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1.
J Sports Sci ; 24(5): 509-20, 2006 May.
Article in English | MEDLINE | ID: mdl-16608765

ABSTRACT

The aim of this study was to carry out a statistical analysis of the Banister model to verify how useful it is in monitoring the training programmes of elite swimmers. The accuracy, the ill-conditioning and the stability of this model were thus investigated. The training loads of nine elite swimmers, measured over one season, were related to performances with the Banister model. First, to assess accuracy, the 95% bootstrap confidence interval (95% CI) of parameter estimates and modelled performances were calculated. Second, to study ill-conditioning, the correlation matrix of parameter estimates was computed. Finally, to analyse stability, iterative computation was performed with the same data but minus one performance, chosen at random. Performances were related to training loads for all participants (R(2) = 0.79 +/- 0.13, P < 0.05) and the estimation procedure seemed to be stable. Nevertheless, the range of 95% CI values of the most useful parameters for monitoring training was wide: t(a) = 38 (17, 59), t(f) = 19 (6, 32), t(n) = 19 (7, 35), t(g) = 43 (25, 61). Furthermore, some parameters were highly correlated, making their interpretation worthless. We suggest possible ways to deal with these problems and review alternative methods to model the training-performance relationships.


Subject(s)
Models, Biological , Physical Education and Training , Physical Fitness/physiology , Swimming/physiology , Adult , Female , Humans , Male , Physical Education and Training/methods , Rest/physiology , Task Performance and Analysis
2.
J Strength Cond Res ; 19(1): 67-75, 2005 Feb.
Article in English | MEDLINE | ID: mdl-15705048

ABSTRACT

The aim of this study was to model the residual effects of training on the swimming performance and to compare a model that includes threshold saturation (MM) with the Banister model (BM). Seven Olympic swimmers were studied over a period of 4 +/- 2 years. For 3 training loads (low-intensity w(LIT), high-intensity w(HIT), and strength training w(ST)), 3 residual training effects were determined: short-term (STE) during the taper phase (i.e., 3 weeks before the performance [weeks 0, 1, and 2]), intermediate-term (ITE) during the intensity phase (weeks 3, 4, and 5), and long-term (LTE) during the volume phase (weeks 6, 7, and 8). ITE and LTE were positive for w(HIT) and w(LIT), respectively (p < 0.05). Low-intensity training load during taper was related to performances by a parabolic relationship (p < 0.05). Different quality measures indicated that MM compares favorably with BM. Identifying individual training thresholds may help individualize the distribution of training loads.


Subject(s)
Models, Biological , Physical Education and Training/methods , Physical Endurance/physiology , Swimming/physiology , Adult , Female , Humans , Male , Muscle, Skeletal/physiology , Regression Analysis
3.
Med Sci Sports Exerc ; 36(2): 218-24, 2004 Feb.
Article in English | MEDLINE | ID: mdl-14767243

ABSTRACT

PURPOSE: The effect of training variations on 24-h urinary cortisol/cortisone (C/Cn) ratio was investigated in highly trained swimmers to determine whether it could be a good marker of training stress and performance. METHODS: Fourteen swimmers (five female and nine male) were tested after 4 wk of intense training (IT), 3 wk of reduced training (RT), and 5 wk of moderate training (MT). At the end of each period, the swimmers performed in their best event at an official competition. Individual performances were expressed as a percentage of the previous season's best performance. The fatigue state was evaluated with a questionnaire. RESULTS: The C/Cn ratio was statistically different for the three periods (IT: 1.10 +/- 0.7, RT: 0.64 +/- 0.3, and MT: 0.57 +/- 0.2). The differences in the C/Cn ratio between two consecutive performances were related to the differences in performance (r = -0.52, P < 0.01), and the C/Cn ratio was significantly related to the total training (r = 0.32, P < 0.05) and total score of fatigue (TSF) (r = 0.35, P < 0.03) over the follow-up period. Cn levels were related to the dryland training (r = -0.46; P < 0.01) and TSF (r = -0.40; P < 0.02). During IT, variations in the C/Cn ratio were related to the changes in the mean intensity (r = -0.67; P < 0.02) and to TSF (r = 0.69; P < 0.01). CONCLUSION: The 24-h C/Cn ratio was moderately related to both training and performance whereas Cn levels were only related to training. The C/Cn ratio could be a useful indicator for monitoring the overreaching state in elite swimmers.


Subject(s)
Cortisone/urine , Hydrocortisone/urine , Physical Education and Training/methods , Sports Medicine/methods , Swimming/physiology , Adult , Biomarkers/urine , Fatigue/urine , Female , Humans , Male , Stress, Physiological/urine , Task Performance and Analysis
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