Laboratoire Interuniversitaire de Biologie de la Motricité, Université Jean Monnet Saint-Etienne, Lyon 1, Université Savoie Mont-Blanc, Saint-Etienne, FRANCE.
Club des Dauphins de Guilherand-Granges, Guilherand-Granges, FRANCE.
Med Sci Sports Exerc. 2023 Jul 1;55(7):1274-1285. doi: 10.1249/MSS.0000000000003139. Epub 2023 Feb 7.
The aim of this study was to compare the suitability of models for practical applications in training planning.
We tested six impulse-response models, including Banister's model (Model Ba), a variable dose-response model (Model Bu), and indirect-response models differing in the way they account or not for the effect of previous training on the ability to respond effectively to a given session. Data from 11 swimmers were collected during 61 wk across two competitive seasons. Daily training load was calculated from the number of pool-kilometers and dry land workout equivalents, weighted according to intensity. Performance was determined from 50-m trials done during training sessions twice a week. Models were ranked on the base of Aikaike's information criterion along with measures of goodness of fit.
Models Ba and Bu gave the greatest Akaike weights, 0.339 ± 0.254 and 0.360 ± 0.296, respectively. Their estimates were used to determine the evolution of performance over time after a training session and the optimal characteristics of taper. The data of the first 20 wk were used to train these two models and predict performance for the after 8 wk (validation data set 1) and for the following season (validation data set 2). The mean absolute percentage error between real and predicted performance using Model Ba was 2.02% ± 0.65% and 2.69% ± 1.23% for validation data sets 1 and 2, respectively, and 2.17% ± 0.65% and 2.56% ± 0.79% with Model Bu.
The findings showed that although the two top-ranked models gave relevant approximations of the relationship between training and performance, their ability to predict future performance from past data was not satisfactory for individual training planning.
本研究旨在比较模型在训练计划中的实际应用的适用性。
我们测试了六个脉冲响应模型，包括巴尼斯特模型（模型 Ba）、可变剂量反应模型（模型 Bu）以及在考虑或不考虑先前训练对有效应对特定训练课程能力的影响方面不同的间接反应模型。数据来自两名参加两个竞赛赛季的游泳运动员，共收集了 61 周的 11 名游泳运动员的数据。根据强度对泳池公里数和旱地锻炼等效物的数量进行加权，计算每日训练负荷。每周两次在训练期间进行 50 米试验，以确定性能。根据赤池信息量准则和拟合优度的度量，对模型进行排名。
模型 Ba 和 Bu 的赤池信息量准则权重最大，分别为 0.339±0.254 和 0.360±0.296。他们的估计值用于确定训练后一段时间内的性能随时间的演变，以及最佳的渐降特征。前 20 周的数据用于训练这两个模型，并预测接下来 8 周的表现（验证数据集 1）和下一个赛季（验证数据集 2）。使用模型 Ba 时，真实表现与预测表现之间的平均绝对百分比误差分别为验证数据集 1 和 2 的 2.02%±0.65%和 2.69%±1.23%，使用模型 Bu 时，分别为 2.17%±0.65%和 2.56%±0.79%。
研究结果表明，尽管排名前两位的模型对训练与表现之间的关系进行了相关的近似，但它们从过去的数据中预测未来表现的能力并不足以满足个体训练计划的需求。
