Relationship between game-related statistics in elite men`s beach handball and the final result: a classification tree approach
(Beziehung zwischen spielbezogenen Statistiken im Beachhandball im männlichen Spitzenbereich und dem Endergebnis: ein Klassifikationsbaum-Ansatz)
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.
© Copyright 2019 International Journal of Performance Analysis in Sport. Taylor & Francis. Alle Rechte vorbehalten.
Schlagworte: | Handball Wettkampf international Statistik Belag Spielposition |
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Notationen: | Spielsportarten |
Tagging: | beach handball Torwart |
DOI: | 10.1080/24748668.2019.1642040 |
Veröffentlicht in: | International Journal of Performance Analysis in Sport |
Veröffentlicht: |
2019
|
Jahrgang: | 19 |
Heft: | 4 |
Seiten: | 584-594 |
Dokumentenarten: | Artikel |
Sprache: | Englisch |
Level: | hoch |