# Performance modelling and tapering

## Presentation on theme: "Performance modelling and tapering"— Presentation transcript:

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: , 1993

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

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

Modelling application in swimming
Performance (% PB) 105 100 95 90 Modeled Performance Actual Performance 85 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 5 10 15 20 25 30 35 40 45 Training Load (A.U. wk-1) . 120 100 80 60 40 20 5 10 15 20 25 30 35 40 45 Mujika et al. Med. Sci. Sports Exerc. 28: , 1996 Weeks of Training

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: , 1996

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

Performance Swimmer HR 14 38 Swimmer CJ 10 24 Time Training

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

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

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

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

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

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

Performance changes during optimal two-phase taper
Performance (%NT) 104 27 26 28 29 30 103,40 103,45 103,50 103,55 Days of Taper Performance Optimal linear taper Optimal two-phase taper 103 102 101 NT 100 99 OT 98 97 96 1 2 3 4 Weeks of Taper Thomas et al. J. Strength Cond. Res. Submitted

Conclusions

Conclusions 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

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