Dynamic Network DEA approach to basketball games efficiency

Villa, Gabriel; Lozano, Sebastián

doi:10.1080/01605682.2017.1409158

Cited by 19 publications

(15 citation statements)

References 36 publications

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“…the problems with using factor analysis methods to reveal the consistent patterns of team, group, and individual dynamics of the competitive activity effectiveness in basketball were described in the studies by Bazanov et al [13], Kozina et al [14], Villa and Lozano [15]. An analysis of factor variables that determine the parameters of teamwork of qualified basketball players in conditions of increasing competitive activity is presented in a study by Gruber and Gray [16].…”

Section: Introductionmentioning

confidence: 99%

The competitive activity structure of highly skilled basketball players on the basis of factor analysis methods

Doroshenko¹,

Sushko²,

Koryahin³

et al. 2019

Hum Mov.

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Purpose. to analyse and generalize the competitive activity structure on the basis of the hierarchy of technical and tactical indicators of qualified basketball players in won and lost games by using the factor analysis methods. Methods. the study involved 96 professional basketball players who were national team players of countries that took 1-8 places in the final tournament of the European Basketball Championship 2017. technical and tactical indicators of their competitive activity were analysed for revealing and interpreting the results with the factor analysis methods. Results. the grouping of elements of the competitive activity structure of highly skilled basketball players was analysed. Groups with the highest value of factor capacity depending on the results of the game were determined. A significant difference in the structure of technical and tactical activity in the won and lost games was presented. Conclusions. the data obtained in the course of the study on the basis of factor analysis allowed us to present updated information on the competitive activity structure of highly skilled basketball players and to partially confirm the existing data.

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Section: Introductionmentioning

confidence: 99%

The competitive activity structure of highly skilled basketball players on the basis of factor analysis methods

Doroshenko¹,

Sushko²,

Koryahin³

et al. 2019

Hum Mov.

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“…The two main kinds of efficiency measurement approaches that have been applied to sports in the literature are econometric or parametric approaches, such as stochastic frontier analysis (SFA), and nonparametric approaches, such as DEA (Barros et al., 2011). By applying these approaches, researchers have conducted many studies on efficiency measurement in sports such as the Olympics (e.g., Li et al., 2015, 2020), the National Football League (e.g., Hadley et al., 2000; Collier et al., 2011; Santín, 2014; Villa and Lozano, 2016), Major League Baseball (e.g., Lewis et al., 2009), English Premier League soccer (e.g., Barros and Leach, 2006a, 2006b, 2007), and the NBA (e.g., Zak et al., 1979; Hoefler and Payne, 1997, 2006; Moreno and Lozano, 2014; Chen et al., 2017; Villa and Lozano, 2018; Zhu et al., 2019; Yang et al., 2020). Bhat et al.…”

Section: Literature Reviewmentioning

confidence: 99%

Identifying standards for postseason advancement: a case of the National Basketball Association

Chen

Liao

2020

Int Trans Operational Res

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This paper identifies a standard for postseason advancement and predicts whether a team will advance when criteria are known but requirements are undetermined. A frontier function for advancing teams is constructed based on their past statistics of influential performance factors. The difference between a team's performance and the frontier function indicates whether a team will advance. The importance of each performance factor and team efficiency (TE) after a certain number of regular‐season games is identified. The ratio of a team's actual winning percentage to its highest winning percentage indicates the in‐season TE. Data from advancing teams in the National Basketball Association (NBA) over 11 years are collected. The difference between the Eastern Conference and the Western Conference and the changes in NBA playing styles are analyzed. The results predict whether stakeholders’ teams will advance and provide managers and coaches a metric to measure the optimal performance and direction of improvement.

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“…The use of the methods of multivariate mathematical analysis of technical and tactical indicators in the competitive activity of skilled basketball players is also highlighted in the study by Scanlan, Dascombe, and Reaburn (2011), which, on the basis of comparative analysis of elementary technical and tactical actions of basketball players of the Australian National Basketball League, shows the need to study the hidden structure of standard indicators of game efficiency in basketball, which significantly supplements the modern approaches to special analysis of indicators of the competitive activity and the formation of its algorithm. The discriminant analysis of game indicators of basketball players with different positions is shown as an adequate, reliable, and informative method for studying technical and tactical indicators and is a necessary prerequisite for developing an algorithm for special analysis of the competitive activity in basketball (Villa & Lozano, 2018).…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Competitive Activity Structure of Skilled Female Basketball Players

Doroshenko

Sushko

Shamardin³

et al. 2020

Teor. metod. fiz. vihov.

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The study purpose was to examine, analyze, and generalize the competitive activity structure based on the hierarchy of technical and tactical indicators of skilled female basketball players in won and lost games using principal component analysis. Materials and methods. The study participants were 96 professional female basketball players, members of national teams of Spain, France, Belgium, Greece, Turkey, Latvia, Italy, and Slovakia, which took the 1st-8th places in the final tournament of the European Basketball Championship 2017. The study analyzed 16 main technical and tactical indicators of skilled female basketball players in 52 official games to examine and interpret the obtained results using principal component analysis. The total number of observations is 52. Results. The experimental indicators obtained during the study made it possible to examine and analyze the grouping of elements of the competitive activity structure of skilled female basketball players, to interpret the obtained results in order to define informative criteria for optimizing training and improving the competitive activity effectiveness. The study revealed considerable differences in the competitive activity structure in won and lost games: in accordance with the most significant indicators of factor loadings, the percentage of a sample of elements that correlate with one another is: for won games – 67.40%, for lost games – 69.52%. Conclusions. Principal component analysis is quite effective and informative for studying the competitive activity structure of skilled female basketball players. It was demonstrated that the greatest difficulties in studying the competitive activity structure in basketball using principal component analysis are the selection of indicators that do not duplicate one another and are not calculated, expert interpretation of the obtained results, and algorithmization of special analysis of technical and tactical indicators.

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Dynamic Network DEA approach to basketball games efficiency

Cited by 19 publications

References 36 publications

The competitive activity structure of highly skilled basketball players on the basis of factor analysis methods

The competitive activity structure of highly skilled basketball players on the basis of factor analysis methods

Identifying standards for postseason advancement: a case of the National Basketball Association

Analysis of the Competitive Activity Structure of Skilled Female Basketball Players

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