ArticleBMC sports science, medicine & rehabilitation2022
Within-week differences in external training load demands in elite volleyball players.
Article in BMC sports science, medicine & rehabilitation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Machine Learning and Non-Invasive Monitoring Technologies for Training Load Management in Women's Volleyball: A Scoping Review.Sports (Basel, Switzerland) · 2026Review
- Optimizing position-specific preparation: Long-term pre-match warm-up external load analysis using micro-sensor integrated LPS in elite female volleyball players.BMC sports science, medicine & rehabilitation · 2025Article
- External Load Variability in Elite Futsal: Positional Demands and Microcycle Structuring for Player Well-Being and Performance.Sports (Basel, Switzerland) · 2025Article
- Enhancing Sports Injury Risk Assessment in Soccer Through Machine Learning and Training Load Analysis.Journal of sports science & medicine · 2024Article
- Quantifying internal and external training loads in collegiate male volleyball players during a competitive season.BMC sports science, medicine & rehabilitation · 2024Article
- Comparing Two Methods of Acute: Chronic Workload Calculations in Girls' Youth Volleyball.Sports (Basel, Switzerland) · 2023Article
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe aim of this study was to analyze the within-week differences in external training intensity in different microcycles considering different playing positions in women elite volleyball players.
methodsThe training and match data were collected during the 2020-2021 season, which included 10 friendly matches, 41 league matches and 11 champions league matches. The players' position, training/match duration, training/match load, local positioning system (LPS) total distance, LPS jumps, accelerations, decelerations, high metabolic load distance (HMLD), acute and chronic (AC) mean and AC ratio calculated with the rolling average (RA) method and the exponentially weighted moving average (EWMA) method, monotony and strain values were analyzed.
resultsAll the variables except strain, Acc/Dec ratio and acute mean (RA) showed significant differences among distance to match days. Regarding the players' positions, the only difference was found in the AC ratio (EWMA); in all microcycles, the middle blocker player showed workload values when compared with the left hitter, setter and libero.
conclusionOverall, the analysis revealed that the intensity of all performance indicators, except for strain, acc/dec and acute mean load (RA), showed significant differences among distance to match day with moderate to large effect sizes. When comparing players' positions, the middle blocker accumulated the lowest loads. There were no significant differences among other positions.
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