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Performance modelling and tapering Iñigo Mujika Department of Research and Development ATHLETIC CLUB BILBAO.

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Presentation on theme: "Performance modelling and tapering Iñigo Mujika Department of Research and Development ATHLETIC CLUB BILBAO."— Presentation transcript:

1 Performance modelling and tapering Iñigo Mujika Department of Research and Development ATHLETIC CLUB BILBAO

2 Mathematical modelling and systems theory Athlete = System Fitness Fatigue Σ Training - + Performance Banister & Fitz-Clarke J. Therm. Biol. 18: , 1993

3 Modelling the effects of training Mujika et al. Med. Sci. Sports Exerc. 28: , 1996 Time Training Performance Initial Negative Influence Positive influence tntn tgtg

4 Characterisation of a dynamical process Busso & Thomas Int. J. Sports Physiol. Perf. 1: , 2006 ? t t InputOuputSystem..... Goodness-of-fit

5 Weeks of Training PI NI Modeled Performance Actual Performance Performance (% PB) Positive Influence (PI)Negative Influence (NI) Training Load (A.U. wk -1 ). Mujika et al. Med. Sci. Sports Exerc. 28: , 1996 Modelling application in swimming

6 Mathematical modelling and taper duration Mujika et al. Med. Sci. Sports Exerc. 28: , 1996 Time Training Performance t g = 32 ± 12 days t n = 12 ± 6 days tntn tgtg

7 Mujika et al. Med. Sci. Sports Exerc. 28: , 1996 T Positive Influence (PI) Early SeasonPre-TaperPost-Taper T1T2 ES 0,5 1,0 1,5 2,0 2,5 3,0 3,5 ** * Negative Influence (NI) T1T2T3 ES Modelling the effects of the taper

8 Varying adaptation profiles Time Training 10 Performance 24 Swimmer HR 1438 Swimmer CJ

9 Limitations and model evolution “The theoretical analysis based on the original model of Banister et al. (1975) is possibly flawed because of the underlying linear formulation. The response to a given training dose was independent of the accumulated fatigue with past training. This implies that the taper duration should be identical whatever the severity of the training preceding the taper ” “This led us to propose a formulation of a new non-linear model. This non- linear model implied that the magnitude and duration of the fatigue produced by a given training dose increased with the repetition of exercise bouts, and was reversed when training was reduced (Busso, 2003)” Thomas et al. J. Sports Sci. 26: , 2008

10 Prediction of system’s behaviour from previous observation Busso & Thomas Int. J. Sports Physiol. Perf. 1: , 2006 Model & Parameters ? t t InputOuput Model & Parameters ? t t InputOuput

11 Characteristics of the optimal simulated taper % Reduction Form of training reduction StepExponential *$ 51.6*$ Without OT With OT Linear 46.3* 43.1* Duration (days) * 39.1* Without OT With OT 25.4* 42.5* Performance (% Personal record) * Without OT With OT * *: different from Step; $: different from Linear Thomas et al. J. Sports Sci. 26: , 2008

12 Effects of previous training on optimal taper characteristics Without OTWith OT * Optimal Training Load (Training Units) Without OTWith OT Optimal Reduction (% Pre-Taper Training) Without OTWith OT * Optimal Duration (Days) Without OTWith OT ** Performance Improvement (% Pre-Taper Performance) Thomas et al. J. Sports Sci. 26: , 2008

13 Effects of optimal taper on NI, PI and performance PrePost * Negative Influence PrePost Positive Influence PrePost * Performance (% Personal Record) WITHOUT OT PrePost * Negative Influence PrePost Positive Influence PrePost Performance (% Personal Record) WITH OT $ * $ * $ $ Thomas et al. J. Sports Sci. 26: , 2008

14 Changes in training load during optimal two-phase taper Weeks of Taper Training Load (%NT) Thomas et al. J. Strength Cond. Res. Submitted * $* $ NT OT

15 Performance changes during optimal two-phase taper Weeks of Taper Performance (%NT) NT OT ,40 103,45 103,50 103,55 Days of Taper Performance Optimal linear taper Optimal two-phase taper Thomas et al. J. Strength Cond. Res. Submitted

16 Conclusions

17 The available data on performance modelling confirm the relevance of the modelling approach in the study of individual responses to training and the optimisation of tapering strategies Computer simulations based on mathematical modelling offer new prospects for further investigation into innovative tapering strategies and performance optimisation

18 ESKERRIK ASKO! (“Thank you very much!” in Basque Language)


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