Determining optimal cadence for an individual road cyclist from field data

The cadence that maximises power output developed at the crank by an individual cyclist is conventionally determined using a laboratory test. The purpose of this study was two-fold: (i) to show that such a cadence, which we call the optimal cadence, can be determined using power output, heart-rate, and cadence measured in the field and (ii) to describe methodology to do so. For an individual cyclist's sessions, power output is related to cadence and the elicited heart-rate using a non-linear regression model. Optimal cadences are found for two riders (83 and 70 revolutions per minute, respectively); these cadences are similar to the riders’ preferred cadences (82–92?rpm and 65–75?rpm). Power output reduces by approximately 6% for cadences 20?rpm above or below optimum. Our methodology can be used by a rider to determine an optimal cadence without laboratory testing intervention: the rider will need to collect power output, heart-rate, and cadence measurements from training and racing sessions over an extended period (>6 months); ride at a range of cadences within those sessions; and calculate his/her optimal cadence using the methodology described or a software tool that implements it.     

Convergent validity of a novel method for quantifying rowing training loads

Elite rowers complete rowing-specific and non-specific training, incorporating continuous and interval-like efforts spanning the intensity spectrum. However, established training load measures are unsuitable for use in some modes and intensities. Consequently, a new measure known as the T2minute method was created. The method quantifies load as the time spent in a range of training zones (time-in-zone), multiplied by intensity- and mode-specific weighting factors that scale the relative stress of different intensities and modes to the demands of on-water rowing. The purpose of this study was to examine the convergent validity of the T2minute method with Banister’s training impulse (TRIMP), Lucia’s TRIMP and Session-RPE when quantifying elite rowing training. Fourteen elite rowers (12 males, 2 females) were monitored during four weeks of routine training. Unadjusted T2minute loads (using coaches’ estimates of time-in-zone) demonstrated moderate-to-strong correlations with Banister’s TRIMP, Lucia’s TRIMP and Session-RPE (rho: 0.58, 0.55 and 0.42, respectively). Adjusting T2minute loads by using actual time-in-zone data resulted in stronger correlations between the T2minute method and Banister’s TRIMP and Lucia’s TRIMP (rho: 0.85 and 0.81, respectively). The T2minute method is an appropriate in-field measure of elite rowing training loads, particularly when actual time-in-zone values are used to quantify load.     

Training load quantification in elite swimmers using a modified version of the training impulse method

Abstract

Prior reports have described the limitations of quantifying internal training loads using hear rate (HR)-based objective methods such as the training impulse (TRIMP) method, especially when high-intensity interval exercises are performed. A weakness of the TRIMP method is that it does not discriminate between exercise and rest periods, expressing both states into a single mean intensity value that could lead to an underestimate of training loads. This study was designed to compare Banister's original TRIMP method (1991) and a modified calculation procedure (TRIMPc) based on the cumulative sum of partial TRIMP, and to determine how each model relates to the session rating of perceived exertion (s-RPE), a HR-independent training load indicator. Over four weeks, 17 elite swimmers completed 328 pool training sessions. Mean HR for the full duration of a session and partial values for each 50 m of swimming distance and rest period were recorded to calculate the classic TRIMP and the proposed variant (TRIMPc). The s-RPE questionnaire was self-administered 30 minutes after each training session. Both TRIMPc and TRIMP measures strongly correlated with s-RPE scores (r = 0.724 and 0.702, respectively; P < 0.001). However, TRIMPc was ～9% higher on average than TRIMP (117 ± 53 vs. 107 ± 47; P < 0.001), with proportionally greater inter-method difference with increasing workload intensity. Therefore, TRIMPc appears to be a more accurate and appropriate procedure for quantifying training load, particularly when monitoring interval training sessions, since it allows weighting both exercise and recovery intervals separately for the corresponding HR-derived intensity.     

我国优秀女子举重运动员邓薇的赛前训练研究

为研究我国优秀女子举重运动员邓薇赛前备战训练,从训练学角度探讨赛前训练规律,通过文献资料法、个案分析法和数理统计法,探索赛前训练研究热点,结合邓薇赛前阶段划分、训练内容和训练强度,对举重项目赛前训练进行研究。研究认为,邓薇赛前训练特点为:赛前训练阶段持续6周,最高训练量出现在第3、4周,第5周开始减量幅度较为明显,每周内训练内容相对集中,训练强度分布有明显的极化趋势。     

运用TRIMP评估足球训练负荷的研究

摘要:目的：探讨运用TRMP评估足球训练的负荷,简化足球训练中的负荷评价及控制过程。方法：采用芬兰产RS300X POLAR表对鲁能足球学校的U17梯队不同位置队员进行了TRIMP(Stagno算法)的采集,并将获得的数据进行分析,与通过现场采访和标准心里量表调查到的实际情况进行对照。结果：所得分训练手段和分时间段指标,与队员训练和比赛的实际吻合;球员在比赛中体能状况以及训练和比赛负荷的差距也可以通过对TRIMP的分析得到概括;可以利用TRIMP评价负荷及判断过度训练和疲劳等。结论：TRIMP的采集快速而简单,可以计算累积负荷量,并且指标可以有效指导训练计划的安排和调整,包括对长期训练计划的制定和临场技战术的调整。为教练的训练监控和计划安排提供理论支持,并期望该探索能在足球训练和比赛中得到推广和运用。