title: Performance modeling in an Olympic 1500-m finalist: a practical approach.
abstract: The purpose of this study was to test if a simplified impulse-response (IR) model would correlate with competition performances in an elite middle-distance runner over a period of 7 years that encompassed two Olympiads. Daily recorded pace and time obtained from training logs of this individual for the years 2000 to 2006 were used to calculate the impulse (training stress score, or TSS). The daily TSS was used to generate acute and chronic training loads (ATL and CTL, respectively), and a model response output, or p(t), was calculated based on the relationship p(t) = CTL - ATL. Competition performances (800 m-1 mile) were converted to Mercier scores (MS) and compared to p(t) and model parameters TSS, ATL, and CTL. MS was positively correlated with model output response p(t) (p < 0.01) and negatively with ATL (p < 0.01). Quadratic relationships were also observed between MS and both p(t) and CTL (p < 0.001), potentially indicating an optimal balance between fitness, fatigue, and performance. The results of this study demonstrate that the output of this simplified IR modeling approach correlates with performance in at least 1 elite athlete. Further studies are necessary to determine the generalizability of this method, but coaches may wish to use this approach to analyze previous training and performance relationships and iteratively modify training to optimize performance.
authors.affiliation: School of Health Promotion and Human Performance, Eastern Michigan University, Ypsilanti, Michigan, USA. smcgregor@emich.edu
authors.forename: Stephen J
authors.initials: SJ
authors.lastname: McGregor
authors.forename: Rachael K
authors.initials: RK
authors.lastname: Weese
authors.forename: Ian K
authors.initials: IK
authors.lastname: Ratz
mesh_terms: D000328:Adult; D015308:Anaerobic Threshold / Q000502:physiology; D000704:Analysis of Variance; D056352:Athletes / Q000523:psychology; D054874:Athletic Performance / Q000502:physiology* / Q000523:psychology; D003163:Competitive Behavior; D003198:Computer Simulation; D004526:Efficiency / Q000502:physiology; D005081:Exercise Therapy / Q000379:methods; D006801:Humans; D008297:Male; D008954:Models, Biological; D018763:Muscle Fatigue / Q000502:physiology*; D010809:Physical Fitness / Q000502:physiology*; D011237:Predictive Value of Tests; D012123:Pulmonary Ventilation / Q000502:physiology; D012044:Regression Analysis; D012420:Running / Q000293:injuries / Q000502:physiology* / Q000523:psychology; D013997:Time Factors