ArticleScientific reports2020
Corresponding Assessment Scenarios in Laboratory and on-Court Tests: Centrality Measurements by Complex Networks Analysis in Young Basketball Players.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Complex networks analysis reinforces centrality hematological role on aerobic-anaerobic performances of the Brazilian Paralympic endurance team after altitude training.Scientific reports · 2022Trial
- Multivariate dynamic association analysis between sprint interval training and adolescent freestyle swimming performance.BMC sports science, medicine & rehabilitation · 2026Article
- Complex network model reveals the positive effect of melatonin on bone parameters in rats with induced hypoestrogenism.Bone & joint research · 2025Article
- Glycerophospholipids in Red Blood Cells Are Associated with Aerobic Performance in Young Swimmers.Nutrients · 2024Article
- Article
- Effects of different inspiratory muscle warm-up loads on mechanical, physiological and muscle oxygenation responses during high-intensity running and recovery.Scientific reports · 2022Article
- Article
- Comparison of parameters derived from a three-minute all-out test with classical benchmarks for running exercise.PloS one · 2022Article
- Associations among sleep, hematologic profile, and aerobic and anerobic capacity of young swimmers: A complex network approach.Frontiers in physiology · 2022Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
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