhancing recovery processes.
Emerging Themes: Themes such as boys, ‘exercise’, and ‘physical activity’ represent areas that are emerging. These themes have low density and centrality, indicating they are either gaining attention as new areas of interest or losing relevance. Emerging themes often reflect new research directions driven by societal needs or advancements in scientific understanding, such as the holistic benefits of physical activity. Declining themes may indicate that foundational questions have been largely answered, shifting focus to more current issues.

3.3.2. Thematic Evolution in Youth Sports Research

Analyzing the thematic evolution of publications provides critical insights into the shifting research priorities within the field of youth sports. As illustrated in Figure 3, the diversity of research subjects has increased notably over time. Initially focused on a singular theme, the field has expanded to encompass multiple themes by 2024, reflecting its dynamic and evolving nature.
From 2003 to 2010, the research focus transitioned from basketball players to children and age. This shift indicates an increased interest in understanding the physical attributes of young athletes. Researchers began to be interested in the influence of age during growth and maturation on the impact of athletic performance.
The focus between 2011 and 2015 and 2016 and 2020 moved from ‘performance’ and ‘growth’ to broader themes such as ‘selection’, ‘achievement-motivation’, and ‘injures’. This shift represents a more comprehensive approach to assessing and enhancing athletic performance. Research during this period not only measured physical capabilities but also explored factors contributing to optimal performance, including psychological aspects, training methodologies, and recovery strategies. The inclusion of ’injuries’ highlights a growing concern with the potential to be hurt during the GAM of players.
From 2020 to 2024, there has been a significant focus on the different practice strategies and more border participants of basketball sport. Research in these years has prioritized the development of sport teaching strategies and also the practice methods. The emphasis on fat shows that researchers are motivated to include a broader group of players (females and ‘fatter’ participants) into the GAM research of basketball players.

4. Discussion

Our research initiative commenced with a comprehensive and rigorous data collection methodology. We thoroughly analyzed a massive academic literature and assembled 1160 research publications that were likely relevant to our study. These publications were sourced from multiple academic sites and databases, showcasing a wide range of scholarly viewpoints. A stringent selection process was implemented, adhering to a defined and exacting set of criteria. The criteria were created to ensure the relevance, quality, and significance of the selected publications for further study. Subsequent to this comprehensive assessment, we identified 141 GAM publications that specifically focused on basketball players. These publications were sourced from the Web of Science, a reputable academic repository, and were published prior to 2024.
International collaborations accounted for 52.60% of all publications, reflecting a growing global research network in growth and maturation studies among youth basketball players. This high level of collaboration suggests that researchers from different regions are increasingly sharing data, methodologies, and analytical frameworks, which enhances the robustness of maturity assessments across diverse populations. Prior studies in sports science have highlighted that international research networks contribute to the development of standardized protocols for biological maturity assessment [38], ensuring their applicability across different competitive levels and cultural contexts. Furthermore, such collaborations facilitate comparative studies, allowing researchers to identify regional variations in growth patterns, which can inform tailored training and injury prevention strategies [51]. Given these benefits, future research should explore how institutional and funding mechanisms influence global partnerships and how collaborative efforts can be optimized to address gaps in youth athletic development [52,53].
Analysis of the conceptual framework of this topic revealed that GAM research on basketball players predominantly centers on three critical components: athletic performance, strength, and injury-related characteristics. Sports performance is a multifaceted concept encompassing elements such as shot precision, velocity, agility, and overall game awareness. Conversely, strength is crucial as it directly affects a player’s ability to carry out physically demanding tasks on the court, such as rebounding, defending, and driving to the basket [54,55]. Research pertaining to injuries is essential since it aims to prevent and manage injuries that can significantly hinder a player’s development and career [56].
Our thematic analysis revealed salient subjects, including performance and maturation. These challenges demonstrated a significant degree of integration into the core research subject. Their extensive study has produced a significant corpus of knowledge, with several studies examining the factors influencing a player’s performance during physical and psychological development. Studies have investigated the effects of hormonal variations during puberty on an athlete’s strength, velocity, and stamina, along with the requisite modifications to coaching strategies. The thematic map, a visual representation of the research landscape, highlighted essential themes such as growth, strength, and age. Although these themes are essential for understanding GAM in basketball players, they were recognized as somewhat underdeveloped compared to other themes. There is a clear need for more focused research efforts. While there is some comprehension of the overall growth patterns of young basketball players, additional research might be conducted to investigate how different training regimens may improve growth concerning particular basketball-related skills.
The analysis of the historical correlation between centrality and density in prior studies was a crucial aspect of our research [15,57]. Centrality signifies the importance of a particular subject within the wider research area, whereas density reflects the extent of research conducted on that topic [21,58]. Through the analysis of the relationship between these two characteristics across time, we identified the maturity and importance of several themes in the development of juvenile athletes. This understanding is crucial as it outlines a foundation for future research objectives. A key topic with low density signifies a domain that requires further exploration.
Nevertheless, similar to any research endeavor, our study included specific limitations. To acquire the most authentic and reliable publishing information, we restricted our inquiry to publications indexed in the WoS database. While the WoS database is esteemed for its exceptional quality and comprehensive coverage, this choice naturally risks overlooking important information from other equally crucial databases, such as PubMed and Scopus. These databases may provide unique research perspectives, case studies, and experimental findings that could have improved our understanding of GAM studies in basketball players. Secondly, the substantial volume of included publications presented a significant barrier. Owing to the substantial quantity of publications, our analysis was confined to the titles and abstracts of each article. This strategy, while efficient in terms of time and resources, posed difficulties in accurately identifying concerns related to football and running. Due to the similarity in physical demands and player development between these sports and basketball, misclassification was inevitable. This may have resulted in errors in identifying key terms compared to a more comprehensive manual annotation process. Manual annotation would have enabled a more thorough understanding of each article’s content, ensuring the accurate identification of all relevant key terms [59,60]. The absence of language constraints in our search methodology introduced certain biases. In the global academic community, English-language articles are generally perceived as having greater influence due to their wider dissemination and accessibility. However, by neglecting to filter for language, we may have inadvertently accentuated English-language research, leading to a language-based bias [61]. Publications in languages other than English, especially from regions with unique research cultures and perspectives, may have presented important findings that were probably overlooked. The interplay of these elements may influence the accuracy of our bibliometric analysis.
Despite these limitations, our investigation’s findings revealed a vibrant field characterized by productivity and robust interconnections among authors and publications. The significant number of publications, the broad involvement of authors, and the plethora of citations signify a vibrant and active research community. We offer substantial insights into the trends within this subject, encompassing emerging research areas, the decline of particular themes, and persistent topics of interest. Moreover, we highlight the significant role of notable authors and papers. These key individuals often define the study agenda, introduce innovative methodologies, and inspire other scholars to explore related topics.

5. Conclusions

Overall, this bibliometric analysis aims to enhance the academic understanding and practical application of growth and maturation in youth team sports. Our objective was to augment the current body of knowledge by conducting a comprehensive analysis of the research landscape. By identifying key thematic clusters and research gaps, this study provides a structured overview of existing knowledge on growth and maturation in youth basketball. The results highlight the predominance of research on sports performance, strength, and injuries, while foundational themes such as growth and maturation processes remain underdeveloped.
By mapping the current landscape, this study serves as a foundation for subsequent empirical investigations, enabling researchers to build on established knowledge and enhance evidence-based practices in youth basketball development. To better capture maturation-related performance fluctuations over time, future research should address these gaps by integrating longitudinal studies on maturation-related performance fluctuations. And examining the role of biological age in talent selection could also be a crucial factor in talent selection and athlete development by offering a structured overview of the current state of research, exploring effective load management strategies for effective load management and injury prevention during growth spurts. By highlighting essential areas for future research, we seek to reinforce the foundations of youth sports programs. This involves focusing on enhancing training methods based on a player’s growth stage, devising targeted injury prevention strategies, and promoting holistic athlete development.

Author Contributions

Conceptualization, X.S., J.A. and N.L.; methodology, formal analysis, X.S. and J.A.; investigation, X.S. and J.A.; resources, X.S. and J.A.; data curation, X.S. and J.A.; writing—original draft preparation, X.S. and J.A.; writing—review and editing, X.S., J.A. and N.L.; visualization, X.S. and J.A.; supervision, N.L.; project administration, N.L.; funding acquisition, N.L. All authors have read and agreed to the published version of the manuscript.

Funding

X. Shang was funded by China Scholarship Council, grant number 202207920001.

Conflicts of Interest

The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Figure 1. The workflow of Biblio reviewing: (1) identification; (2) scanning; (3) included.
Figure 1. The workflow of Biblio reviewing: (1) identification; (2) scanning; (3) included.
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Figure 2. Thematic map of growth and maturation of youth team sports.
Figure 2. Thematic map of growth and maturation of youth team sports.
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Figure 3. Thematic evolution of the growth and maturation of youth team sports.
Figure 3. Thematic evolution of the growth and maturation of youth team sports.
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Table 1. Thematic classification section.
Table 1. Thematic classification section.
Theme CategoryDefinitionCentrality RangeDensity Range
Motor Themes Highly developed and essential to the field, with strong external connections.HighHigh
Basic Themes Broadly relevant but less internally developed, forming the foundation of the field.HighLow
Emerging ThemesWeakly connected and still developing (or disappearing).LowLow
Niche Themes Internally well-developed but weakly connected to the broader research field.LowHigh
Table 2. Main information of the papers.
Table 2. Main information of the papers.
DescriptionResults
Timespan2003:2024
Sources (Journals, Books, etc.)68
Documents141
Annual Growth Rate %11.59
Document Average Age5.69
Average citations per doc22
References4461
Keywords Plus (ID)469
Author’s Keywords (DE)352
Authors576
Authors of single-authored docs2
Single-authored docs2
Co-Authors per Doc5.42
International co-authorships %52.60
Table 3. Top 10 productive countries on related research.
Table 3. Top 10 productive countries on related research.
CountryArticlesArticles %SCPMCPMCP %
PORTUGAL3120.1382374.19
BRAZIL2415.5871770.83
SPAIN2012.9913735.00
AUSTRALIA106.495550.00
USA95.848111.11
UNITED KINGDOM63.891583.33
POLAND53.253240.00
GERMANY42.591375.00
ITALY42.592250.00
CANADA31.952133.33
SCP: Single Country Publishing; MCP: Multiple Country Publications; Freq: Percentage of One Country Compared with Total Countries Publications; MCP_Ratio: Ratio of Multiple Country Publications Compared with Total Publications.
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Shang, X.; Arede, J.; Leite, N. Exploring the Structure of Growth and Maturation Research Among Basketball Players Using R Tools. Appl. Sci. 2025, 15, 4411. https://doi.org/10.3390/app15084411

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Shang X, Arede J, Leite N. Exploring the Structure of Growth and Maturation Research Among Basketball Players Using R Tools. Applied Sciences. 2025; 15(8):4411. https://doi.org/10.3390/app15084411

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Shang, Ximing, Jorge Arede, and Nuno Leite. 2025. "Exploring the Structure of Growth and Maturation Research Among Basketball Players Using R Tools" Applied Sciences 15, no. 8: 4411. https://doi.org/10.3390/app15084411

APA Style

Shang, X., Arede, J., & Leite, N. (2025). Exploring the Structure of Growth and Maturation Research Among Basketball Players Using R Tools. Applied Sciences, 15(8), 4411. https://doi.org/10.3390/app15084411

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