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Assessing worst case scenarios in movement demands derived from global positioning systems during international rugby union matches: Rolling averages versus fixed length epochs

机译:评估国际橄榄球联盟比赛期间源自全球定位系统的运动需求中的最坏情况:滚动平均值与固定长度时期

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摘要

The assessment of competitive movement demands in team sports has traditionally relied upon global positioning system (GPS) analyses presented as fixed-time epochs (e.g., 5–40 min). More recently, presenting game data as a rolling average has become prevalent due to concerns over a loss of sampling resolution associated with the windowing of data over fixed periods. Accordingly, this study compared rolling average (ROLL) and fixed-time (FIXED) epochs for quantifying the peak movement demands of international rugby union match-play as a function of playing position. Elite players from three different squads (n = 119) were monitored using 10 Hz GPS during 36 matches played in the 2014–2017 seasons. Players categorised broadly as forwards and backs, and then by positional sub-group (FR: front row, SR: second row, BR: back row, HB: half back, MF: midfield, B3: back three) were monitored during match-play for peak values of high-speed running (>5 m·s-1; HSR) and relative distance covered (m·min-1) over 60–300 s using two types of sample-epoch (ROLL, FIXED). Irrespective of the method used, as the epoch length increased, values for the intensity of running actions decreased (e.g., For the backs using the ROLL method, distance covered decreased from 177.4 ± 20.6 m·min-1 in the 60 s epoch to 107.5 ± 13.3 m·min-1 for the 300 s epoch). For the team as a whole, and irrespective of position, estimates of fixed effects indicated significant between-method differences across all time-points for both relative distance covered and HSR. Movement demands were underestimated consistently by FIXED versus ROLL with differences being most pronounced using 60 s epochs (95% CI HSR: -6.05 to -4.70 m·min-1, 95% CI distance: -18.45 to -16.43 m·min-1). For all HSR time epochs except one, all backs groups increased more (p < 0.01) from FIXED to ROLL than the forward groups. Linear mixed modelling of ROLL data highlighted that for HSR (except 60 s epoch), SR was the only group not significantly different to FR. For relative distance covered all other position groups were greater than the FR (p < 0.05). The FIXED method underestimated both relative distance (~11%) and HSR values (up to ~20%) compared to the ROLL method. These differences were exaggerated for the HSR variable in the backs position who covered the greatest HSR distance; highlighting important consideration for those implementing the FIXED method of analysis. The data provides coaches with a worst-case scenario reference on the running demands required for periods of 60–300 s in length. This information offers novel insight into game demands and can be used to inform the design of training games to increase specificity of preparation for the most demanding phases of matches.
机译:传统上,团队运动对竞技运动需求的评估依赖于以固定时间段(例如5-40分钟)呈现的全球定位系统(GPS)分析。最近,由于担心与固定时期的数据窗口化有关的采样分辨率的损失,将游戏数据呈现为滚动平均值已变得普遍。因此,本研究比较了滚动平均值(ROLL)和固定时间(FIXED)时期,以量化国际橄榄球联盟比赛的高峰运动需求与比赛位置的关系。在2014–2017赛季进行的36场比赛中,使用10 Hz GPS监控了来自三个不同班级(n = 119)的精英球员。在比赛过程中对球员进行大致的分类,包括前向和后向,然后按位置分组(FR:前排,SR:第二排,BR:后排,HB:后卫,MF:中场,B3:后三)进行监视-在60-300 s内播放高速运行(> 5 m·s -1 ; HSR)的峰值和相对距离(m·min -1 )使用两种类型的采样时间(滚动,固定)。无论使用哪种方法,随着历时长度的增加,跑步动作强度的值都会减小(例如,对于使用ROLL方法的后背,覆盖距离从177.4±20.6 m·min -1 减小在60秒内达到300秒的107.5±13.3 m·min -1 )。对于整个团队而言,无论职位高低,对固定影响的估计都表明,相对时间范围和高铁的所有时间点在方法上都存在显着差异。 FIXED与ROLL一致低估了运动需求,其中使用60 s epochs的差异最为明显(95%CI HSR:-6.05至-4.70 m·min -1 ,95%CI距离:-18.45至-16.43 m·min -1 )。对于除一个以外的所有HSR时间段,所有后卫组从固定到滚动都比前卫组增加(p <0.01)。 ROLL数据的线性混合建模突出表明,对于HSR(除了60 s epoch),SR是唯一与FR没有显着差异的组。对于相对距离,所有其他位置组均大于FR(p <0.05)。与ROLL方法相比,FIXED方法低估了相对距离(〜11%)和HSR值(高达〜20%)。对于背靠背位置的HSR变量(覆盖最大的HSR距离),这些差异被夸大了;强调了那些实施固定分析方法的重要考虑因素。该数据为教练提供了最坏情况的参考,以了解60-300 s的持续时间。该信息提供了对游戏需求的新颖见解,并可用于指导训练游戏的设计,以增加针对最苛刻的比赛阶段的准备工作的特异性。

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