This study quantifies the maximum number of impacts and peak running demands during 1– to 10– minute rolling window periods in elite rugby union matches using a multi-team dataset (n = 2232 player-games). Maximum values for impacts (impacts·min⁻¹) and running (m·min⁻¹) were calculated for 161 athletes from four teams across the 2018 and 2019 Super Rugby seasons. The effect of window duration and playing position on peak impact and running demands were estimated using linear mixed effect models and prediction intervals. The peak impact and running demands for a 1-min period were 4.5 – 5.5 impacts·min⁻¹ and 150 – 180 m·min⁻¹, depending on playing position. While small variations in mean impact and running movements could be observed by position, the large prediction interval and individual player variation meant that there was no practically meaningful difference by position. As such, when prescribing training drills to replicate the peak demands in rugby union, impact and running movements of players can be similar, regardless of position. Using a prediction interval allows us to identify the range where the demands in a future game may fall, and are beneficial to use when also trying to prepare players for the demands of rugby union.

这项研究使用多团队数据集（n = 2232个玩家游戏）对精英橄榄球联盟比赛中1到10分钟滚动窗口期间的最大影响数和峰值跑步需求进行了量化。计算了2018年和2019年超级橄榄球赛季四支球队的161名运动员的冲击力（impacts·min ^-1）和跑步（m·min ^-1）的最大值。使用线性混合效应模型和预测间隔来估计窗口持续时间和比赛位置对最高冲击力和跑步需求的影响。1分钟内的峰值冲击和运行需求为4.5 – 5.5 Impacts·min ^-1和150 – 180 m·min ^-1，具体取决于比赛位置。虽然按位置可以观察到平均冲击和奔跑动作的微小变化，但较大的预测间隔和单个运动员的变化意味着按位置没有实际意义上的差异。这样，当规定训练演习来复制橄榄球联合会的最高要求时，无论位置如何，运动员的撞击和奔跑动作都可能相似。使用预测间隔可以使我们确定未来游戏的需求可能下降的范围，并且在尝试为球员准备橄榄球联合的需求时很有用。