Article Data

  • Views 474
  • Dowloads 132

Original Research

Open Access Special Issue

Within- and between-mesocycle variations of well-being measures in top elite male soccer players: a longitudinal study

  • Rafael Oliveira1,2,3,*,
  • Halil İbrahim Ceylan4
  • João Paulo Brito1,2,3
  • Alexandre Martins1,2,5
  • Matilde Nalha1
  • Bruno Mendes6
  • Filipe Manuel Clemente7,8

1Sports Science School of Rio Maior–Polytechnic Institute of Santarém, 2040-413 Rio Maior, Portugal

2Life Quality Research Centre, 2040-413 Rio Maior, Portugal

3Research Center in Sport Sciences, Health Sciences and Human Development, 5001-801 Vila Real, Portugal

4Ataturk University, Faculty of Kazim Karabekir Education, Physical Education and Sports Teaching Department, 25240 Erzurum, Turkey

5Comprehensive Health Research Centre (CHRC), Departamento de Desporto e Saúde, Escola de Saúde e Desenvolvimento Humano, Universidade de Évora, Largo dos Colegiais, 7000 Évora, Portugal

6Faculty of Human Kinetics, University of Lisbon, 1649-004 Lisbon, Portugal

7Escola Superior Desporto e Lazer, Instituto Politécnico de Viana do Castelo, Rua Escola Industrial e Comercial de Nun’Álvares, 4900-347 Viana do Castelo, Portugal

8Instituto de Telecomunicações, Delegação da Covilhã, 1049-001 Lisboa, Portugal

DOI: 10.31083/j.jomh1804094 Vol.18,Issue 4,April 2022 pp.1-14

Submitted: 14 December 2021 Accepted: 17 January 2022

Published: 30 April 2022

(This article belongs to the Special Issue Functional and health development approaches in male athletes)

*Corresponding Author(s): Rafael Oliveira E-mail:


Background: The aims of this study were to describe the variations of training monotony (TM), training strain (TS), and acute:chronic workload ratio (ACWR) through Hooper Index categories (fatigue, stress, DOMS, and sleep quality) and to compare those variations between player status and player positions. Methods: Seventeen male professional soccer players participated in this study. Considering player status, participants were divided in nine starters and eight non-starters. Additionally, participants were divided by playing positions: three wide defenders, four central defenders, three wide midfielders, four central midfielders, and three strikers. They were followed during 40-week in-season period. TM, TS, and ACWR were calculated for each HI category, respectively. Data were grouped in 10 mesocycles for further analysis. Results: Results showed variations across the mesocycles. In general, starters showed higher values for TM, TS, and ACWR calculations than non-starters, although there were some exceptions. Regarding player positions, significant differences were found in stress between wide defenders vs central midfielders for TM (p = 0.033, ES = 5.16), central defenders vs wide defenders for ACWR (p = 0.044, ES = 4.95), and in sleep between wide defenders and strikers for TM (p = 0.015, ES = 5.80). Conclusions: This study revealed that an analysis of players’ well-being parameters according to player status and positions can provide clear information to the coaches and their staff to complement the tasks of training monitoring.


ACWR; fatigue; football; muscle soreness; training monotony; training strain; sleep; stress

Cite and Share

Rafael Oliveira,Halil İbrahim Ceylan,João Paulo Brito,Alexandre Martins,Matilde Nalha,Bruno Mendes,Filipe Manuel Clemente. Within- and between-mesocycle variations of well-being measures in top elite male soccer players: a longitudinal study. Journal of Men's Health. 2022. 18(4);1-14.


[1] Gabbett TJ, Nassis GP, Oetter E, Pretorius J, Johnston N, Med-ina D, et al. The athlete monitoring cycle: a practical guide to interpreting and applying training monitoring data. British Jour-nal of Sports Medicine. 2017; 51: 1451–1452.

[2] Brink MS, Visscher C, Arends S, Zwerver J, Post WJ, Lemmink KA. Monitoring stress and recovery: new insights for the pre-vention of injuries and illnesses in elite youth soccer players. British Journal of Sports Medicine. 2010; 44: 809–815.

[3] Miguel M, Oliveira R, Loureiro N, García-Rubio J, Ibáñez SJ. Load Measures in Training/Match Monitoring in Soccer: A Systematic Review. International Journal of Environmental Re-search and Public Health. 2021; 18: 2721.

[4] Staunton CA, Abt G, Weaving D, Wundersitz DWT. Misuse of the term ‘load’ in sport and exercise science. Journal of Science and Medicine in Sport. 2021. (in press)

[5] Borresen J, Ian Lambert M. The Quantification of Training Load, the Training Response and the Effect on Performance. Sports Medicine. 2009; 39: 779–795.

[6] Mujika I. Quantification of Training and Competition Loads in Endurance Sports: Methods and Applications. International Journal of Sports Physiology and Performance. 2017; 12: S2–17.

[7] Weaving D, Jones B, Marshall P, Till K, Abt G. Multiple Mea-sures are Needed to Quantify Training Loads in Professional Rugby League. International Journal of Sports Medicine. 2017; 38: 735–740.

[8] Borges TO, Moreira A, Thiengo CR, Medrado RGSD, Titton A, Lima MR, et al. Training intensity distribution of young elite soccer players. Revista Brasileira de Cineantropometria & De-sempenho. 2019; 21: 1–11. (In Português)

[9] Foster C. Monitoring training in athletes with reference to over-training syndrome. Medicine & Science in Sports & Exercise. 1998; 30: 1164–1168.

[10] Haddad M, Stylianides G, Djaoui L, Dellal A, Chamari K. Session-RPE Method for Training Load Monitoring: Validity, Ecological Usefulness, and Influencing Factors. Frontiers in Neuroscience. 2017; 11: 612.

[11] Rabbani A, Kargarfard M, Twist C. Fitness Monitoring in Elite Soccer Players: Group vs. Individual Analyses. Journal of Strength and Conditioning Research. 2020; 34: 3250–3257.

[12] Giles S, Fletcher D, Arnold R, Ashfield A, Harrison J. Measur-ing well-being in Sport Performers: where are we now and how do we Progress? Sports Medicine. 2020; 50: 1255–1270.

[13] Duignan C, Doherty C, Caulfield B, Blake C. Single-Item Self-Report Measures of Team-Sport Athlete Wellbeing and their Re-lationship with Training Load: a Systematic Review. Journal of Athletic Training. 2020; 55: 944–953.

[14] Hooper SL, Mackinnon LT. Monitoring Overtraining in Ath-letes. Sports Medicine. 1995; 20: 321–327.

[15] Rabbani A, Clemente FM, Kargarfard M, Chamari K. Match Fa-tigue Time-Course Assessment Over Four Days: Usefulness of the Hooper Index and Heart Rate Variability in Professional Soc-cer Players. Frontiers in Physiology. 2019; 10: 109.

[16] Nobari H, Aquino R, Clemente FM, Khalafi M, Adsuar JC, Pérez-Gómez J. Description of acute and chronic load, train-ing monotony and strain over a season and its relationships with well-being status: a study in elite under-16 soccer players. Phys-iology & Behavior. 2020; 225: 113117.

[17] Windt J, Gabbett TJ, Ferris D, Khan KM. Training load–injury paradox: is greater preseason participation associated with lower in-season injury risk in elite rugby league players? British Journal of Sports Medicine. 2017; 51: 645–650.

[18] Nobari H, Fani M, Pardos-Mainer E, Pérez-Gómez J. Fluctu-ations in Well-Being Based on Position in Elite Young Soccer Players during a Full Season. Healthcare. 2021; 9: 586.

[19] Clemente FM, Silva R, Castillo D, Los Arcos A, Mendes B, Afonso J. Weekly Load Variations of Distance-Based Variables in Professional Soccer Players: A Full-Season Study. Interna-tional Journal of Environmental Research and Public Health. 2020; 17: 3300.

[20] Oliveira R, Martins A, Nobari H, Nalha M, Mendes B, Clemente FM, et al. In-season monotony, strain and acutechronic work-load of perceived exertion, global positioning system running based variables between player positions of a top elite soccer team. BMC Sports Science, Medicine and Rehabilitation. 2021; 13: 126.

[21] Oliveira R, Palucci Vieira LH, Martins A, Brito JP, Nalha M, Mendes B, Clemente FM. In-Season Internal and External Workload Variations between Starters and Non-Starters-A Case Study of a Top Elite European Soccer Team. Medicina. 2021; 57: 1–15.

[22] Hader K, Rumpf MC, Hertzog M, Kilduff LP, Girard O, Silva JR. Monitoring the Athlete Match Response: can External Load Variables Predict Post-match Acute and Residual Fatigue in Soc-cer? A Systematic Review with Meta-analysis. Sports Medicine

- Open. 2019; 5: 48.

[23] Clemente FM, Martinho R, Calvete F, Mendes B. Training load and well-being status variations of elite futsal players across a full season: Comparisons between normal and congested weeks. Physiology & Behavior. 2019; 201: 123–129.

[24] Nobari H, Fani M, Clemente FM, Carlos-Vivas J, Pérez-Gómez J, Ardigò LP. Intra- and Inter-week Variations of Well-Being Across a Season: A Cohort Study in Elite Youth Male Soccer Players. Frontiers in Psychology. 2021; 12: 671072.

[25] Fessi MS, Nouira S, Dellal A, Owen A, Elloumi M, Moalla W. Changes of the psychophysical state and feeling of wellness of professional soccer players during pre-season and in-season pe-riods. Research in Sports Medicine. 2016; 24: 375–386.

[26] Dalen T, Lorås H. Monitoring Training and Match Physical Load in Junior Soccer Players: Starters versus Substitutes. Sports. 2019; 7: 70.

[27] Nobari H, Oliveira R, Clemente FM, Adsuar JC, Pérez-Gómez J, Carlos-Vivas J, et al. Comparisons of accelerometer variables training monotony and strain of starters and non-starters: A full-season study in professional soccer players. International Jour-nal of Environmental Research and Public Health. 2020; 17: 1–14.

[28] Clemente FM, Mendes B, Nikolaidis PT, Calvete F, Carriço S, Owen AL. Internal training load and its longitudinal relation-ship with seasonal player wellness in elite professional soccer. Physiology & Behavior. 2017; 179: 262–267.

[29] Clemente F, Silva R, Ramirez-Campillo R, Afonso J, Mendes B, Chen Y. Accelerometry-based variables in professional soccer players: Comparisons between periods of the season and playing positions. Biology of Sport. 2020; 37: 389–403.

[30] Hasan UC, Silva R, Clemente F. Weekly variations of biome-chanical load variables in professional soccer players: compar-isons between playing positions. Human Movement. 2021; 22: 19–34.

[31] Oliveira R, Brito JP, Martins A, Mendes B, Marinho DA, Ferraz R, et al. In-season internal and external training load quantifi-cation of an elite European soccer team. PLoS ONE. 2019; 14: 0209393.

[32] Nobari H, Praça GM, Clemente FM, Pérez-Gómez J, Car-los Vivas J, Ahmadi M. Comparisons of new body load and metabolic power average workload indices between starters and non-starters: a full-season study in professional soccer players. Proceedings of the Institution of Mechanical Engineers, Part P. 2020; 235: 105–113.

[33] Nobari H, Castillo D, Clemente FM, Carlos-Vivas J, Pérez-Gómez J. Acute, chronic and acute/chronic ratio between starters and non-starters professional soccer players across a competitive season. Proceedings of the Institution of Mechanical Engineers, Part P. 2021.

[34] Foster C, Florhaug Ja, Franklin J, Gottschall L, Hrovatin La, Parker S, et al. A New Approach to Monitoring Exercise Train-ing. the Journal of Strength and Conditioning Research. 2001; 15: 109.

[35] Foster C, Hector LL, Welsh R, Schrager M, Green MA, Snyder AC. Effects of specific versus cross-training on running perfor-mance. European Journal of Applied Physiology and Occupa-tional Physiology. 1995; 70: 367–372.

[36] Impellizzeri FM, Marcora SM, Coutts AJ. Internal and Exter-nal Training Load: 15 Years on. International Journal of Sports Physiology and Performance. 2019; 14: 270–273.

[37] Dalen-Lorentsen T, Bjørneboe J, Clarsen B, Vagle M, Fager-land MW, Andersen TE. Does load management using the acute:chronic workload ratio prevent health problems? a clus-ter randomised trial of 482 elite youth footballers of both sexes. British Journal of Sports Medicine. 2021; 55: 108–114.

[38] Myers NL, Aguilar KV, Mexicano G, Farnsworth JL, Knudson D, Kibler WB. The Acute:Chronic Workload Ratio is Associ-ated with Injury in Junior Tennis Players. Medicine & Science in Sports & Exercise. 2020; 52: 1196–1200.

[39] Hopkins Wg, Marshall Sw, Batterham Am, Hanin J. Progressive Statistics for Studies in Sports Medicine and Exercise Science. Medicine & Science in Sports & Exercise. 2009; 41: 3–12.

[40] Faul F, Erdfelder E, Lang A, Buchner A. G*Power 3: a flexi-ble statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods. 2007; 39: 175–191.

[41] Haddad M, Chaouachi A, Wong DP, Castagna C, Hambli M, Hue O, et al. Influence of fatigue, stress, muscle soreness and sleep on perceived exertion during submaximal effort. Physiology & Behavior. 2013; 119: 185–189.

[42] Ferreira M, Camões M, Lima RF, Silva R, de Oliveira Castro H, Mendes B, et al. Variations of workload and well-being mea-sures across a professional basketball season. Revista Brasileira de Cineantropometria & Desempenho. 2021; 23.

[43] Anderson L, Orme P, Michele RD, Close GL, Milsom J, Mor-gans R, et al. Quantification of Seasonal-Long Physical Load in Soccer Players with Different Starting Status from the English Premier League: Implications for Maintaining Squad Physical Fitness. International Journal of Sports Physiology and Perfor-mance. 2016; 11: 1038–1046.

[44] Vilamitjana J, Vaccari JC, Toedtli M, Navone D, Rodriguez-Buteler JM, Verde PE, et al. Monitoring biochemical markers in professional soccer players during the season and preseason preparation phase. Revista Internacional de Ciencias del De-porte. 2017; 13: 211–224. (In Spanish)

[45] Impellizzeri FM, Ward P, Coutts AJ, Bornn L, McCall A. Training Load and Injury Part 1: the Devil is in the Detail—Challenges to Applying the Current Research in the Training Load and Injury Field. Journal of Orthopaedic & Sports Phys-ical Therapy. 2020; 50: 574–576.

[46] Impellizzeri FM, Ward P, Coutts AJ, Bornn L, McCall A. Train-ing Load and Injury Part 2: Questionable Research Practices Hi-jack the Truth and Mislead well-Intentioned Clinicians. Journal of Orthopaedic & Sports Physical Therapy. 2020; 50: 577–584.

[47] Enright K, Green M, Hay G, Malone JJ. Workload and Injury in Professional Soccer Players: Role of Injury Tissue Type and Injury Severity. International Journal of Sports Medicine. 2020; 41: 89–97.

Abstracted / indexed in

Science Citation Index Expanded (SciSearch) Created as SCI in 1964, Science Citation Index Expanded now indexes over 9,200 of the world’s most impactful journals across 178 scientific disciplines. More than 53 million records and 1.18 billion cited references date back from 1900 to present.

Journal Citation Reports/Science Edition Journal Citation Reports/Science Edition aims to evaluate a journal’s value from multiple perspectives including the journal impact factor, descriptive data about a journal’s open access content as well as contributing authors, and provide readers a transparent and publisher-neutral data & statistics information about the journal.

Directory of Open Access Journals (DOAJ) DOAJ is a unique and extensive index of diverse open access journals from around the world, driven by a growing community, committed to ensuring quality content is freely available online for everyone.

SCImago The SCImago Journal & Country Rank is a publicly available portal that includes the journals and country scientific indicators developed from the information contained in the Scopus® database (Elsevier B.V.)

Publication Forum - JUFO (Federation of Finnish Learned Societies) Publication Forum is a classification of publication channels created by the Finnish scientific community to support the quality assessment of academic research.

Scopus: CiteScore 0.7 (2022) Scopus is Elsevier's abstract and citation database launched in 2004. Scopus covers nearly 36,377 titles (22,794 active titles and 13,583 Inactive titles) from approximately 11,678 publishers, of which 34,346 are peer-reviewed journals in top-level subject fields: life sciences, social sciences, physical sciences and health sciences.

Norwegian Register for Scientific Journals, Series and Publishers Search for publication channels (journals, series and publishers) in the Norwegian Register for Scientific Journals, Series and Publishers to see if they are considered as scientific. (

Submission Turnaround Time