Laboratory of Applied Sport Physiology, School of Applied Sciences, University of Campinas, Limeira, SP, Brazil.
Department of ICT and Natural Sciences, Norwegian University of Science and Technology, Alesund, Norway.
Sci Rep. 2020 May 25;10(1):8620. doi: 10.1038/s41598-020-65420-3.
Besides technical and tactical aspects, basketball matches involve high aerobic and anaerobic capacities, conferring the final performance of a team. Thus, the evaluation of physical and technical responses is an effective way to predict the performance of athletes. Field and laboratory tests have been used in sports. The first involving high ecological validity and low cost, and the second, greater control and accuracy but not easy application, considering the different preparation phases in a season. This study aimed, through complex networks analysis, to verify whether centrality parameters analysed from significant correlations behave similarly in distinct scenarios (laboratory and on-court), emphasizing aerobic and anaerobic physical parameters and technical performances. The results showed that, in a compelling analysis involving basketball athletes, the studied centralities (degree, betweenness, eigenvector and pagerank) revealed similar responses in both scenarios, which is widely attractive considering the greater financial economy and lower time when applying tests in the field.
除了技术和战术方面，篮球比赛还涉及到高有氧和无氧能力，这决定了球队的最终表现。因此，评估身体和技术反应是预测运动员表现的有效方法。在运动中，已经使用了现场和实验室测试。前者涉及高生态有效性和低成本，后者具有更大的控制和准确性，但由于赛季中的不同准备阶段，应用起来并不容易。本研究旨在通过复杂网络分析，验证从显著相关性中分析得出的中心性参数在不同场景（实验室和场上）中是否表现相似，强调有氧和无氧物理参数以及技术表现。结果表明，在涉及篮球运动员的引人注目的分析中，所研究的中心性（度、介数、特征向量和Pagerank）在两种情况下都显示出相似的反应，这考虑到在现场应用测试时具有更大的经济节约和更低的时间成本，因此具有广泛的吸引力。
