Anthropometric profile and indicators of playing performance in Brazilian women´s olympic basketball teams

• Main Authors: João Antonio Nunes (Author), Marcelo Saldanha Aoki (Author), Leandro Ricardo Altimari (Author), Edio Luiz Petroski (Author), Dante De Rose Júnior (Author), Paulo Cesar Montagner (Author)
• Format: Book
• Published: Universidade Federal de Santa Catarina, 2009-01-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 1415-8426; 1980-0037; 10.5007/1980-0037.2009v11n1p67
• Keywords: Sports; GV557-1198.995; Medicine (General); R5-920
• Source: Revista Brasileira de Cineantropometria e Desempenho Humano, Vol 11, Iss 1, Pp 67-72 (2009)

The aim of the present study was to investigate the correlation between anthropometric parameters (weight, height, body fat, BMI) and performance indicators (playing time, points, rebounds, errors, steals) in female national basketball players. The study was conducted during the 2000 and 2004 Olympic Games. Data were analyzed by ANOVA with random effects. Pearson's simple correlation coefficients were also determined. No difference in anthropometric profile or performance indicators was observed between the two national teams (2000 and 2004). There was a significant correlation (r = 0.61, p<0.05) between height and number of rebounds. Free fat mass was also correlated with the number of rebounds performed (r = 0.45, p<0.05). BMI showed moderate correlations with playing time (r = -0.51, p<0.05), points scored (r = -0.50, p<0.05), number of errors (r = 0.53, p<0.05), and number of steals (r = -0.43, p<0.05). A similar pattern of correlation was observed between relative fat mass (%) and performance indicators (playing time: -0.51, points scored: -0.44, errors: 0.50, and steals: 0.51) (p<0.05). The present results indicate a relationship between anthropometric profile and performance indicators. The results also suggest that height and free fat mass influence rebound performance. In addition, it is reasonable to assume that body fat interferes with most of the performance indicators analyzed.