Aquino Rodrigo, Alves Isabella S, Padilha Maickel B, Casanova Filipe, Puggina Enrico F, Maia José
CIFI2D, Faculty of Sport, University of Porto, Porto, Portugal.
Post-graduate Program in Rehabilitation and Functional Performance, Medicine School of Ribeirao Preto, University of São Paulo, Ribeirao Preto, Brazil.
J Hum Kinet. 2017 Dec 28;60:113-121. doi: 10.1515/hukin-2017-0094. eCollection 2017 Dec.
This study determined whether a multivariate profile more effectively discriminated selected than non-selected elite youth Brazilian soccer players. This examination was carried out on 66 youth soccer players (selected, n = 28, mean age 16.3 ± 0.1; non-selected, n = 38, mean age 16.7 ± 0.4) using objective instruments. Multivariate profiles were assessed through anthropometric characteristics, biological maturation, tactical-technical skills, and motor performance. The Student's t-test identified that selected players exhibited significantly higher values for height (t = 2.331, p = 0.02), lean body mass (t = 2.441, p = 0.01), and maturity offset (t = 4.559, p < 0.001), as well as performed better in declarative tactical knowledge (t = 10.484, p < 0.001), shooting (t = 2.188, p = 0.03), dribbling (t = 5.914, p < 0.001), speed - 30 m (t = 8.304, p < 0.001), countermovement jump (t = 2.718, p = 0.008), and peak power tests (t = 2.454, p = 0.01). Forward stepwise discriminant function analysis showed that declarative tactical knowledge, running speed -30 m, maturity offset, dribbling, height, and peak power correctly classified 97% of the selected players. These findings may have implications for a highly efficient selection process with objective measures of youth players in soccer clubs.
本研究确定了多变量概况是否比未入选的巴西精英青年足球运动员更有效地鉴别入选球员。使用客观仪器对66名青年足球运动员(入选者,n = 28,平均年龄16.3±0.1;未入选者,n = 38,平均年龄16.7±0.4)进行了此项检测。通过人体测量特征、生物成熟度、战术技术技能和运动表现评估多变量概况。学生t检验表明,入选球员在身高(t = 2.331,p = 0.02)、瘦体重(t = 2.441,p = 0.01)和成熟度偏移(t = 4.559,p < 0.001)方面表现出显著更高的值,并且在陈述性战术知识(t = 10.484,p < 0.001)、射门(t = 2.188,p = 0.03)、运球(t = 5.914,p < 0.001)、30米速度(t = 8.304,p < 0.001)、反向纵跳(t = 2.718,p = 0.008)和峰值功率测试(t = 2.454,p = 0.01)中表现更好。向前逐步判别函数分析表明,陈述性战术知识、30米跑步速度、成熟度偏移、运球、身高和峰值功率正确分类了97%的入选球员。这些发现可能对足球俱乐部中采用客观指标的高效青年球员选拔过程具有启示意义。