Mangine Gerald T, Tankersley Joy E, McDougle Jacob M, Velazquez Nathanael, Roberts Michael D, Esmat Tiffany A, VanDusseldorp Trisha A, Feito Yuri
Department of Exercise Science and Sport Management, Kennesaw State University, Kennesaw, GA 30144, USA.
School of Kinesiology, Auburn University, Auburn, AL 36849, USA.
Sports (Basel). 2020 Jul 20;8(7):102. doi: 10.3390/sports8070102.
The 2018 CrossFit Open (CFO) was the initial stage of an annual competition that consisted of five weekly workouts. Current evidence suggests that a variety of fitness parameters are important for progressing beyond this stage, but little is known about which are the most important. To examine relationships between CFO performance, experience, and physiological fitness, sixteen experienced (>2 years) athletes (30.7 ± 6.9 years, 171 ± 12 cm, 78.0 ± 16.2 kg) volunteered to provide information about their training and competitive history, and then complete a battery of physiological assessments prior to competing in the 2018 CFO. Athletes' resting energy expenditure, hormone concentrations, body composition, muscle morphology, cardiorespiratory fitness, and isometric strength were assessed on two separate occasions. Spearman correlations demonstrated significant ( < 0.05) relationships between most variables and performance on each workout. Stepwise regression revealed competition experience (R = 0.31-0.63), body composition (R = 0.55-0.80), vastus lateralis cross-sectional area (R = 0.29-0.89), respiratory compensation threshold (R = 0.54-0.75), and rate of force development (R = 0.30-0.76) to be the most common predictors. Of these, body composition was the most important. These fitness parameters are known targets with established training recommendations. Though preliminary, athletes may use these data to effectively train for CFO competition.
2018年CrossFit公开赛(CFO)是一项年度赛事的初始阶段,该赛事由五次每周训练组成。目前的证据表明,多种健身参数对于在这个阶段之后取得进展很重要,但对于哪些是最重要的参数却知之甚少。为了研究CFO表现、经验和生理健康之间的关系,16名有经验的(>2年)运动员(30.7±6.9岁,171±12厘米,78.0±16.2千克)自愿提供他们的训练和比赛历史信息,然后在参加2018年CFO之前完成一系列生理评估。在两个不同的时间点评估了运动员的静息能量消耗、激素浓度、身体成分、肌肉形态、心肺适能和等长力量。Spearman相关性分析表明,大多数变量与每次训练的表现之间存在显著(<0.05)关系。逐步回归显示比赛经验(R=0.31-0.63)、身体成分(R=0.55-0.80)、股外侧肌横截面积(R=0.29-0.89)、呼吸补偿阈值(R=0.54-0.75)和力量发展速率(R=0.30-0.76)是最常见的预测因素。其中,身体成分是最重要的。这些健身参数是已知的目标,并有既定的训练建议。尽管是初步的,但运动员可以利用这些数据有效地为CFO比赛进行训练。