Handball game-related statistics in men at Olympic Games (2004-2016): Differences and discriminatory power (Estadísticas de juego en balonmano masculino en los Juegos Olímpicos (2004-2016): Diferencias y poder discriminatorio)

Autores/as

  • Jose M Saavedra Physical Activity, Physical Education, Sport and Health Research Centre, Sports Science Department, School of Science and Engineering, Reykjavik University, Reykjavik, Iceland
  • Sveinn Þorgeirsson Physical Activity, Physical Education, Sport and Health Research Centre, Sports Science Department, School of Science and Engineering, Reykjavik University, Reykjavik, Iceland
  • Hafrún Kristjánsdóttir Physical Activity, Physical Education, Sport and Health Research Centre, Sports Science Department, School of Science and Engineering, Reykjavik University, Reykjavik, Iceland
  • Milan Chang Physical Activity, Physical Education, Sport and Health Research Centre, Sports Science Department, School of Science and Engineering, Reykjavik, Iceland. The Icelandic Gerontological Research Center, Reykjavik, Iceland
  • Kristján Halldórsson Physical Activity, Physical Education, Sport and Health Research Centre, Sports Science Department, School of Science and Engineering, Reykjavik, Iceland

DOI:

https://doi.org/10.47197/retos.v0i32.56542

Palabras clave:

notational analysis, performance, match, shot, goalkeeper (análisis notacional, rendimiento, partido, lanzamiento, portero)

Resumen

Handball can be considered a complex game. Sports performance analysis is a relevant topic for scientists and coaches. The objectives of the present study were: (i) to compare handball game-related statistics by match outcome (winning and losing teams) and (ii) to identify characteristics that discriminate the performance in elite men´s handball. The game-related statistics of the 324 games played in the last four Olympic Games (Athens, Greece, 2004; Beijing, China, 2008; London, United Kingdom, 2012; and Rio de Janeiro, Brazil, 2016) were analyzed. Differences between match outcomes (winning or losing teams) were determined by using the chi-squared statistic, and by calculating the effect sizes of the differences. A discriminant analysis was then performed applying the sample-splitting method according to match outcomes. The results showed that the differences between winning and losing teams were shots, 9 m shots, assists, goalkeeper-blocked shots fast break. Also, discriminant analysis selected four variables (shots, goalkeeper-blocked shots, technical foul, and attacks) that classified correctly 82% of matches (Wilks's lambda=0.575; canonical correlation index 0.652). The selected variables included offensive and defensive predictors: Shots, goalkeeper-blocked shots, technical foul, attacks. Coaches and players can use these results as a reference against which to assess their performance and plan their team’s training.


Resumen. El balonmano puede considerarse un juego complejo. El análisis del rendimiento deportivo es un tópico relevante para los científicos y entrenadores. Los objetivos del presente estudio fueron: (i) comparar las estadísticas de juego en balonmano en función del contexto (equipos ganadores y perdedores) e (ii) identificar las estadísticas que discriminan el rendimiento en el balonmano masculino de élite. Se analizaron las estadísticas de juego de los 324 partidos disputados en los últimos cuatro Juegos Olímpicos (Atenas, Grecia, 2004, Beijing, China, 2008, Londres, Reino Unido, 2012 y Río de Janeiro, Brasil, 2016). Las diferencias entre los equipos ganadores y perdedores) se determinaron usando el estadístico chi-cuadrado y calculando los tamaños del efecto de las diferencias. A continuación, se realizó un análisis discriminante aplicando el método de por pasos. Los resultados mostraron que las diferencias entre los equipos vencedores y perdedores se presentaron en las variables lanzamientos de 9 m, asistencias, lanzamientos bloqueados por el portero en situación de contrataque. Además, el análisis discriminante seleccionó cuatro variables (lanzamientos, lanzamientos bloqueados por el portero, falta técnica y número de ataques) que clasificaron correctamente el 82% de los partidos (Lambda de Wilks=0,575; índice de correlación canónica=0,652). Las variables seleccionadas incluyeron predictores ofensivos y defensivos: lanzamientos, paradas del portero, faltas técnicas y ataques. Los entrenadores y los jugadores pueden utilizar estos resultados como referencia para evaluar su rendimiento y planificar el entrenamiento del equipo.

 

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Publicado

2017-07-01

Cómo citar

Saavedra, J. M., Þorgeirsson, S., Kristjánsdóttir, H., Chang, M., & Halldórsson, K. (2017). Handball game-related statistics in men at Olympic Games (2004-2016): Differences and discriminatory power (Estadísticas de juego en balonmano masculino en los Juegos Olímpicos (2004-2016): Diferencias y poder discriminatorio). Retos, 32, 260–263. https://doi.org/10.47197/retos.v0i32.56542

Número

Sección

Monográfico: Análisis de Rendimiento Deportivo. Coordinación: José Antonio Pérez Turpin