Galán-Rioja Miguel Ángel, Gonzalez-Ravé José María, González-Mohíno Fernando, Seiler Stephen
Sport Training Laboratory, Faculty of Sport Sciences, University of Castilla la Mancha, Toledo,Spain.
Facultad de Ciencias de la Vida y de la Naturaleza, Universidad Nebrija, Madrid,Spain.
Int J Sports Physiol Perform. 2023 Jan 14;18(2):112-122. doi: 10.1123/ijspp.2022-0302. Print 2023 Feb 1.
A well-planned periodized approach endeavors to allow road cyclists to achieve peak performance when their most important competitions are held.
To identify the main characteristics of periodization models and physiological parameters of trained road cyclists as described by discernable training intensity distribution (TID), volume, and periodization models.
The electronic databases Scopus, PubMed, and Web of Science were searched using a comprehensive list of relevant terms. Studies that investigated the effect of the periodization of training in cyclists and described training load (volume, TID) and periodization details were included in the systematic review.
Seven studies met the inclusion criteria. Block periodization (characterized by employment of highly concentrated training workload phases) ranged between 1- and 8-week blocks of high-, medium-, or low-intensity training. Training volume ranged from 8.75 to 11.68 h·wk-1 and both pyramidal and polarized TID were used. Traditional periodization (characterized by a first period of high-volume/low-intensity training, before reducing volume and increasing the proportion of high-intensity training) was characterized by a cyclic progressive increase in training load, the training volume ranged from 7.5 to 10.76 h·wk-1, and pyramidal TID was used. Block periodization improved maximum oxygen uptake (VO2max), peak aerobic power, lactate, and ventilatory thresholds, while traditional periodization improved VO2max, peak aerobic power, and lactate thresholds. In addition, a day-by-day programming approach improved VO2max and ventilatory thresholds.
No evidence is currently available favoring a specific periodization model during 8 to 12 weeks in trained road cyclists. However, few studies have examined seasonal impact of different periodization models in a systematic way.
精心规划的周期化训练方法旨在使公路自行车运动员在最重要的比赛举行时达到最佳竞技状态。
根据可识别的训练强度分布（TID）、训练量和周期化模型，确定周期化模型的主要特征以及训练有素的公路自行车运动员的生理参数。
使用相关术语综合列表检索电子数据库Scopus、PubMed和Web of Science。系统评价纳入了研究自行车运动员训练周期化效果并描述训练负荷（训练量、TID）和周期化细节的研究。
七项研究符合纳入标准。分段周期化（其特点是采用高度集中的训练工作量阶段）包括1至8周的高、中、低强度训练阶段。训练量在8.75至11.68小时·周-1之间，同时使用了金字塔形和极化TID。传统周期化（其特点是在减少训练量并增加高强度训练比例之前，先进行一段时间的高训练量/低强度训练）的特点是训练负荷呈周期性逐渐增加，训练量在7.5至10.76小时·周-1之间，并使用了金字塔形TID。分段周期化提高了最大摄氧量（VO2max）、峰值有氧功率、乳酸和通气阈值，而传统周期化提高了VO2max、峰值有氧功率和乳酸阈值。此外，逐日编程方法提高了VO2max和通气阈值。
目前没有证据表明在训练有素的公路自行车运动员的8至12周训练期间，某种特定的周期化模型更具优势。然而，很少有研究系统地考察不同周期化模型的季节影响。
