Relationship between game-related statistics in elite men´s beach handball and the final results: A classification tree approach

10.8.2019

Recently, Jose M. Saavedra, Hafrún Kristjánsdóttir and their colleagues have been published an interesting paper in the International Journal of Performance Analysis in Sport. This journal has an Impact factor of 1.325 and it is ranked in 64th place out of 83 journals (Sport Sciences) Science Edition-2018, Journal Citation Reports. This study's objectives were to (i) to compare beach handball game-related statistics by match outcome (winning and losing teams) and (ii) to develop a multivariate model explaining the performance in elite men's beach handball. Seventy-two matches of the VIII Men's Beach Handball World Championship held in Kazan (Russia) in 2018 were analysed. The dependent variable was match outcome (winning and losing teams), and the independent variables were the game-related statistics. A paired sample t-test was used to examine differences between teams. The effect sizes of the differences were calculated. The data were subjected to a multivariate analysis in the form of a regression and classification tree. The game statistics with the greatest effect size (ES≥0.88) and which differentiated the winning and losing teams were the team's overall valuation and total points. The classification and regression tree model correctly classified 94.5% of the records on the basis of eight variables distributed over 20 nodes: overall valuation, goalkeeper blocked spin-shots, goalkeeper received spin-shots, goalkeeper received one-pointer, spin-shot goals, specialist goals, blocks, technical fouls. Coaches could apply these results to seek better performance in the goalkeeper position and in two-pointer goals.

More information: https://www.tandfonline.com/doi/full/10.1080/24748668.2019.1642040

Relationship between game-related statistics in elite men´s beach handball and the final results: A classification tree approach

10.8.2019

Recently, Jose M. Saavedra, Hafrún Kristjánsdóttir and their colleagues have been published an interesting paper in the International Journal of Performance Analysis in Sport. This journal has an Impact factor of 1.325 and it is ranked in 64th place out of 83 journals (Sport Sciences) Science Edition-2018, Journal Citation Reports. This study's objectives were to (i) to compare beach handball game-related statistics by match outcome (winning and losing teams) and (ii) to develop a multivariate model explaining the performance in elite men's beach handball. Seventy-two matches of the VIII Men's Beach Handball World Championship held in Kazan (Russia) in 2018 were analysed. The dependent variable was match outcome (winning and losing teams), and the independent variables were the game-related statistics. A paired sample t-test was used to examine differences between teams. The effect sizes of the differences were calculated. The data were subjected to a multivariate analysis in the form of a regression and classification tree. The game statistics with the greatest effect size (ES≥0.88) and which differentiated the winning and losing teams were the team's overall valuation and total points. The classification and regression tree model correctly classified 94.5% of the records on the basis of eight variables distributed over 20 nodes: overall valuation, goalkeeper blocked spin-shots, goalkeeper received spin-shots, goalkeeper received one-pointer, spin-shot goals, specialist goals, blocks, technical fouls. Coaches could apply these results to seek better performance in the goalkeeper position and in two-pointer goals.

More information: https://www.tandfonline.com/doi/full/10.1080/24748668.2019.1642040

Relationship between game-related statistics in elite men´s beach handball and the final results: A classification tree approach

10.8.2019

Recently, Jose M. Saavedra, Hafrún Kristjánsdóttir and their colleagues have been published an interesting paper in the International Journal of Performance Analysis in Sport. This journal has an Impact factor of 1.325 and it is ranked in 64th place out of 83 journals (Sport Sciences) Science Edition-2018, Journal Citation Reports. This study's objectives were to (i) to compare beach handball game-related statistics by match outcome (winning and losing teams) and (ii) to develop a multivariate model explaining the performance in elite men's beach handball. Seventy-two matches of the VIII Men's Beach Handball World Championship held in Kazan (Russia) in 2018 were analysed. The dependent variable was match outcome (winning and losing teams), and the independent variables were the game-related statistics. A paired sample t-test was used to examine differences between teams. The effect sizes of the differences were calculated. The data were subjected to a multivariate analysis in the form of a regression and classification tree. The game statistics with the greatest effect size (ES≥0.88) and which differentiated the winning and losing teams were the team's overall valuation and total points. The classification and regression tree model correctly classified 94.5% of the records on the basis of eight variables distributed over 20 nodes: overall valuation, goalkeeper blocked spin-shots, goalkeeper received spin-shots, goalkeeper received one-pointer, spin-shot goals, specialist goals, blocks, technical fouls. Coaches could apply these results to seek better performance in the goalkeeper position and in two-pointer goals.

More information: https://www.tandfonline.com/doi/full/10.1080/24748668.2019.1642040

Relationship between game-related statistics in elite men´s beach handball and the final results: A classification tree approach

10.8.2019

Recently, Jose M. Saavedra, Hafrún Kristjánsdóttir and their colleagues have been published an interesting paper in the International Journal of Performance Analysis in Sport. This journal has an Impact factor of 1.325 and it is ranked in 64th place out of 83 journals (Sport Sciences) Science Edition-2018, Journal Citation Reports. This study's objectives were to (i) to compare beach handball game-related statistics by match outcome (winning and losing teams) and (ii) to develop a multivariate model explaining the performance in elite men's beach handball. Seventy-two matches of the VIII Men's Beach Handball World Championship held in Kazan (Russia) in 2018 were analysed. The dependent variable was match outcome (winning and losing teams), and the independent variables were the game-related statistics. A paired sample t-test was used to examine differences between teams. The effect sizes of the differences were calculated. The data were subjected to a multivariate analysis in the form of a regression and classification tree. The game statistics with the greatest effect size (ES≥0.88) and which differentiated the winning and losing teams were the team's overall valuation and total points. The classification and regression tree model correctly classified 94.5% of the records on the basis of eight variables distributed over 20 nodes: overall valuation, goalkeeper blocked spin-shots, goalkeeper received spin-shots, goalkeeper received one-pointer, spin-shot goals, specialist goals, blocks, technical fouls. Coaches could apply these results to seek better performance in the goalkeeper position and in two-pointer goals.

More information: https://www.tandfonline.com/doi/full/10.1080/24748668.2019.1642040