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耐力和超级耐力运动员的人体测量学及训练特征与比赛成绩的关系。

Relationship of anthropometric and training characteristics with race performance in endurance and ultra-endurance athletes.

作者信息

Knechtle Beat

机构信息

Institute of General Practice and Health Services Research, University of Zurich, Zurich, Switzerland ; Gesundheitszentrum St. Gallen, St. Gallen, Switzerland.

出版信息

Asian J Sports Med. 2014 Jun;5(2):73-90.

Abstract

A variety of anthropometric and training characteristics have been identified as predictor variables for race performance in endurance and ultra-endurance athletes. Anthropometric characteristics such as skin-fold thicknesses, body fat, circumferences and length of limbs, body mass, body height, and body mass index were bi-variately related to race performance in endurance athletes such as swimmers in pools and in open water, in road and mountain bike cyclists, and in runners and triathletes over different distances. Additionally, training variables such as volume and speed were also bi-variately associated with race performance. Multi-variate regression analyses including anthropometric and training characteristics reduced the predictor variables mainly to body fat and speed during training units. Further multi-variate regression analyses including additionally the aspects of previous experience such as personal best times showed that mainly previous best time in shorter races were the most important predictors for ultra-endurance race times. Ultra-endurance athletes seemed to prepare differently for their races compared to endurance athletes where ultra-endurance athletes invested more time in training and completed more training kilometers at lower speed compared to endurance athletes. In conclusion, the most important predictor variables for ultra-endurance athletes were a fast personal best time in shorter races, a low body fat and a high speed during training units.

摘要

多种人体测量和训练特征已被确定为耐力和超耐力运动员比赛成绩的预测变量。人体测量特征,如皮褶厚度、体脂、肢体周长和长度、体重、身高以及体重指数,与耐力运动员的比赛成绩存在双变量关系,这些耐力运动员包括泳池和公开水域的游泳运动员、公路和山地自行车手以及不同距离的跑步运动员和铁人三项运动员。此外,训练变量,如训练量和速度,也与比赛成绩存在双变量关联。包含人体测量和训练特征的多元回归分析将预测变量主要减少到体脂和训练单元期间的速度。进一步的多元回归分析,另外纳入诸如个人最好成绩等以往经验方面,结果显示,较短距离比赛中的以往最好成绩主要是超耐力比赛时间的最重要预测因素。与耐力运动员相比,超耐力运动员似乎对比赛的准备方式不同,超耐力运动员在训练中投入更多时间,且与耐力运动员相比,以较低速度完成更多的训练公里数。总之,超耐力运动员最重要的预测变量是较短距离比赛中的快速个人最好成绩、低体脂以及训练单元期间的高速度。

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