ArticleHealthcare (Basel, Switzerland)2022
Comparison of Measurements of External Load between Professional Soccer Players.
Article in Healthcare (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Assessment of Internal Load and External Load in Senior Football Players: Differences Between Competitive Levels.Journal of functional morphology and kinesiology · 2026Article
- The Influence of Competition Time on Soccer Players' Performance Factors: A Scoping Review with Evidence Gap Map.Sports medicine (Auckland, N.Z.) · 2026Article
- Non-contact injury incidence in professional women's football depends on the starting status of the player.Biology of sport · 2025Article
- Does elite European match-play affect salivary immunoglobulin-A and cortisol in soccer players? The influence of playing status and match outcome.Frontiers in physiology · 2024Article
- Load Monitoring and Its Relationship with Healthcare in Sports.Healthcare (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Background: The excessive and rapid increases in training load (TL) may be responsible for most non-contact injuries in soccer. This study’s aims were to describe, week(w)-by-week, the acute (AW), chronic (CW), acute:chronic workload ratio (wACWR), total distance (wTD), duration training (wDT), sprint total distance (wSTD), repeat sprint (wRS), and maximum speed (wMS) between starter and non-starter professional soccer players based on different periods (i.e., pre-, early-, mid-, and end-season) of a full-season (Persian Gulf Pro League, 2019−2020). Methods: Nineteen players were divided according to their starting status: starters (n = 10) or non-starters (n = 9). External workload was monitored for 43 weeks: pre- from w1−w4; early- from w5−w17; mid- from w18−w30, and end-season from w31−w43. Results: In starters, AW, CW, and wACWR were greater than non-starters (p < 0.05) throughout the periods of early- (CW, p ≤ 0.0001), mid- (AW, p = 0.008; CW, p ≤ 0.0001; wACWR, p = 0.043), or end-season (AW, p = 0.035; CW, p = 0.017; wACWR, p = 0.010). Starters had a greater wTD (p ≤ 0.0001), wSTD (p ≤ 0.0001 to 0.003), wDT (p ≤ 0.0001 to 0.023), wRS (p ≤ 0.0001 to 0.018), and wMS (p ≤ 0.0001) than non-starters during early-, mid-, and end-season. Conclusion: Starters experienced more CW and AW during the season than non-starters, which underlines the need to design tailored training programs accounting for the differences between playing status.
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