Yustres Inmaculada, Del Cerro Jesús Santos, González-Mohíno Fernando, Peyrebrune Michael, González-Ravé José María
Department of Physical Activity and Sport Sciences, University of Castilla-La Mancha, Toledo, Spain.
Facultad de Lenguas y Educación, Universidad Nebrija, Madrid, Spain.
Front Psychol. 2020 Jan 22;10:3078. doi: 10.3389/fpsyg.2019.03078. eCollection 2019.
The primary aim was to create a performance progression model of elite competitors in the World Swimming Championships from 2006 to 2017 for all strokes and distances. Secondly, to identify the influence of annual ratios of progression, ages of peak performance and junior status on success in senior competitions.
Data regarding the participants of senior and junior World Championships (WCs) between 2006 and 2017 were obtained from FINA. The final filtered database, after removing those swimmers who just participated in junior WCs, included 4076. Statistical models were used to examine differences between the top senior swimmers (the top 30% best performances; T30) and lower level swimmers (the bottom 70% performances; L70) for minimum age (MA), progress (P) and best junior time (BJ). In order to identify the variables that contribute to reach the T30 group, a logistic regression (LR), stepwise LR and decision tree were applied. To analyze the effect of each variable separately, a simple LR (gross odds ratio) was performed. Ratio probabilities (OR) and 95% confidence intervals were calculated for each variable.
Swimmer's BJ and P were higher in the T30 group ( < 0.000). The decision tree showed the greatest explanatory capacity for BJ, followed by P. The MA had a very low explanatory capacity and was not significant in the LR.
Swimmers with exceptional junior performance times, or have a high rate of progress are more likely to be successful at the senior WCs.
主要目标是为2006年至2017年世界游泳锦标赛中所有泳姿和距离的精英选手创建一个成绩进步模型。其次,确定年度进步率、最佳成绩年龄和青年组身份对成年组比赛成绩的影响。
从国际泳联获取了2006年至2017年期间成年组和青年组世界锦标赛(WC)参与者的数据。在剔除仅参加青年组WC的游泳运动员后,最终筛选出的数据库包含4076名运动员。使用统计模型检验顶级成年组游泳运动员(最佳成绩前30%;T30)和较低水平游泳运动员(成绩后70%;L70)在最小年龄(MA)、进步(P)和最佳青年组成绩(BJ)方面的差异。为了确定有助于进入T30组的变量,应用了逻辑回归(LR)、逐步LR和决策树。为了分别分析每个变量的影响,进行了简单LR(总优势比)。计算每个变量的比值概率(OR)和95%置信区间。
T30组游泳运动员的BJ和P更高(<0.000)。决策树对BJ的解释能力最强,其次是P。MA的解释能力非常低,在LR中不显著。
青年组成绩优异或进步速度快的游泳运动员在成年组世界锦标赛中更有可能取得成功。