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Mathematical Models to Measure the Variability of Nodes and Networks in Team Sports

Fernando Martins, Ricardo Gomes, Vasco Lopes, Frutuoso Silva, Rui Mendes
2021 Entropy  
The aim of this paper is to present new mathematical concepts that are based on information and probability theory and can be applied to network analysis in Team Sports.  ...  The proposed models refer to individual and collective rates and indexes of total variability between players and teams as well as the overall passing capacity of a network, all of which are demonstrated  ...  to these, node and network entropy mathematical models [21] .  ... 
doi:10.3390/e23081072 fatcat:h4zjoy6qazfm5jn7kscacu6ex4

Node and Network Entropy—A Novel Mathematical Model for Pattern Analysis of Team Sports Behavior

Fernando Martins, Ricardo Gomes, Vasco Lopes, Frutuoso Silva, Rui Mendes
2020 Mathematics  
Taking a Bayesian approach to the study of these interactions, this work presents novel entropy mathematical models for Markov chain-based pattern analysis in team sports networks, with Relative Transition  ...  Pattern analysis is a well-established topic in team sports performance analysis, and is usually centered on the analysis of passing sequences.  ...  The aim of this paper is to present several novel mathematical models for pattern analysis in team sports, particularly football, to analyze the level of entropy in passing networks using a Markov chain  ... 
doi:10.3390/math8091543 fatcat:ceiym7goenhqncgrbbkmeinpr4

Machine Learning for sport results prediction using algorithms

Said Lotfi, Mohamed Rebbouj
2021 International Journal of Information Technology and Applied Sciences (IJITAS)  
The purpose of this paper is to benchmark existing analysis methods used in literature, to understand the prediction processes used to model Data collection and its analysis; and determine the characteristics  ...  Given the recent trend in Data science and sport analytics, the use of Machine Learning and Data Mining as techniques in sport reveals the essential contribution of technology in results and performance  ...  Neural network Tab.2: algorithm measurement methods, variables features and results according to sport studies.  ... 
doi:10.52502/ijitas.v3i3.114 fatcat:wwhke5is5fawncy2ajqsgf7kt4

Complex Networks Models and Spectral Decomposition in the Analysis of Swimming Athletes' Performance at Olympic Games

Vanessa Helena Pereira-Ferrero, Theodore Gyle Lewis, Luciane Graziele Pereira Ferrero, Leonardo Tomazeli Duarte
2019 Frontiers in Physiology  
In addition, this is a general method and may, in the future, be developed in the analysis of other competitive sports.  ...  variables relate to competition results and are reflected in the SR for the best performance.  ...  In this way, 6 variables were selected and transformed into nodes of the complex models.  ... 
doi:10.3389/fphys.2019.01134 pmid:31551810 pmcid:PMC6733958 fatcat:e75wudsbbjaflazhjbf7ku4rmq

Team Sports Performance Analysed Through the Lens of Social Network Theory: Implications for Research and Practice

João Ribeiro, Pedro Silva, Ricardo Duarte, Keith Davids, Júlio Garganta
2017 Sports Medicine  
emergent properties of interactions between players in sports teams. 18 Key Points 19  The network approach highlights interactional processes established by team players within-and 20 between-teams  ...  word count: 241 Abstract This paper discusses how social network analyses and graph theory can be implemented in team 1 sports performance analyses to evaluate individual (micro) and collective (macro)  ...  The fraction P(k) of nodes in the network 22 has connections to other nodes with large values of k as P(k) ̴ − [50] .  ... 
doi:10.1007/s40279-017-0695-1 pmid:28197801 fatcat:aegnozux7vexbii5u67nmmn2ai

A Networks and Machine Learning Approach to Determine the Best College Coaches of the 20th-21st Centuries [article]

Tian-Shun Jiang, Zachary Polizzi, Christopher Yuan
2014 arXiv   pre-print
We created a networks-based model to calculate team skill from historical game data. A digraph was created for each year in each sport.  ...  We multiplied the probabilities of all edges in the network together to find the probability that the correct network would occur with any given player skill and coach skill matrix.  ...  Create a network-based model to visualize all college sports teams, the teams won/lost against, and the margin of win/loss. Each network describes the games of one sport over a single year. 2.  ... 
arXiv:1404.2885v1 fatcat:lm2xuunh2vabvddulpse3lqgla

Computational and Complex Network Modeling for Analysis of Sprinter Athletes' Performance in Track Field Tests

Vanessa H. Pereira, Claudio A. Gobatto, Theodore G. Lewis, Luiz F. P. Ribeiro, Wladimir R. Beck, Ivan G. M. dos Reis, Filipe A. B. Sousa, Fúlvia B. Manchado-Gobatto
2018 Frontiers in Physiology  
However, the literature lacks studies regarding sports performance, running, exercise, and more specifically, sprinter athletes analyzed mathematically through complex network modeling.  ...  Moreover, our type of analysis can inspire the study and analysis of other complex sport scenarios.  ...  A complex network is a mathematical representation of measurable variables as nodes and its interactions as links (a graph) (Lewis, 2009 ).  ... 
doi:10.3389/fphys.2018.00843 pmid:30034346 pmcid:PMC6043640 fatcat:kzukaydhgzhbfah5dlq7swwify

A Comparative Study of Neural Networks and ANFIS for Forecasting Attendance Rate of Soccer Games

Mehmet Şahin, Rızvan Erol
2017 Mathematical and Computational Applications  
Neural network studies in sports are used for predicting a game's winner or the winning rate of a team, sports results, and success for different sports disciplines.  ...  This is the first attempt to use an ANFIS model for that purpose. Math. Comput. Appl. 2017, 22, 43 2 of 12 variables.  ...  team is measured as the ratio of points that the away team has earned to possible total points to the game day.  ... 
doi:10.3390/mca22040043 fatcat:g7aapsovyvdxhizj46vocayd74

A machine learning framework for sport result prediction

Rory P. Bunker, Fadi Thabtah
2017 Applied Computing and Informatics  
This paper provides a critical analysis of the literature in ML, focusing on the application of Artificial Neural Network (ANN) to sport results prediction.  ...  In doing so, we identify the learning methodologies utilised, data sources, appropriate means of model evaluation, and specific challenges of predicting sport results.  ...  and how we propose that model performance should be measured for the problem of sport results prediction.  ... 
doi:10.1016/j.aci.2017.09.005 fatcat:67cmbnpp2jej7cj65dfcyj7cwm

Exploring Team Passing Networks and Player Movement Dynamics in Youth Association Football

Bruno Gonçalves, Diogo Coutinho, Sara Santos, Carlos Lago-Penas, Sergio Jiménez, Jaime Sampaio, Satoru Hayasaka
2017 PLoS ONE  
The present study aims to explore how passing networks and positioning variables can be linked to the match outcome in youth elite association football.  ...  Overall, this study emphasizes the potential of coupling notational analyses with spatial-temporal relations to produce a more functional and holistic understanding of teams' sports performance.  ...  Acknowledgments This work was supported by the Portuguese Foundation for Science and Technology (FCT) and European Social Fund (ESF), through a Doctoral grant endorsed to the first author  ... 
doi:10.1371/journal.pone.0171156 pmid:28141823 pmcid:PMC5283742 fatcat:3rxld5wchfatzofixnh6nma3xq

Evaluating the effectiveness of different network flow motifs in association football

Else Marie Håland, Astrid Salte Wiig, Lars Magnus Hvattum, Magnus Stålhane
2020 Journal of Quantitative Analysis in Sports (JQAS)  
The analysis is performed with a generalized additive model (GAM), with a range of explanatory variables included.  ...  This information has previously been used to classify the passing style of different teams. In this work, flow motifs are analyzed in terms of their effectiveness in terms of generating shots.  ...  Football coach Hugo Pereira is thanked for his input and feedback during the research. Jørgen Skålnes is thanked for his assistance in executing additional calculations during revisions of the work.  ... 
doi:10.1515/jqas-2019-0097 fatcat:mpcmwt42ozdmjlabu3obsutj5u

The Development of Talent in Sports: A Dynamic Network Approach

Ruud J. R. Den Hartigh, Yannick Hill, Paul L. C. Van Geert
2018 Complexity  
The dynamic network model offers a new avenue toward understanding talent development in sports and other achievement domains.  ...  Understanding the development of talent has been a major challenge across the arts, education, and particularly sports.  ...  Acknowledgments Publication of this article was funded by the Heymans Institute for Psychological Research, University of Groningen, and a research grant awarded to Yannick Hill by the Sparkasse Bank.  ... 
doi:10.1155/2018/9280154 fatcat:lgtjk6mry5hpxnahsi7rsac5qy

Identifying Opinion Leaders on Twitter during Sporting Events: Lessons from a Case Study

José M. Lamirán-Palomares, Tomás Baviera, Amparo Baviera-Puig
2019 Social Sciences  
Mathematical variables of the social network analysis and variables provided by Twitter and Google are compared.  ...  Social media platforms have had a significant impact on the public image of sports in recent years.  ...  In this way, we relate mathematical variables of the SNA and variables offered by Twitter and Google with the dimensions of influence in a global conversation on Twitter during a sporting event.  ... 
doi:10.3390/socsci8050141 fatcat:exk3f4o6h5hgfaswrwrgn4flkq

Notational analysis – a mathematical perspective

Mike Hughes
2004 International Journal of Performance Analysis in Sport  
These are areas that will continue to develop to the good of the discipline and the confidence of the sports scientist, coach and athlete.  ...  If we consider the role of a performance analyst in its general sense in relation the to the data that the analyst is collecting, processing and analysing, then there a number of mathematical skills that  ...  or other team members or due to noise in measurements or the motor control apparatus.  ... 
doi:10.1080/24748668.2004.11868308 fatcat:6nc5jwbaknfojdblsaa53x4lcm

A Dockerized big data architecture for sports analytics

Yavuz Özgüven, Utku Gönener, Süleyman Eken
2022 Computer Science and Information Systems  
When we rely on central processing systems to aggregate and analyze large amounts of sport data from many sources, we compromise the accuracy and timeliness of the data.  ...  The big data revolution has had an impact on sports analytics as well. Many large corporations have begun to see the financial benefits of integrating sports analytics with big data.  ...  The conclusions need to be originated from established data analytics, according to mathematical models that the sports industry has evaluated and are used in some manner.  ... 
doi:10.2298/csis220118010o fatcat:vzdylnrvjnbbri2dhefugsvks4
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