PURPOSE: To investigate the existence of faster vs slower recovery profiles in futsal and factors distinguishing them. METHODS: 22 male futsal players were evaluated in countermovement jump, 10-m sprint, creatine kinase, total quality of recovery (TQR), and Brunel Mood Scale (fatigue and vigor) before and immediately and 3, 24, and 48 h posttraining. Hierarchical cluster analysis allocated players to different recovery profiles using the area under the curve (AUC) of the percentage differences from baseline. One-way ANOVA compared the time course of each variable and players' characteristics between clusters. RESULTS: Three clusters were identified and labeled faster recovery (FR), slower physiological recovery (SLphy), and slower perceptual recovery (SLperc). FR presented better AUC in 10-m sprint than SLphy (P = .001) and SLperc (P = .008), as well as better TQR SLphy (P = .018) and SLperc (P = .026). SLperc showed better AUC in countermovement jump than SLphy (P = .014) but presented worse fatigue AUC than SLphy (P = .014) and FR (P = .008). AUC of creatine kinase was worse in SLphy than in FR (P = .001) and SLperc (P < .001). The SLphy players were younger than SLperc players (P = .027), whereas FR were slower 10-m sprinters than SLphy players (P = .003) and SLperc (P = .013) and tended to have higher maximal oxygen consumption than SLphy (effect size =1.13). CONCLUSION: Different posttraining recovery profiles exist in futsal players, possibly influenced by their physical abilities and age/experience.
PURPOSE: To investigate the existence of faster vs slower recovery profiles in futsal and factors distinguishing them. METHODS: 22 male futsal players were evaluated in countermovement jump, 10-m sprint, creatine kinase, total quality of recovery (TQR), and Brunel Mood Scale (fatigue and vigor) before and immediately and 3, 24, and 48 h posttraining. Hierarchical cluster analysis allocated players to different recovery profiles using the area under the curve (AUC) of the percentage differences from baseline. One-way ANOVA compared the time course of each variable and players' characteristics between clusters. RESULTS: Three clusters were identified and labeled faster recovery (FR), slower physiological recovery (SLphy), and slower perceptual recovery (SLperc). FR presented better AUC in 10-m sprint than SLphy (P = .001) and SLperc (P = .008), as well as better TQR SLphy (P = .018) and SLperc (P = .026). SLperc showed better AUC in countermovement jump than SLphy (P = .014) but presented worse fatigue AUC than SLphy (P = .014) and FR (P = .008). AUC of creatine kinase was worse in SLphy than in FR (P = .001) and SLperc (P < .001). The SLphy players were younger than SLperc players (P = .027), whereas FR were slower 10-m sprinters than SLphy players (P = .003) and SLperc (P = .013) and tended to have higher maximal oxygen consumption than SLphy (effect size =1.13). CONCLUSION: Different posttraining recovery profiles exist in futsal players, possibly influenced by their physical abilities and age/experience.
Entities:
Keywords:
classification analysis; cluster analysis; performance; team sport
Authors: Luca Paolo Ardigò; Stefano Palermi; Johnny Padulo; Wissem Dhahbi; Luca Russo; Simone Linetti; Drazen Cular; Mario Tomljanovic Journal: Front Sports Act Living Date: 2020-07-14