Malone Shane, Owen Adam, Newton Matt, Mendes Bruno, Tiernan Leo, Hughes Brian, Collins Kieran
Human Performance Lab, Institute of Technology Tallaght, Ireland.
Claude Bernard University Lyon, Villeurbanne, Centre de Recherche et d'Innovation sur le Sport (CRIS), France; Servette Centre for Football Research (SCFR), Servette Football Club, Switzerland.
J Sci Med Sport. 2018 Jan;21(1):29-34. doi: 10.1016/j.jsams.2017.03.019. Epub 2017 Apr 13.
The objective of the investigation was to observe the impact of player wellbeing on the training output of elite soccer players.
Prospective cohort design.
Forty-eight soccer players (age: 25.3±3.1years; height: 183±7cm; mass: 72±7kg) were involved in this single season observational study across two teams. Each morning, pre-training, players completed customised perceived wellbeing questionnaires. Global positioning technology devices were used to measure external load (total distance, total high-speed running distance, high speed running, player load, player load slow, maximal velocity, maximal velocity exposures). Players reported ratings of perceived exertion using the modified Borg CR-10 scale. Integrated training load ratios were also analysed for total distance:RPE, total high speed distance:RPE player load:RPE and player load slow:RPE respectively.
Mixed-effect linear models revealed significant effects of wellbeing Z-score on external and integrated training load measures. A wellbeing Z-score of -1 corresponded to a -18±2m (-3.5±1.1%), 4±1m (-4.9±2.1%,) 0.9±0.1kmh (-3.1±2.1%), 1±1 (-4.6±2.9%), 25±3AU (-4.9±3.1%) and 11±0.5AU (-8.9±2.9%) reduction in total high speed distance, high speed distance, maximal velocity, maximal velocity exposures, player load and player load slow respectively. A reduction in wellbeing impacted external:internal training load ratios and resulted in -0.49±0.12mmin, -1.20±0.08mmin,-0.02±0.01AUmin in total distance:RPE, total high speed distance:RPE and player load slow:RPE respectively.
The results suggest that systematic monitoring of player wellbeing within soccer cohorts can provide coaches with information about the training output that can be expected from individual players during a training session.
本调查的目的是观察运动员健康状况对精英足球运动员训练产出的影响。
前瞻性队列设计。
48名足球运动员(年龄:25.3±3.1岁;身高:183±7厘米;体重:72±7千克)参与了这项针对两支球队的单赛季观察性研究。每天早晨,在训练前,运动员完成定制的健康感知问卷。使用全球定位技术设备测量外部负荷(总距离、总高速跑距离、高速跑、运动员负荷、运动员慢负荷、最大速度、最大速度暴露次数)。运动员使用改良的Borg CR-10量表报告自觉用力程度评分。还分别分析了总距离:主观用力程度、总高速距离:主观用力程度、运动员负荷:主观用力程度和运动员慢负荷:主观用力程度的综合训练负荷比率。
混合效应线性模型显示,健康Z评分对外部和综合训练负荷指标有显著影响。健康Z评分为-1时,总高速距离、高速距离、最大速度暴露次数、运动员负荷和运动员慢负荷分别减少-18±2米(-3.5±1.1%)、4±1米(-4.9±2.1%)、0.9±0.1千米/小时(-3.1±2.%)、1±1(-4.6±2.9%)、25±3任意单位(-4.9±3.1%)和11±0.5任意单位(-8.9±2.9%)。健康状况下降会影响外部:内部训练负荷比率,总距离:主观用力程度、总高速距离:主观用力程度和运动员慢负荷:主观用力程度分别减少-0.49±0.12分钟、-1.20±0.08分钟、-0.02±0.01任意单位/分钟。
结果表明,在足球群体中对运动员健康状况进行系统监测,可以为教练提供关于训练产出的信息,使他们了解在一次训练课中每个运动员可能达到的训练效果。