Performance prediction models based on anthropometric, genetic and psychological traits of Croatian sprinters

• Main Authors: Luciana Zaccagni (Author), Barbara Lunghi (Author), Davide Barbieri (Author), Natascia Rinaldo (Author), Sasa Missoni (Author), Tena Šaric (Author), Jelena Šarac (Author), Vesna Babic (Author), Marija Rakovac (Author), Francesco Bernardi (Author), Emanuela Gualdi-Russo (Author)
• Format: Book
• Published: Termedia Publishing House, 2018-10-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 0860-021X; 2083-1862; 10.5114/biolsport.2018.78901
• Keywords: sprint performance; personal best; anthropometry; genetic polymorphisms; competitive anxiety; Sports medicine; RC1200-1245; Biology (General); QH301-705.5
• Source: Biology of Sport, Vol 36, Iss 1, Pp 17-23 (2018)

Elite athletes differ from each other in their characteristics according to their discipline. This study aimed to identify performance predictors in elite Croatian sprinters taking into consideration their anthropometric, psychological and genetic characteristics. One hundred and four elite Croatian sprinters (68 males and 36 females) participated in this study. Of them, 38 are currently competing in the 100-metre dash. The others are former sprinters. The participants underwent direct anthropometric assessment. Participants were also tested by means of the Competitive State Anxiety Inventory-2 and for ACE and ACTN3 polymorphisms. Multiple linear regression analysis was applied to identify the best model for performance prediction. Different models were developed for males and females. Anthropometric traits accounted for 44% of the variance in performance for males, 62% for females. Once other traits (psychological for females) were entered into the model, no additional contribution to the variance was observed. The most significant predictors of higher running velocity were bicristal diameter and foot dimensions in males, and leg length and clean one-repetition maximum in females. The findings suggest that performance in sprinters is associated with anthropometric characteristics, with biomechanical implications that may be used to provide a more complete evaluation of sprinters' performance.