School of Biological Sciences, The University of Queensland, St Lucia, Australia.
School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia.
Scand J Med Sci Sports. 2021 Aug;31(8):1647-1656. doi: 10.1111/sms.13969. Epub 2021 Apr 24.
We designed and tested a protocol for measuring the performance of individuals in small-sided soccer games. We tested our protocol on three different groups of youth players from elite Brazilian football academies. Players in each group played a series of 3v3 games, in which individuals were randomly assigned into new teams and against new opponents for each game. We calculated each individual's average individual goals scored, goals scored by teammates, goals conceded, and net team goals per game. Our protocol was consistent across days and repeatable across groups, with intraclass correlation coefficients (ICCs) of 0.57-0.69 for average net goals per game across testing days. Players could achieve high success by scoring goals or ensuring their team concede few goals. We also calculated the first and second dimension of a principal component analysis based on each player's number of goals scored, goals scored by teammates, and number of goals conceded per game. Players that were overall high performers had higher PC scores, while PC scores represented the type of contribution made by a player to overall performance. Positive PC values were indicative of high number of individual goals while negative values were associated with more goals from teammates and fewer conceded goals. Our design allows coaches and scouts to easily collect a robust metric of individual performance using randomly designed, small-sided games. We also provide simulations that allow one to apply our methodology for individual talent identification to other small-sided games in any team sport.
我们设计并测试了一种用于测量个人在小型足球比赛中表现的方案。我们在来自巴西精英足球学院的三组不同青年球员中测试了我们的方案。每组球员进行一系列 3v3 比赛，在每场比赛中，个人被随机分配到新的团队，并与新的对手对抗。我们计算了每个个体的平均个人进球数、队友进球数、失球数和每场比赛的净团队进球数。我们的方案在不同天和不同组别之间是一致的，平均每场比赛净进球数的组内相关系数（ICC）为 0.57-0.69。球员可以通过进球或确保自己的球队少失球来获得高成功率。我们还根据每个球员的进球数、队友进球数和每场比赛失球数，计算了主成分分析的第一维和第二维。总体表现出色的球员具有更高的 PC 分数，而 PC 分数代表了球员对整体表现的贡献类型。正 PC 值表示个人进球数高，而负 PC 值与更多来自队友的进球和更少失球相关。我们的设计使教练和球探能够使用随机设计的小型比赛轻松收集个人表现的可靠指标。我们还提供了模拟，允许将我们的个体才能识别方法应用于任何团队运动中的其他小型比赛。
