How weekly monitoring variables influence players' and teams' match performance in elite futsal players

• Main Authors: João Nuno Ribeiro (Author), Diogo Monteiro (Author), Jaime Sampaio (Author), Micael Couceiro (Author), Bruno Travassos (Author)
• Format: Book
• Published: Termedia Publishing House, 2022-01-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 0860-021X; 2083-1862; 10.5114/biolsport.2023.112091
• Keywords: monitoring system; weekly training load; readiness; match outcome; Sports medicine; RC1200-1245; Biology (General); QH301-705.5
• Source: Biology of Sport, Vol 40, Iss 1, Pp 77-83 (2022)

This study aimed to investigate how weekly training load constrains the performance of players and teams in official futsal competitions. Data from a professional male team were collected during two seasons (46 weeks). The applied monitoring system analysed the training load (as measured by session perceived exertion, sRPE), the total recovery status (TQR), the well-being score (WBs) and the variability of neuromuscular performance during each week (CMJ-cv). In addition, the performance was assessed for all the matches. A path analysis model was performed to test the associations across variables. Results from the path analysis model revealed that it explains 31% of the teams' performance. In general, the results show that previous team performance has no significant effects on the training week. A significant negative relationship was found between CMJ-cv and match performance (β = -.34; CI95% -.359 to -.070), as well as a significant negative relationship between players' match performance and the team's match performance (β = -.55; CI95% -.292 to .740). Regarding indirect effects, only a negative association between CMJ-cv and team match performance via players' match performance (β = -.19; CI95% -.342 to -.049) was identified. The small variation of the weekly CMJ (CMJ-cv) seems to be a key variable to monitor and explain both player and team performance. Based on this model, and only looking at the physical variables, it was possible to explain 31% of the team's performance. Longitudinal and multi-team studies should be conducted to integrate other technical, tactical and psychological variables that allow the level of understanding of players' and teams' performance to be improved.