Thornton Heidi Rose, Armstrong Cameron R, Rigby Alex, Minahan Clare L, Johnston Rich D, Duthie Grant Malcolm
Gold Coast Suns Football Club, Metricon Stadium, Carrara, QLD, Australia.
Griffith Sports Science, Griffith University, Gold Coast, QLD, Australia.
Front Sports Act Living. 2020 Dec 23;2:608939. doi: 10.3389/fspor.2020.608939. eCollection 2020.
The aims were to investigate the externally measured weekly loads, and the distribution intensity relative to the 1-min maximal mean (MM) intensity of matches. Athletes ( = 28) wore 10 Hz GNSS devices during training and matches. For the descriptive analysis, a range of movement variables were collected, including total distance, high-speed distance, very high-speed distance, acceleration, and acceleration load. Using raw GNSS files, 1-min moving averages were calculated for speed (m·min) and acceleration (m·s), and were multiplied by time, specifying total distance (m), and by body mass to quantify impulse (kN·s). The distribution of distance and impulse accumulated at varied intensities relative to MMs was calculated, with percentages ranging from zero to 110%. Drills were categorized as either; warm-ups, skill drills, games (i.e., small-sided games), conditioning and matches. Linear mixed models determined if the distribution of intensity within each threshold (>50%) varied between drill types and matches, and if the distribution within drill types varied across the season. Effects were described using standardized effect sizes (ES) and 90% confidence limits (CL). Compared to matches, a higher proportion of distance was accumulated at 50% of the MM within warm-ups and conditioning (ES range 0.86-1.14). During matches a higher proportion of distance was accumulated at 60% of MM when compared to warms ups, skill drills and conditioning (0.73-1.87). Similarly, greater proportion of distance was accumulated between 70 and 100% MM in matches compared to skill drills and warm-ups (1.05-3.93). For impulse, matches had a higher proportion between 60 and 80% of the MM compared to conditioning drills (0.91-3.23). There were no other substantial differences in the proportion of impulse between matches and drill types. When comparing phases, during competition there was a higher proportion of distance accumulated at 50% MM than general preparation (1.08). A higher proportion of distance was covered at higher intensities within matches compared to drills. The proportion of impulse was higher between 60 and 80% MM within matches compared to conditioning. Practitioners can therefore ensure athletes are not only exposed to the intensities common within competition, but also the volume accumulated is comparable, which may have positive performance outcomes, but is also extremely important in the return to play process.
目的是调查外部测量的每周负荷,以及相对于比赛1分钟最大平均(MM)强度的分布强度。运动员(n = 28)在训练和比赛期间佩戴10 Hz的全球导航卫星系统(GNSS)设备。对于描述性分析,收集了一系列运动变量,包括总距离、高速距离、极高速距离、加速度和加速度负荷。使用原始GNSS文件,计算速度(米/分钟)和加速度(米/秒²)的1分钟移动平均值,并乘以时间以确定总距离(米),再乘以体重以量化冲量(千牛·秒)。计算相对于MM在不同强度下积累的距离和冲量分布,百分比范围为0%至110%。训练分为以下几类:热身、技能训练、比赛(即小型比赛)、体能训练和正式比赛。线性混合模型确定每个阈值(>50%)内强度分布在训练类型和正式比赛之间是否存在差异,以及训练类型内的分布在整个赛季中是否变化。使用标准化效应量(ES)和90%置信区间(CL)描述效应。与正式比赛相比,热身和体能训练中在MM的50%时积累的距离比例更高(ES范围为0.86 - 1.14)。与热身、技能训练和体能训练相比,正式比赛中在MM的60%时积累的距离比例更高(0.73 - 1.87)。同样,与技能训练和热身相比,正式比赛中在MM 的70%至100%之间积累的距离比例更大(1.05 - 3.93)。对于冲量,与体能训练相比,正式比赛在MM的60%至80%之间的比例更高(0.91 - 3.23)。正式比赛和训练类型之间冲量比例没有其他实质性差异。比较不同阶段时,比赛期间在MM的50%时积累的距离比例高于一般准备阶段(1.08)。与训练相比,正式比赛中在更高强度下覆盖的距离比例更高。与体能训练相比,正式比赛在MM的60%至80%之间的冲量比例更高。因此,从业者可以确保运动员不仅接触到比赛中常见的强度,而且积累的运动量相当,这可能会产生积极的运动表现结果,在重返比赛过程中也极其重要。