Manunzio Christian, Mester Joachim, Kaiser Walter, Wahl Patrick
Institute of Training Science and Sport Informatics, German Sport University Cologne, Germany.
Institute of Training Science and Sport Informatics, German Sport UniversityCologne, Germany; The German Research Centre of Elite Sport, German Sport University CologneCologne, Germany.
Front Physiol. 2016 Dec 27;7:642. doi: 10.3389/fphys.2016.00642. eCollection 2016.
To monitor the training intensity distribution (TID) and the development of physiological and performance parameters. During their preparation period for the RAAM, 4 athletes (plus 1 additional backup racer) performed 3 testing sessions; one before, one after 3, and one after 6 months of training. VO, maximal rate of lactate accumulation (dLa/dt), critical power, power output at lactate minimum (MLSS), peak and mean power output during a sprint test, heart rate recovery, isometric strength, jumping height, and body composition were determined. All training sessions were recorded with a power meter. The endurance TID was analyzed based on the time in zone approach, according to a classical 3-zone model, including all power data of training sessions, and a power specific 3-zone model, where time with power output below 50% of MLSS was not considered. The TID using the classical 3-zone model reflected a pyramidal TID (zone 1: 63 ± 16, zone 2: 28 ± 13 and zone 3: 9 ± 4%). The power specific 3-zone model resulted in a threshold-based TID (zone 1: 48 ± 13, zone 2: 39 ± 10, zone 3: 13 ± 4%). VO increased by 7.1 ± 5.3% ( = 0.06). dLa/dt decreased by 16.3 ± 8.1% ( = 0.03). Power output at lactate minimum and critical power increased by 10.3 ± 4.1 and 16.8 ± 6.2% ( = 0.01), respectively. No changes were found for strength parameters and jumps. The present study underlines that a threshold oriented TID results in only moderate increases in physiological parameters. The amount of training below 50% of MLSSp (~28% of total training time) is remarkably high. Researchers, trainers, and athletes should pay attention to the different ways of interpreting training power data, to gain realistic insights into the TID and the corresponding improvements in performance and physiological parameters.
监测训练强度分布(TID)以及生理和运动表现参数的变化。在4名运动员(外加1名备用车手)备战环美自行车耐力赛(RAAM)期间,进行了3次测试;分别在训练前、训练3个月后和训练6个月后各进行一次。测定了最大摄氧量(VO)、乳酸积累最大速率(dLa/dt)、临界功率、乳酸最低值时的功率输出(MLSS)、冲刺测试中的峰值和平均功率输出、心率恢复情况、等长肌力、跳跃高度以及身体成分。所有训练课程均使用功率计进行记录。耐力TID基于“区域时间”方法进行分析,依据经典的三区模型,包括训练课程的所有功率数据,以及一个特定功率的三区模型,其中功率输出低于MLSS的50%的时间不被考虑。使用经典三区模型的TID呈现出金字塔形TID(1区:63±16,2区:28±13,3区:9±4%)。特定功率的三区模型得出基于阈值的TID(1区:48±13,2区:39±10,3区:13±4%)。VO增加了7.1±5.3%( = 0.06)。dLa/dt下降了16.3±8.1%( = 0.03)。乳酸最低值时的功率输出和临界功率分别增加了10.3±4.1%和16.8±6.2%( = 0.01)。力量参数和跳跃方面未发现变化。本研究强调,基于阈值的TID只会导致生理参数适度增加。低于MLSSp的50%(约占总训练时间的28%)的训练量非常高。研究人员、教练和运动员应注意解释训练功率数据的不同方式,以便对TID以及相应的运动表现和生理参数改善有实际的了解。