Aplicação de técnicas de análise multivariada para análise das jogadoras ponteiras da Superliga Brasileira de Voleibol Feminino na temporada 2022/2023
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Data
2023-12-04
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Universidade Estadual Paulista (Unesp)
Resumo
O objetivo do estudo foi analisar as jogadoras ponteiras dos 12 times da Superliga Brasileira de Voleibol Feminino na temporada 2022/2023, a partir de métodos de Análise Multivariada, a fim de determinar a melhor ponteira da temporada. Os dados foram obtidos através da CBV, que disponibilizou as súmulas de jogo e a descrição lance a lance, além de tabelas de desempenho dos times durante o jogo. Foram coletadas as variáveis Nome, Time, Nacionalidade, Ano de nascimento, Número de ataques (totais, certos e errados), Número de saques (totais, aces e errados), Número de bloqueios, Pontos totais no jogo, Número de jogos (vencidos e perdidos) e Número de sets jogados (vencidos e perdidos). Foram abordadas técnicas de Análise de Componentes Principais e Análise de Agrupamentos. Foram feitos cálculos de distância euclidiana utilizando métodos de similaridade e dissimilaridade e gráficos através de métodos hierárquicos. Ao longo do trabalho, foram analisados o 1º e 2º turno do campeonato, incluindo todas as 64 jogadoras na posição de ponteira para obtenção de grupos e definição do método de agrupamento mais adequado e das jogadoras com melhor rendimento.
The objective of the study was to analyze the striker players of the 12 teams of the Brazilian Women's Volleyball Superliga in the 2022/2023 season, using Multivariate Analysis methods, in order to determine the best striker of the season. The data was obtained through CBV, which made the game summary and play-by-play description available, as well as team performance tables during the game. The variables Name, Team, Nationality, Year of birth, Number of attacks (total, right and wrong), Number of serves (total, aces and wrong), Number of blocks, Total points in the game, Number of games (won) were collected. and lost) and Number of sets played (won and lost). Principal Component Analysis and Cluster Analysis techniques were covered. Euclidean distance calculations were made using similarity and dissimilarity methods and graphs using hierarchical methods. Throughout the work, the 1st and 2nd round of the championship were analyzed, including all 64 players in the winger position to obtain groups and define the most appropriate grouping method and the players with the best performance.
The objective of the study was to analyze the striker players of the 12 teams of the Brazilian Women's Volleyball Superliga in the 2022/2023 season, using Multivariate Analysis methods, in order to determine the best striker of the season. The data was obtained through CBV, which made the game summary and play-by-play description available, as well as team performance tables during the game. The variables Name, Team, Nationality, Year of birth, Number of attacks (total, right and wrong), Number of serves (total, aces and wrong), Number of blocks, Total points in the game, Number of games (won) were collected. and lost) and Number of sets played (won and lost). Principal Component Analysis and Cluster Analysis techniques were covered. Euclidean distance calculations were made using similarity and dissimilarity methods and graphs using hierarchical methods. Throughout the work, the 1st and 2nd round of the championship were analyzed, including all 64 players in the winger position to obtain groups and define the most appropriate grouping method and the players with the best performance.
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Palavras-chave
Voleibol, Superliga, Análise multivariada, Análise de componentes principais, Análise de agrupamento, Volleyball, Superliga, Multivariate analysis, Principal component analysis, Cluster analysis
Como citar
SANTOS, Isadora de Paula e Silva dos. Aplicação de técnicas de análise multivariada para análise das jogadoras ponteiras da Superliga Brasileira de Voleibol Feminino na temporada 2022/2023. Miriam Rodrigues Silvestre. 2023. 59 f. Trabalho de Conclusão de Curso (Bacharelado em Estatística) - Faculdade de Ciências e Tecnologia, Universidade Estadual Paulista, Presidente Prudente, 2023.