Hellard Philippe, Avalos Marta, Lacoste Lucien, Barale Frederic, Chatard Jean-Claude, Millet Gregoire P
Département d'Etudes et Recherches, Fédération Française de Natation, Paris.
J Sports Sci. 2006 May;24(5):509-20. doi: 10.1080/02640410500244697.
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.
本研究的目的是对巴尼斯特模型进行统计分析，以验证其在监测优秀游泳运动员训练计划方面的有用性。因此，对该模型的准确性、病态性和稳定性进行了研究。在一个赛季中测量的九名优秀游泳运动员的训练负荷，通过巴尼斯特模型与成绩相关联。首先，为了评估准确性，计算了参数估计值和模拟成绩的95%自助置信区间（95%CI）。其次，为了研究病态性，计算了参数估计值的相关矩阵。最后，为了分析稳定性，使用相同的数据但随机减去一个成绩进行迭代计算。所有参与者的成绩与训练负荷相关（R(2)=0.79±0.13，P<0.05），并且估计程序似乎是稳定的。然而，用于监测训练的最有用参数的95%CI值范围很宽：t(a)=38（17，59），t(f)=19（6，32），t(n)=19（7，35），t(g)=43（25，61）。此外，一些参数高度相关，使其解释毫无价值。我们提出了处理这些问题的可能方法，并回顾了模拟训练-成绩关系的替代方法。
