Gephi Software Research Articles

Identification of cohesive subgroups in a university hall of residence during the COVID-19 pandemic using a social network analysis approach

The aims: (i) analyze connectivity between subgroups of university students, (ii) assess which bridges of relational contacts are essential for connecting or disconnecting subgroups and (iii) to explore the similarities between the attributes of the subgroup nodes in relation to the pandemic context. During the COVID-19 pandemic, young university students have experienced significant changes in their relationships, especially in the halls of residence. Previous research has shown the importance of relationship structure in contagion processes. However, there is a lack of studies in the university setting, where students live closely together. The case study methodology was applied to carry out a descriptive study. The participation consisted of 43 university students living in the same hall of residence. Social network analysis has been applied for data analysis. Factions and Girvan–Newman algorithms have been applied to detect the existing cohesive subgroups. The UCINET tool was used for the calculation of the SNA measure. A visualization of the global network will be carried out using Gephi software. After applying the Girvan–Newman and Factions, in both cases it was found that the best division into subgroups was the one that divided the network into 4 subgroups. There is high degree of cohesion within the subgroups and a low cohesion between them. The relationship between subgroup membership and gender was significant. The degree of COVID-19 infection is related to the degree of clustering between the students. College students form subgroups in their residence. Social network analysis facilitates an understanding of structural behavior during the pandemic. The study provides evidence on the importance of gender, race and the building where they live in creating network structures that favor, or not, contagion during a pandemic.

Active Participation of Buildings in the Energy Networks: Dynamic/Operational Models and Control Challenges

New advances in small-scale generation and consumption technologies have shifted conventional buildings’ functionality towards energy-efficient active buildings (ABs). Such developments drew the attention of researchers all around the world, resulting in a variety of publications, including several review papers. This study conducts a systematic literature review so as to analyse the concepts/factors enabling active participation of buildings in the energy networks. To do so, a relatively large number of publications devoted to the subject are identified, introducing the taxonomy of control and optimisation methods for the ABs. Then, a study selection methodology is proposed to nominate potential literature that has investigated the role of ABs in the energy networks. The modelling approaches in enabling flexible ABs are identified, while the potential challenges have been highlighted. Furthermore, the citation network of included papers is illustrated by Gephi software and analysed using “ForceAtlas2” and “Yifan Hu Proportional” algorithms so as to analyse the insights and possibilities for future developments. The survey results provide a clear answer to the research question around the potential flexibility that can be offered by ABs to the energy grids, and highlights possible prospective research plans, serving as a guide to research and industry.

A Bridging Centrality Plugin for GEPHI and a Case Study for Mycobacterium Tuberculosis H37Rv.

Bridging Centrality (BriCe) is a popular measure that combines the Betweenness centrality and Bridging coefficient metrics to characterize nodes acting as a bridge among clusters. However, there were no implementations of the BriCe plugin that can be readily used in the GEPHI software or any other software dedicated to graph-based studies. In this paper, we present the BriCe plugin for GEPHI. It is available as a third-party functionality from the native GEPHI interface as a handy plugin to add; hence, no additional download and installation process is necessary. The BriCe plugin for GEPHI is open-source, and one can access the code through the GEPHI GitHub repository. As a use case of the BriCe plugin, we analyzed the genome of Mycobacterium tuberculosis H37Rv to identify biological explanations on why some proteins were ranked with top BriCe values? For instance, we were able to formulate a new hypothesis combining the predicted sub cellular localization and high BriCe values concerning lipopolysaccharides (LPS) exportation. Our hypothesis provides a possible link among proteins of a glycosyltransferase group and the type VII Secretion System. The Bridging Centrality plugin for GEPHI is an easy to use tool for analyzing complex graphs and draw novel insights from graphical data.

Mapping the biomedical sciences using Medical Subject Headings: a comparison between MeSH co-assignments and MeSH citation pairs.

Objective:This study compares two maps of biomedical sciences using Medical Subject Headings (MeSH) term co-assignments versus MeSH terms of citing/cited articles and reveals similarities and differences between the two approaches.Methods:MeSH terms assigned to 397,475 journal articles published in 2015, as well as their 4,632,992 cited references, were retrieved from Web of Science and MEDLINE databases, respectively, which formed over 7 million MeSH co-assignments and nearly 18 million direct citation pairs. We generated six network visualizations of biomedical science at three levels using Gephi software based on these MeSH co-assignments and citation pairs.Results:The MeSH co-assignment map contained more nodes and edges, as MeSH co-assignments cover all medical topics discussed in articles. By contrast, the MeSH citation map contained fewer but larger nodes and wider edges, as citation links indicate connections to two similar medical topics.Conclusion:These two types of maps emphasize different aspects of biomedical sciences, with MeSH co-assignment maps focusing on the relationship between topics in different categories and MeSH direct citation maps providing insights into relationships between topics in the same or similar category.

An Approach to Exploring Non-Governmental Development Organizations Interest Groups on Facebook

This paper presents an approach for analyzing the stakeholders from various organizations based on their Facebook activity. On a practical level, the proposed approach has been applied in two of the Non-Governmental Development Organizations (NGDOs) with the largest number of delegations in the province of Cadiz: Red Cross Cadiz, and Caritas Asidonia Jerez. The purposes of the research are to describe the management of marketing activities on Facebook; to identify the network stakeholders, their roles in the communication, and the community generating factors; and to position organizations according to their leadership, activity, and popularity in the network. This study used a mixed-methods research design, combining personal interviews and Social Network Analysis (SNA). The SNA provided insights into the various ways the analyzed NGDOs are active on Facebook, the roles they play in communication, and how communities are generated. Moreover, the SNA made it possible to visualize the interactions between organizations and their stakeholders within the Facebook environment using the Gephi software package. Two factors that generate communities were detected in the results: the organization’s nature and its geographical location. Moreover, two solutions were proposed to determine the organizations’ positioning according to their roles in communication. Consequently, two maps were created, a two-dimensional map with the activity and popularity of the parameters, which shows that just because an NGDO is active does not mean it is popular (in terms of receiving “likes”), and a second three-dimensional graph to which a leadership parameter was added. In this last map, four groups of important actors can be seen, with one group formed by the organizations with the best ratings on the three dimensions, and the other three with a low level of leadership in common but who were different in terms of the popularity and activity dimensions.

Defining categories of Fintechs: A Categorization Proposal Based on Literature and Empirical Data

Purpose – The analysis of the competitive impact of FinTechs requires the standardization of their categories to compare their products and services with the already delivered by incumbent banks. In this study, we address the problem of the multiplicity of FinTechs categories and provide a solution using content and cluster analysis.Theoretical framework – The literature about FinTechs. In our bibliographical research, we do not find works aiming to present a standard definition of categories of FinTechs. This type of work is almost nonexistent and categorization of FinTechs is defined as a “blurry issue”.Design/methodology/approach – In this study, we address the problem of the multiplicity of FinTechs categories and provide a solution using content analysis, cluster analysis, and the software Gephi.Findings – The result is a model comprised of nine FinTechs categories: Payments and Transfers; Exchange; Lending; Insurance; Investments; Advice; B2B; Digital Banks; and Others. We also elaborate a portfolio with 157 products and services offered by Brazilian incumbent banks, which allows the comparison between these two types of companies.Originality/value – The main contribution is the use of objective criteria and existing literature, as well as Gephi software, to build categories of FinTechs analysis, an emerging theme in financial market studies.

Social Interaction and Academic Performance of Construction Management Students

Social interaction between students is a crucial but under-researched part of the education realm. Understanding how connections form in university classes and their effects on learning outcomes may provide extraordinary knowledge for researchers, educators, and policy-makers. This paper collected data from the questionnaire survey and then processed them with Gephi software to produce visualization and measurement. Initial results seem to indicate a significant correlation between students' connectedness and academic performance in one class. However, in another class, the results show a contrasting situation as there is no evidence that social network attributes impact learning performance. Taken together, these results would seem to suggest that the characteristics of the network should be judged on a case-by-case basis, and large-scale SNA analyses have been rarely reported. This present study provides a springboard for a new way to shed some light on classmates' interconnection. Using a similar approach to this article, it is believed that there is ample opportunity to study the association between classmate connectedness and career success. Research techniques and approaches around Social Network Analysis are expected to evolve further in the foreseeable future.

Social Connectivity, Sentiment and Participation on Twitter during COVID-19.

In a transnational context defined by the irruption of COVID-19 and the social isolation it has generated around the world, social networking sites are essential channels for communicating and developing new forms of social coexistence based on connectivity and interaction. This study analyzes the feelings expressed on Twitter through the hashtags #YoMeQuedoEnCasa, #stayhome, #jeresteàlamaison, #restealamaison, #stoacasa, #restaacasa, #ficaemcasa, #euficoemcasa, #ichbleibezuHause and #Bleibzuhause, and the communicative and social processes articulated from network participation, during the lockdown in 2020. Through Gephi software, the aspects underlying the communicative interaction and the distribution of the network at a global level are studied, with the identification of leaderships, communities and connectivity nodes. As a result of this interaction, the emergence of social and organizational links derived from community participation and motivated by the common interest of preserving health and general wellbeing through collective action is detected. The study notes the presence of feelings of solidarity, a sense of community and social support among connected crowds who, despite being in geographically dispersed settings, share similar concerns about the virus effect.

Mapping terrorism in the academic landscape of business field of study: a bibliometric study of the past 30 years

PurposeTerrorism is as old as humanity itself, but its new form in the twenty-first century is adversely affecting the performance of businesses in both developing and developed countries. The purpose of this study is to identify and analyse the evolution and diffusion of academic knowledge on the topic of terrorism in business-related literature.Design/methodology/approachData was gathered from two databases, namely, the Scopus and Web of Science over 30 years (1990–2019). The search terms related to terrorism in titles, abstracts and authors’ keywords, which resulted in a total of 1,097 articles. Bibliometric methods, including a thematic and content analysis identifying main themes and using Gephi and VOSviewer software, were used to analyse the data.FindingsThe results reveal the productivity of the main actors, current thematic choices and future research opportunities. The main thematic areas of the research arising from the bibliometric analysis included the impact of terrorism on economic growth, Foreign Direct Investment, tourism, stock market reforms, security of multinational corporations as a result of terrorism and finally, the impact of political instability and terrorism on business. This study’s findings may guide the research of future academics and assist policy stakeholders in their strategic choices related to future business development.Research limitations/implicationsThe study has certain limitations that are inherent to the bibliometric methods or to the choices related to data collection and processing.Practical implicationsThis study recognised evolution and trends regarding the influence of terrorism on businesses, which is crucial information for the development of business and policy strategies in the future. These strategies should enhance the ability of businesses to cope with the negative effects of terrorism and make these effects less devastating. For academics, this study provides relevant insights on recent research trends in the field of terrorism in business and emerging future academic thematic opportunities.Social implicationsThe findings of the study indicate that issues of terrorism in business have broader social implications, which both academia and policy stakeholders can attend with their work.Originality/valueThis bibliometric review offers new insights into terrorism from the business lens by identifying the common streams of research in the field, along with the key journals, articles, countries, institutions, authors, data sources and networks in this field. The future research directions in this field of knowledge are also articulated in the study.

Prediction of the molecular mechanism of eucommiae Cortex - Achyranthis bidentatae radix in the treatment of osteoarthritis: network pharmacology and molecular docking

Objective To retrieve the core drug of osteoarthritis in clinic using Data Mining, predict the drug molecular action target through the Network Pharmacology, identify the key nodes of the interaction by combining with the related targtes of osteoarthritis, explore the pharmacological mechanism of Traditional Chinese Medicine against osteoarthritis and other possible mechanisms of actions. Methods to retrieve the commonly used therapeutic formulations for osteoarthritis patients in clinical with PubMed, CNKI, VIP, CBM, Wan Fang Database and other databases, and screen out the core drugs through the Ancient and Modern Medical Case Cloud Platform and software Gephi, filter out the core drug molecules and targets combined with TCMSP database and the targets of osteoarthritis in Genecard and OMIM database, plunge those data into R project and Cytoscape to construct the intersection model of Drug molecule-osteoarthritis, establish PPI network and GO and conduct KEGG enrichment analysis with String database. Vina molecular docking was finally implemented to draw molecular docking diagram, and the results were analyzed after comprehensive analysis. Results The core drug pairs were identified as ‘Eucommiae Cortex - Achyranthis Bidentatae Radix’ through correlation analysis, complex network analysis based on the coefficient. ‘Eucommiae Cortex - Achyranthis Bidentatae Radix’ can intervene cell behavior through multiple pathways and regulate cell metabolism, cytokine synthesis, oxidative and cellular immunity with the help of topology analysis in String Database. Conclusions The core molecules of Quercetin and Kaempferol derived from ‘Eucommia bark – achyranthes’ can change the spatial conformation of PTGSs by hydrogen bonding with PTGSs, the hydrophobic bonds and van der Waals forces generated by Baicalein, Wogonin and β-carotene, thereby changing the activity of PTGSs and affecting bone properties the process of osteoarthritis.

Five decades of the International Endodontic Journal: Bibliometric overview 1967-2020.

The International Endodontic Journal (IEJ) has served as a platform for research and clinical practice in Endodontics since 1967. This study provides a bibliographic analysis and overview of the publications that have appeared in the IEJ from 1967 to 2020. A literature search was performed in Elsevier's Scopus database to locate all the publications of the International Endodontic Journal. Various bibliometric software packages including the open-source visualization software Gephi and Biblioshiny (version 2.0) were employed for data visualization and analysis. A total of 3739 records with citation and bibliographic details were selected and retrieved to allow a bibliometric analysis to be performed. The bibliometric analysis indicates that the IEJ has grown both in terms of productivity and influence. Over time, the journal has been associated with an increase in the number of manuscripts published and the citations they have attracted, but with minor downward fluctuations in citations in the last few years. Bibliographic coupling of the IEJ articles revealed that the major research themes published in the journal include 'endodontics', 'root canal treatment', 'calcium hydroxide', 'apical periodontitis', 'mineral trioxide aggregate', 'microbiology', 'cyclic fatigue', 'cone-beam computed tomography' and 'micro-computed tomography'. Authors affiliated to institutions in the UK were the major contributors to the journal and were linked with other countries such as Brazil, USA and Malaysia. The largest number of publications were from the University of São Paulo, Brazil. The IEJ is one of the leading journals in Endodontology and has been providing a platform for innovative research and clinical reports for more than 50years. Publications have been associated with a wide range of authors, institutions and countries around the world.

A Probe into the Status of the Oil Palm Sector in the Malaysian Value Chain

A ban on palm oil imports by the European Union has become a problematic issue, especially for palm oil producers’ countries. Oil palm has been widely used in many sub-sectors, and any changes in the production side may affect many sectors that use oil palm as an input factor in their productions. This study explores the chain of the oil palm sector on the other sub-sectors in Malaysia by using a value-added multiplier method and network modeling. The study focuses on the specific oil palm sub-sector and oils and fats sub-sector in the Malaysian economic structure based on the Malaysian Input-Output 2015 Table. Network visualization and all the analyses involving network methods were developed and performed using UCINET and GEPHI software. The value-added multiplier results explained that the net value between output multiplier and import multiplier is vital to depict the real impact of net resources used as an input factor in the oils and fats and oil palm sub-sectors. The high-density value level shows that the Malaysian oil palm sector has high connectivity in the economic system. From the network visualization analysis, the oils and fats sub-sector has a high level of integration with other sectors within the network. Meanwhile, the oil palm sub-sector categorized in the periphery structure group has a low level of integration in the input-output network. This is due to the high value-added demand for oil palm in the oils and fats sub-sector in the manufacturing sector. Overall, most of the sub-sectors in Malaysia are highly interconnected due to the high clustering ratio. Therefore, ensuring sufficient oil palm production is vital for sustainable production of other sub-sectors.

Far beyond the four lines: the Group B fan pages at the 2018 World Cup

This paper examines how fans of the national teams of Portugal, Spain, Morocco and Iran, the so-called Group B of the 2018 FIFA World Cup, got involved with their respective official Facebook pages and how the fan pages related to stakeholders. The strategy adopted is based on a quantitative approach to the data flows produced, between 1 April 2017 and 3 May 2018, by fan pages and their users. The sample consists of 3068 posts and close to 11 million interactions on the network. Data were extracted via Facebook Graph API and treated with Gephi software. Results reveal that offline social contexts highlight the opportunities and the involvement bans, in a logic in which football goes far beyond the pitch. This research also allowed to map the relationship between fan pages and their key influencers on a global scale, focussing on the content produced.

The knowledge map of energy security

Much efforts have been made in the area of energy security in recent years, but due to its wide scope, it is necessary to review relevant knowledge activities and to analyze the state of knowledge of the field of energy security measurement. The purpose of this article is to present a comprehensive map of knowledge in the field of energy security. For this reason, many documents and articles have been collected during the period 2002–2019 using 7 large and reputable scientific databases as well as 53 different journals, 90% white Q1 quality. There is employed meta-synthesis, scientometrics and network analysis. In the initial survey stage where 1290 articles were found, after analyzing the content using meta-synthesis, 240 scientific articles related to energy security were identified. Then, the following 14 key questions were addressed such as the main conceptual models, processes, and concept structures (concept map). The VOSviewer and Gephi software are also used to explain the conceptual structure (concept map), hot map, co-occurrence map between keywords and their categorization. After Energy Security (and its subsets), the issues of Renewable Energy Security and Energy Supply Security stand in top ranks. The most cited article in this area is the 2006 “Ensuring energy security” article by Yergin on Energy Security. As many as 58 people have published at least two articles, Sovacool with fifteen articles is on the top author with the most published articles in this field. During the evaluation of the articles, 34 conceptual models and 104 quantitative and qualitative methods were found, which illustrate the wide scope of energy security. By examining the coherent vocabulary map in the field of energy security, it can be said that the most important dimensions of energy security include technology, trade, acceptability, productivity, diversity, equity, availability, governance and efficiency.

Stereotypical Representation of a Female Politician in the Language Consciousness of Twitter Users

The study focuses on issues related to gender stereotypes of the blog community based on bloggers’ individual reactions and their impact on the perception of female politicians. The sample comprises tweets of the Russian- and English-speaking segments of this microblog, selected by keywords (based on the researcher’s view on the component structure of the thematic group «women in politics» and the representativeness of the sample) and collected with the help of the Python programming language. The classification of female politicians’ characteristics significant for users is made on the basis of feminine-masculine and psychophysiological criteria (according to E. G. Bakhteeva’s classification). The distribution of characteristics attributed to a female politician allows the researcher to determine which characteristics help women to fulfil their potential in politics or, on the contrary, hinder a successful political career. The results are interpreted in two aspects. On the one hand, from the point of view of the quantitative representation (percentage of characteristic groups), the field structure of the gender stereotype is compiled. On the other hand, in terms of qualitative indicator (content of characteristic’s groups, connotative components), the correlation of characteristics is identified and their visualization is performed with the help of Gephi software. As a result, the study builds models of a female-politician’s stereotypical image in the Russian- and English-speaking segments of Twitter and carries out their their comparative analysis. According to the first type of model, personal characteristics that may be inherent in both men and women are important for Russian- and English-speaking Twitter users, while typical masculine characteristics are the least relevant. For Russian-speaking users, high moral qualities are particularly relevant, while English-speaking bloggers appreciate high professional qualities. The graphs demonstrate that the language consciousness of the blog community tends to masculinize the stereotypical image of a female politician. Thus, a contradiction arises: bloggers explicitly acclaim the equal right for both men and women to fulfill their potential in politics, they recognize and accept the fact that women can be successful in the highest political positions and establishments and approve of the activity of particular women politicians. At the same time, traditional gender stereotypes, claiming that politics is a male sphere, implicitly retain their influence.

Research Topics and Trends in Interprofessional Education in Nursing: A Text Network Analysis.

To provide nurse-led interprofessional practices in a healthcare setting, carrying out effective research that identifies the trends and characteristics of interprofessional education is necessary. This study aimed to objectively ascertain trends in the field through text network analysis of different types of interprofessional education literature. Titles and thesis abstracts were examined for terms "interprofessional education" and "nursing" and were found in 3926 articles from 1970 to August 2018. Python and Gephi software were used to analyze the data and visualize the networks. Keyword ranking was based on the frequency, degree centrality, and betweenness centrality. The terms "interprofessional," "education," "student," "nursing," and "health" were ranked the highest. According to topic analysis, the methods, provided programs, and outcome measures differed according to the research field. These findings can help create nurse-led research and effective future directions for interprofessional education pathways and topic selection. This will emphasize the importance of expanding research on various education programs and accumulating evidence regarding the professional and interdisciplinary impact these programs have on undergraduate and graduate students.

Imbalance and breakout in the post-epidemic era: Research into the spatial patterns of freight demand network in six provinces of central China.

This study aims to explore the freight demand network spatial patterns in six provinces of central China from the perspective of the spread of the epidemic and the freight imbalance and breakout. To achieve this purpose, the big data of “cart search” demand information provided by small and medium freight enterprises on the freight information platform are analyzed. 343,690 pieces of freight demand big data on the freight information platform and Python, ArcGIS, UCINET, and Gephi software are used. The results show that: (1) The choke-point of unbalanced freight demand network is Wuhan, and the secondary choke-points are Hefei and Zhengzhou. (2) In southern China, a chain reaction circle of freight imbalance is formed with Wuhan, Hefei, and Nanchang as the centers. In northern China, a chain reaction circle of freight imbalance is formed with Zhengzhou and Taiyuan as the centers. (3) The freight demand of the six provinces in central China exhibits typical characteristics of long tail distribution with large span and unbalanced distribution. (4) The import and export of freight in different cities vary greatly, and the distribution is unbalanced. This study indicates the imbalance difference, chain reaction, keys and hidden troubles posed by the freight demand network. From the perspectives of freight transfer breakout, freight balance breakout, freight strength breakout, and breakout of freight periphery cities, we propose solutions to breakouts in the freight market in six provinces of central China in the post-epidemic era.

Mapeamento da rede de comunicação dos docentes do curso de Mestrado em Ciências da Documentação e Informação da Faculdade de Letras da Universidade de Lisboa

Introdução: A pesquisa se realizou com o intuito de identificar e compreender as conexões na rede social de coautoria dos docentes, do Curso de mestrado em Ciências da Documentação e Informação, da Faculdade de Letras da Universidade de Lisboa. Buscou-se discutir os conceitos e métodos de análise que fundamentam esse estudo, a saber: rede social, coautoria, análise de rede social e análise bibliométrica. Método: O estudo caracteriza-se como exploratório, em uma abordagem qualitativa e quantitativa. Utilizou-se da plataforma Ciência Vitae para coleta dos dados e do software Gephi para modelagem e análise da rede social. Resultados: Analisaram-se e discutiram-se os dados coletados no Ciência Vitae e a rede e dados gerados no software Gephi. Validando a existência da rede e identificando a existência de dois aglomerados eminentes e uma ligação isolada. Conclusão: Os objetivos propostos foram alcançados, a investigação validou a existência da rede de informação entre os docentes do curso e pesquisadores externos, possibilitando compreender o fluxo informacional e aferir que há docentes que não possuem laços de conexão por coautoria entre si.

Analyzing existing UAE national water, energy and food nexus related strategies

Since 1971, United Arab Emirates strategies on water, food, and energy were top priority for the country and many of the conducted reports were done independently. Today and from security aspect, strategies should take into consideration the interlinkages between the current energy, water, and food strategies, and hence the nexus approach. The paper at hand will identify the historical development of these strategies and their potential relations to the nexus. In addition, the major public and private stakeholders/actors that influence the decision making process are identified. Finally, many of the recent policies that are related to the nexus are evaluated to determine if there are consensus among major stakeholders/actors in the country. Gephi software, network analysis and visualization package, was used to analyze the strength of the relationships among stakeholders/actors. KTAB, a toolkit for behavioral analysis model, is also used to analyze the level of consensus for several selected policies related to the nexus among the major stakeholders that influence the policy decision making in UAE. Results show a consensus among the major stakeholders/actors regarding the relevant policies but the linkages between the different stakeholders/actors need to be enhanced.

Coexistence of Distinct Performance Models in High-Level Women's Volleyball.

In performance analysis, and most notably in match analysis, generalizing game patterns in a sport or competition may result in formulating generic models and neglecting relevant variability in benefit of average or central values. Here, we aimed to understand how different game models can coexist at the same competitive level using social network analysis with degree centrality to obtain systemic mappings for six volleyball matches, one for each of the six national teams playing in the 2014 World Grand Prix Finals, guaranteeing a homogeneous game level and balanced matches. Although the sample was not recent, this was not relevant for our purposes, since we aimed to merely expose a proof of concept. A total of 56 sets and 7,176 ball possessions were analysed through Gephi Software, considering game actions as nodes and the interaction between them as edges. Results supported the coexistence of different performance models at the highest levels of practice, with each of the six teams presenting a very distinct game model. For example, important differences in eigenvector centrality in attack zones (ranging from 0 to 34) and tempos (20 to 38) were found between the six teams, as well as in defensive lines (20 to 39) and block opposition (22 to 37). This further suggests that there may be multiple pathways towards expert performance within any given sport, inviting a re-conceptualization of monolithic talent identification, detection and selection models. Future studies could benefit from standardizing the metrics in function of the number of ball possessions.