Matematički model izvedbe i sposobnosti u sprintu

The classical method - time and average speed for specific intervals (mostly 10m) - of describing performance has significant drawbacks: - It produces a non-continuous step-function of sprinting speed which doesn\u27t allow detailed investigation, i. e. the maximum speed can only be located in and interval but not in a certain point of course. - It is very sensitive to errors because not only differences of measurements are taken but - due to the arrangement as a chain of intervals - the random error for one interval becomes a systematic one for the next interval. It is suggested to model sprinting speed by continuous function with parameters fitted by non-linear regression. Using a system-approach to modelling two growth-processes are combined: acceleration and fatigue. Advantages of this method are: - continuous functions are easy to analyze. By differentiation/integration a complete kinematic description of sprinting behavior is available. - sensitivity to errors is reduced because of the fitting approach. - the obtained parameters allow an interpretation as basic abilities underlying the complex sprinting ability. By this was indicators of basic abilities are measured during competition and not under testing circumstances, which is remarkable theoretical aspect. Analyzng the finals in Rome 1987 demonstrates the capability of the suggested method to provide detailed information on the structure of the complex sprinting ability.Klasična metoda koja mjeri vrijeme i prosječnu brzinu u određenim intervalima (najčešće 10 m) ima znatne nedostatke kaad se radi o opisivanju sprinta: - ona daje nekontinuiranu stepenastu funkciju brzine sprinta koja ne dozvoljava detaljno proučavanju, tj. maksimalna brzina može se locirati samo u nekom intervalu, ali ne i u određenoj točki. - vrlo je osjetljiva na pogreške, jer ne dobiju se samlo razlike u mjerenju već, zbog lanca intervala, slučajna greška za jedan interval postaje sistematska greška za sljedeći interval. Predložen je model brzine sprinta pomoću kontinuirane funkcije sa parametrima koji imaju ne-linearnu regresiju. Koristeći sistematski postupak modeliranja kombinirana su dva rastuća problema; ubrzanje i zamor. Prednosti ove metode su: - kontinuirane funkcije lako se analiziraju. Pomoću diferencijacije/integracije dobije se potpuno kinematička slika ponašanja u sprintu. - osjetljivost na pogreške je smanjena - dobiveni parametri omogućuju interpretaciju da osnovne sposobnosti odgovaraju složenoj sposobnosti kod sprinta. Na ovaj način indikatori osnovnih sposobnosti mjere se u toku natjecanja, a ne u okolnostima testa što daje jedan značajan teoretski aspekt. Analiza finala u Rimu 1987 pokazuje dobre strane ove metode, a to su detaljni podaci o strukturi kompleksne sposobnosti za sprint