Biology of Sport
eISSN: 2083-1862
ISSN: 0860-021X
Biology of Sport
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SCImago Journal & Country Rank
1/2023
vol. 40
 
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abstract:
Original paper

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

João Nuno Ribeiro
1, 2
,
Diogo Monteiro
2, 3
,
Jaime Sampaio
2, 4
,
Micael Couceiro
4, 5
,
Bruno Travassos
1, 2, 6

1.
Department of Sport Sciences, University of Beira Interior, Covilhã, Portugal
2.
Research Centre in Sport Sciences, Health Sciences and Human Development, CIDESD, Vila Real Portugal
3.
ESECS, Polytechnic of Leiria, Leiria, Portugal
4.
University of Trás-os-Montes and Alto Douro, Vila Real, Portugal
5.
Ingeniarius, Lda., Alfena, Portugal
6.
Portugal Football School, Portuguese Football Federation, Oeiras, Portugal
Biol Sport. 2023;40(1):77–83.
Online publish date: 2022/01/03
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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.
keywords:

Monitoring system, Weekly training load, Readiness, Match outcome

 
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