Helsen Werner F, Thomis Martine, Starkes Janet L, Vrijens Sander, Ooms Gerrit, MacMaster Calum, Towlson Chris
KU Leuven, Department of Movement Sciences, Leuven, Belgium.
Department of Kinesiology, McMaster University, Hamilton, ON, Canada.
Front Sports Act Living. 2021 Mar 4;3:635379. doi: 10.3389/fspor.2021.635379. eCollection 2021.
Despite various solutions proposed to solve the relative age effect (RAE), it is still a major problem confounding talent identification and selection processes. In the first phase, we sampled 302 under 7-21 academy soccer players from two Belgian professional soccer clubs to explore the potential of a new approach to solve the inequalities resulting from relative age- and maturity-related bias. This approach allocates players into four discrete quartile groups based on the midway point of their chronological and estimated developmental (ED) birth dates (calculated using the growth curves for stature of Belgian youth). With the use of chi square analyses, a RAE was found ( < 0.01) for the overall sample (Q1 = 41.4% vs. Q4 = 14.9%) that completely disappeared after reallocation (Q1 = 26.5%; Q2 = 21.9%; Q3 = 27.5%; Q4 = 24.2%). According to the new allocation method, the stature difference was reduced, on average, by 11.6 cm (from 24.0 ± 9.9 to 12.4 ± 3.4 cm, = 1.57). Body mass difference between the two methods was 1.9 kg (20.1 ± 11.3-18.2 ± 13.1 kg, respectively, = 0.15). The new method created a maximum chronological age difference of 1.9 vs. 0.8 years for the current method. With the use of this method, 47% of the players would be reallocated. Twenty-three percent would be moved up one age category, and 21% would be moved down. In the second phase, we also examined 80 UK academy soccer players to explore if reallocating players reduces the within-playing group variation of somatic and physical fitness characteristics. The percentage coefficient of variation (%CV) was reduced (0.2-10.1%) in 15 out of 20 metrics across U11-U16 age categories, with the U13 age category demonstrating the largest reductions (0.9-10.1%) in CV. The U12 and U13 age categories and associated reallocation groupings showed to (ES = 0.0-0.5) between-method differences and to (ES = 0.0-1.1) differences within the U14-U16 age categories. A reduction in RAE may lead to fewer dropouts and thus a larger player pool, which benefits, in turn, talent identification, selection, and development.
尽管为解决相对年龄效应（RAE）提出了各种解决方案，但它仍然是一个困扰人才识别和选拔过程的主要问题。在第一阶段，我们从比利时两个职业足球俱乐部抽取了302名7至21岁以下的青少年足球运动员，以探索一种新方法解决因相对年龄和成熟度相关偏差导致的不平等问题的潜力。这种方法根据球员实际出生日期和估计发育（ED）出生日期的中点（使用比利时青少年身高增长曲线计算）将球员分为四个离散的四分位数组。通过卡方分析，发现总体样本存在RAE（<0.01）（第一四分位数组 = 41.4%，第四四分位数组 = 14.9%），重新分配后完全消失（第一四分位数组 = 26.5%；第二四分位数组 = 21.9%；第三四分位数组 = 27.5%；第四四分位数组 = 24.2%）。根据新的分配方法，身高差异平均减少了11.6厘米（从24.0±9.9厘米降至12.4±3.4厘米，效应量 = 1.57）。两种方法之间的体重差异为1.9千克（分别为20.1±11.3千克和18.2±13.1千克，效应量 = 0.15）。新方法产生的最大实际年龄差异为1.9岁，而当前方法为0.8岁。使用这种方法，47%的球员将被重新分配。23%的球员将升入一个年龄组，21%的球员将降入一个年龄组。在第二阶段，我们还研究了80名英国青少年足球运动员，以探讨重新分配球员是否会减少比赛组内身体和体能特征的差异。在U11 - U16年龄组的20项指标中，有15项指标的变异系数百分比（%CV）降低了（0.2 - 10.1%），其中U13年龄组的CV降低幅度最大（0.9 - 10.1%）。U12和U13年龄组以及相关的重新分配分组在U14 - U16年龄组中显示出方法间差异为0.0至0.5（效应量），组内差异为0.0至1.1（效应量）。RAE的减少可能会导致辍学人数减少，从而扩大球员库，这反过来又有利于人才的识别、选拔和培养。
