1 / 18

Performance modelling and tapering

Performance modelling and tapering. Iñigo Mujika Department of Research and Development ATHLETIC CLUB BILBAO. Mathematical modelling and systems theory. Athlete = System. +. Fitness. Σ. Performance. Training. Fatigue. -. Banister & Fitz-Clarke J. Therm. Biol. 18: 587-597, 1993.

ringo
Download Presentation

Performance modelling and tapering

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

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 Σ Performance Training Fatigue - Banister & Fitz-Clarke J. Therm. Biol. 18: 587-597, 1993

  3. Modelling the effects of training Performance Positive influence Initial Negative Influence tn tg Time Training Mujika et al. Med. Sci. Sports Exerc. 28: 251-258, 1996

  4. Input System Ouput . . . . ? . t t Goodness-of-fit Characterisation of a dynamical process Busso & Thomas Int. J. Sports Physiol.Perf. 1: 400-405, 2006

  5. . Training Load (A.U. wk-1) Modelling application in swimming Performance (% PB) 105 100 95 90 Modeled Performance Actual Performance 85 0 5 10 15 20 25 30 35 40 45 Positive Influence (PI) Negative Influence (NI) 102 4 100 3 98 96 2 94 1 92 PI NI 90 0 0 5 10 15 20 25 30 35 40 45 120 100 80 60 40 20 0 0 5 10 15 20 25 30 35 40 45 Mujika et al. Med. Sci. Sports Exerc. 28: 251-258, 1996 Weeks of Training

  6. Mathematical modelling and taper duration Performance tg = 32 ± 12 days tn = 12 ± 6 days tn tg Time Training Mujika et al. Med. Sci. Sports Exerc. 28: 251-258, 1996

  7. Early Season Pre-Taper Post-Taper Positive Influence (PI) Negative Influence (NI) 3,5 100 99 3,0 98 2,5 97 2,0 96 ** 95 1,5 * 94 1,0 93 92 0,5 ES ES T1 T2 T1 T2 T3 Modelling the effects of the taper T3 Mujika et al. Med. Sci. Sports Exerc. 28: 251-258, 1996

  8. Swimmer HR 14 38 Varying adaptation profiles Performance Swimmer CJ 10 24 Time Training

  9. “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)” Limitations and model evolution Thomas et al. J. Sports Sci. 26: 643-652, 2008

  10. Input Ouput Model & Parameters ? t t Input Ouput Model & Parameters ? t t Prediction of system’s behaviour from previous observation Busso & Thomas Int. J. Sports Physiol.Perf. 1: 400-405, 2006

  11. 25.4* Without OT 16.4 22.3* Duration (days) With OT 42.5* 22.4 39.1* 101.1 Without OT 101.1 101.1 Performance (% Personal record) With OT 101.5* 101.4 101.5* Characteristics of the optimal simulated taper Form of training reduction Linear Step Exponential 46.3* Without OT 65.3 54.7*$ % Reduction With OT 43.1* 67.4 51.6*$ *: different from Step; $: different from Linear Thomas et al. J. Sports Sci. 26: 643-652, 2008

  12. Optimal Training Load (Training Units) Optimal Reduction (% Pre-Taper Training) 100 * 6 5 80 4 60 3 40 2 20 1 0 0 Without OT With OT Without OT With OT Optimal Duration (Days) Performance Improvement (% Pre-Taper Performance) 5 * ** 30 25 4 20 3 15 2 10 1 5 0 0 Without OT With OT Without OT With OT Effects of previous training on optimal taper characteristics Thomas et al. J. Sports Sci. 26: 643-652, 2008

  13. WITHOUT OT WITH OT Negative Influence Negative Influence 5 5 * $ 4 4 * 3 3 2 2 1 1 0 0 Pre Post Pre Post * Positive Influence Positive Influence $ 102 102 101 101 100 100 99 99 98 98 97 97 Pre Post Pre Post Performance (% Personal Record) Performance (% Personal Record) $ * * 102 102 101 101 100 100 $ 99 99 98 98 97 97 Pre Post Pre Post Effects of optimal taper on NI, PI and performance Thomas et al. J. Sports Sci. 26: 643-652, 2008

  14. Changes in training load during optimal two-phase taper Training Load (%NT) OT 120 NT 100 *$ 80 60 40 20 0 0 1 2 3 4 5 6 Weeks of Taper Thomas et al. J. Strength Cond. Res. Submitted

  15. Performance Optimal two-phase taper 103,55 103,50 Optimal linear taper 103,45 103,40 26 27 28 29 30 Days of Taper Performance changes during optimal two-phase taper Performance (%NT) 104 103 102 101 NT 100 99 OT 98 97 96 0 1 2 3 4 Weeks of 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 Conclusions

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

More Related