Izvorni znanstveni članak
Non Linear Anthropometric Predictors in Swimming
Nada Grčić Zubčević
APA 6th Edition
Sekulić, D., Zenić, N. i Grčić Zubčević, N. (2007). Non Linear Anthropometric Predictors in Swimming. Collegium antropologicum, 31 (3), 803-809. Preuzeto s https://hrcak.srce.hr/26895
MLA 8th Edition
Sekulić, Damir, et al. "Non Linear Anthropometric Predictors in Swimming." Collegium antropologicum, vol. 31, br. 3, 2007, str. 803-809. https://hrcak.srce.hr/26895. Citirano 06.02.2023.
Chicago 17th Edition
Sekulić, Damir, Nataša Zenić i Nada Grčić Zubčević. "Non Linear Anthropometric Predictors in Swimming." Collegium antropologicum 31, br. 3 (2007): 803-809. https://hrcak.srce.hr/26895
Sekulić, D., Zenić, N., i Grčić Zubčević, N. (2007). 'Non Linear Anthropometric Predictors in Swimming', Collegium antropologicum, 31(3), str. 803-809. Preuzeto s: https://hrcak.srce.hr/26895 (Datum pristupa: 06.02.2023.)
Sekulić D, Zenić N, Grčić Zubčević N. Non Linear Anthropometric Predictors in Swimming. Collegium antropologicum [Internet]. 2007 [pristupljeno 06.02.2023.];31(3):803-809. Dostupno na: https://hrcak.srce.hr/26895
D. Sekulić, N. Zenić i N. Grčić Zubčević, "Non Linear Anthropometric Predictors in Swimming", Collegium antropologicum, vol.31, br. 3, str. 803-809, 2007. [Online]. Dostupno na: https://hrcak.srce.hr/26895. [Citirano: 06.02.2023.]
In this paper we have tried to identify the significance and character of the linear and non-linear relations between
simple anthropometric predictors: body height (BH), body weight (BW), and body mass index, and swimming performance:
freestyle swimming 50 (FS50) and 400 meters (FS400), in a sample of young (15 years old on average) male
(N=40) and female (N=28) swimmers. Linear (general model: y=a+bx) and nonlinear regression (general model: y=
a+bx+cx2) were calculated simultaneously. Morphological variables are a significantly better predictor of the FS50 in
males (BH mostly), and FS400 in females (BW mostly). This study emphasized some of the main advantages in the nonlinear
regression calculation (including an interpretation of the relationships at a more superior level), and consequently
allowed a precise anthropometric modeling in swimming using simple and easily measurable variables. For example,
the best results in FS400 can be expected for the subjects that are average in BW (which guarantees solid muscle mass –
the generator of force), but above average in BH (because of the physical law of lever). In conclusion, nonlinear regressions
allow one to define the real nature of the relationships between variables, but only if compared with the linear ones.
Additionally, this study emphasized one of the most important factors in defining possible specification-equation (e.g.
structure of the influence of the different dimensions on the sport achievement) in different sports. In short, it underlines
the importance of sampling the appropriate sample of the subject – highly skilled athletes exclusively.
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