RESEARCH PAPER
Managing Training Load in the Lead-Up to Competition: Session-Rating of Perceived Exertion,
not the Acute-to-Chronic Workload Ratio,
Associated with the Performance of Elite Swimmers
1
Departamento de Deportes, Facultad de Ciencias de la Actividad Física y del Deporte (INEF), Universidad Politécnica de Madrid, Madrid, Spain.
2
Department of Statistics, University of Castilla-La Mancha, Toledo, Spain.
3
ports Training Laboratory, Faculty of Sports Sciences, University of Castilla-La Mancha, Toledo, Spain.
Submission date: 2025-10-05
Final revision date: 2026-01-10
Acceptance date: 2026-03-06
Publication date: 2026-04-02
Corresponding author
Santiago Veiga
Departamento de Deportes, Universidad Politécnica de Madrid, Madrid, Spain;, sports department, Spain
Departamento de Deportes, Universidad Politécnica de Madrid, Madrid, Spain;, sports department, Spain
Journal of Human Kinetics 2026;101:271-284
KEYWORDS
TOPICS
ABSTRACT
This study aimed to investigate the dynamic relationship between training loads and swimming performance among elite swimmers over a 40-week training period. Training data from seven international-level swimmers (4 men and 3 women) were collected during three macrocycles comprising one target competition each. The best personal times at the beginning of the cycle (MTp) were used to calculate the change in the swimmer's performance at the end of each macrocycle (MT1, MT2, and MT3). The training volume in the pool and the gym, as well as the session rating of perceived exertion (SRPE) were used to calculate the acute-to-chronic workload ratio (ACWR). Associations between training loads and performance change were analyzed using linear mixed models (LMMs), with the swimmer identity being included as a random intercept to account for repeated measures. The higher accumulated dry-land and swimming load during the final seven weeks preceding competition was negatively associated with performance (z_D_SRPEkg7: β = −20.3; z_W_SRPEkm7: β = −15.5), whereas ACWR-based models showed limited explanatory value. The findings of the study emphasize that monitoring the swimmer's SRPE in the lead-up to competition can be important for performance optimization.
REFERENCES (36)
1.
Agrebi, B., Dhahbi, W., Abidi, H., Kasmi, S., Houas, N., Chtara, M., and Chamari, K. (2024). Isokinetic peak torque improvement and shoulder muscle ratio imbalance correction after specific strength training on a new ballistic throwing device: A randomized controlled trial. Journal of Sport Rehabilitation, 33(6), 423–436. https://doi.org/10.1123/jsr.20....
2.
Allen, S. V., Vandenbogaerde, T. J., and Hopkins, W. G. (2014). Career performance trajectories of Olympic swimmers: Benchmarks for talent development. European Journal of Sport Science, 14(7), 643–651. https://doi.org/10.1080/174613....
3.
Borg, G., Hassmén, P., and Lagerström, M. (1987). Perceived exertion related to heart rate and blood lactate during arm and leg exercise. European Journal of Applied Physiology and Occupational Physiology, 56(6), 679–685. https://doi.org/10.1007/BF0042....
4.
Collette, R., Kellmann, M., Ferrauti, A., Meyer, T., and Pfeiffer, M. (2018). Relation between training load and recovery–stress state in high-performance swimming. Frontiers in Physiology, 9, 845. https://doi.org/10.3389/fphys.....
5.
Costa, M. J., Marinho, D. A., Reis, V. M., Silva, A. J., Marques, M. C., Bragada, J. A., and Barbosa, T. M. (2010). Tracking the performance of world-ranked swimmers. Journal of Sports Science & Medicine, 9(3), 411–417.
6.
De Andrade Nogueira, F. C., De Freitas, V. H., Miloski, B., De Oliveira Cordeiro, A. H., Werneck, F. Z., Nakamura, F. Y., and Bara-Filho, M. G. (2016). Relationship between training volume and ratings of perceived exertion in swimmers. Perceptual and Motor Skills, 122(1), 319–335. https://doi.org/10.1177/003151....
7.
Del Castillo, J. A., González-Ravé, J. M., Perona, F. H., Del Cerro, J. S., and Pyne, D. B. (2022). The importance of previous season performance on world-class 200- and 400-m individual medley swimming. Biology of Sport, 39(1), 45–51. https://doi.org/10.5114/biolsp....
8.
Dhahbi, W., Chaabene, H., Pyne, D. B., and Chamari, K. (2024a). Standardizing the quantification of external load across different training modalities: A critical need in sport science research. International Journal of Sports Physiology and Performance. 19(11), 1173–1175. https://doi.org/10.1123/ijspp.....
9.
Dhahbi, W., Materne, O., and Chamari, K. (2025). Rethinking knee injury prevention strategies: The joint-by-joint training approach paradigm versus traditional focused knee strengthening. Biology of Sport, 42(4), 59–65. https://doi.org/10.5114/biolsp....
10.
Dhahbi, W., Padulo, J., Russo, L., Racil, G., Ltifi, M.-A., Picerno, P., Iuliano, E., and Migliaccio, G. M. (2024b). Four- to six-repetition maximum and one-repetition maximum prediction in free-weight bench press and Smith machine squat based on body mass in male athletes. Journal of Strength and Conditioning Research, 38(8), 1366–1371. https://doi.org/10.1519/JSC.00....
11.
Foster, C., Florhaug, J. A., Franklin, J., Gottschall, L., Hrovatin, L. A., Parker, S., Doleshal, P., and Dodge, C. (2001). A new approach to monitoring exercise training. Journal of Strength and Conditioning Research, 15(1), 109–115. https://doi.org/10.1519/1533-4....
12.
Gabbett, T. J. (2016). The training–injury prevention paradox: Should athletes be training smarter and harder? British Journal of Sports Medicine, 50(5), 273–280. https://doi.org/10.1136/bjspor....
13.
Gabbett, T. J., and Whiteley, R. (2017). Two training-load paradoxes: Can we work harder and smarter, and can physical preparation and medicine be teammates? International Journal of Sports Physiology and Performance, 12(Suppl. 2), S2–S54. https://doi.org/10.1123/ijspp.....
14.
García-Ramos, A., Feriche, B., Calderón, C., Iglesias, X., Barrero, A., Chaverri, D., Schuller, T., and Rodríguez, F. A. (2014). Training load quantification in elite swimmers using a modified version of the training impulse method. European Journal of Sport Science, 15(2), 85–93. https://doi.org/10.1080/174613....
15.
González-Boto, R., Salguero, A., Tuero, C., González-Gallego, J., and Márquez, S. (2008). Monitorización de los efectos de cambios en la carga de entrenamiento sobre el estrés y la recuperación en nadadores. Journal of Physiology and Biochemistry, 64(1), 19–26. https://doi.org/10.1007/BF0316....
16.
Hellard, P., Avalos, M., Hausswirth, C., Pyne, D., Toussaint, J.-F., and Mujika, I. (2013). Identifying optimal overload and taper in elite swimmers over time. Journal of Sports Science & Medicine, 12(4), 668–678.
17.
Hellard, P., Avalos-Fernandes, M., Lefort, G., Pla, R., Mujika, I., Toussaint, J.-F., and Pyne, D. B. (2019). Elite swimmers' training patterns in the 25 weeks prior to their season's best performances: Insights into periodization from a 20-year cohort. Frontiers in Physiology, 10, 363. https://doi.org/10.3389/fphys.....
18.
Hulin, B. T., Gabbett, T. J., Blanch, P., Chapman, P., Bailey, D., and Orchard, J. (2013). Spikes in acute workload are associated with increased injury risk in elite cricket fast bowlers. British Journal of Sports Medicine, 48(8), 708–712. https://doi.org/10.1136/bjspor....
19.
Hurwitz, J., Rich, D., Agnew, C., and Harry, J. (2022). Workload management strategies to optimize athlete performance in collegiate men's and women's basketball. International Journal of Strength and Conditioning, 2(1), 136. https://doi.org/10.47206/ijsc.....
20.
Impellizzeri, F. M., Rampinini, E., and Marcora, S. M. (2005). Physiological assessment of aerobic training in soccer. Journal of Sports Sciences, 23(6), 583–592. https://doi.org/10.1080/026404....
21.
Jones, C. M., Griffiths, P. C., and Mellalieu, S. D. (2016). Training load and fatigue marker associations with injury and illness: A systematic review of longitudinal studies. Sports Medicine, 47(5), 943–974. https://doi.org/10.1007/s40279....
22.
Lopes, T. J., Neiva, H. P., Gonçalves, C. A., Nunes, C., and Marinho, D. A. (2020). The effects of dry-land strength training on competitive sprinter swimmers. Journal of Exercise Science & Fitness, 19(1), 32–39. https://doi.org/10.1016/j.jesf....
23.
MacMillan, G. C. S., Batterham, A. M., Chesterton, P., Gregson, W., Lolli, L., Weston, M., and Atkinson, G. (2020). Variability in the study quality appraisals reported in systematic reviews on the acute-to-chronic workload ratio and injury risk. Sports Medicine, 50(11), 2065–2067. https://doi.org/10.1007/s40279....
24.
McKay, A. K. A., Stellingwerff, T., Smith, E. S., Martin, D. T., Mujika, I., Goosey-Tolfrey, V. L., Sheppard, J. M., and Burke, L. M. (2022). Defining training and performance caliber: A participant classification framework. International Journal of Sports Physiology and Performance, 17(2), 317–331. https://doi.org/10.1123/ijspp.....
25.
Mujika, I. (2017). Quantification of training and competition loads in endurance sports: Methods and applications. International Journal of Sports Physiology and Performance, 12(Suppl. 2), S2–S17. https://doi.org/10.1123/ijspp.....
26.
Mujika, I., and Padilla, S. (2003). Scientific bases for pre competition tapering strategies. Medicine & Science in Sports & Exercise, 35(7), 1182–1187. https://doi.org/10.1249/01.MSS....
27.
Mujika, I., Padilla, S., and Pyne, D. (2002). Swimming performance changes during the final three weeks of training leading to the Sydney 2000 Olympic Games. International Journal of Sports Medicine, 23(8), 582–587. https://doi.org/10.1055/s-2002....
28.
Murray, N. B., Gabbett, T. J., Townshend, A. D., and Blanch, P. (2016). Calculating acute-to-chronic workload ratios using exponentially weighted moving averages provides a more sensitive indicator of injury likelihood than rolling averages. British Journal of Sports Medicine, 51(9), 749–754. https://doi.org/10.1136/bjspor....
29.
Myers, N. L., Morrow, R., and Farnsworth, J. L. (2021). Modelling the relationship between relative load and match outcome in junior tennis players. Journal of Human Sport and Exercise, 17(4), 740–749. https://doi.org/10.14198/jhse.....
30.
Nugent, F. J., Comyns, T. M., Burrows, E., and Warrington, G. D. (2017). Effects of low-volume, high-intensity training on performance in competitive swimmers: A systematic review. Journal of Strength and Conditioning Research, 31(3), 837–847. https://doi.org/10.1519/JSC.00....
31.
Psycharakis, S. G. (2011). A longitudinal analysis on the validity and reliability of ratings of perceived exertion for elite swimmers. Journal of Strength and Conditioning Research, 25(2), 420–426. https://doi.org/10.1519/JSC.0b....
32.
Seiler, S. (2010). What is best practice for training intensity and duration distribution in endurance athletes? International Journal of Sports Physiology and Performance, 5(3), 276–291. https://doi.org/10.1123/ijspp.....
33.
Sein, M. L., Walton, J., Linklater, J., Appleyard, R., Kirkbride, B., Kuah, D., and Murrell, G. A. C. (2008). Shoulder pain in elite swimmers: primarily due to swim-volume-induced supraspinatus tendinopathy. British Journal of Sports Medicine, 44(2), 105–113. https://doi.org/10.1136/bjsm.2....
34.
Souaifi, M., Dhahbi, W., Jebabli, N., Ceylan, H. İ., Boujabli, M., Muntean, R. I., and Dergaa, I. (2025). Artificial intelligence in sports biomechanics: A scoping review on wearable technology, motion analysis, and injury prevention. Bioengineering, 12(8), 887. https://doi.org/10.3390/bioeng....
35.
Wallace, L. K., Slattery, K. M., and Coutts, A. J. (2009). The ecological validity and application of the session-RPE method for quantifying training loads in swimming. Journal of Strength and Conditioning Research, 23(1), 33–38. https://doi.org/10.1519/JSC.0b....
36.
Wirth, K., Keiner, M., Fuhrmann, S., Nimmerichter, A., and Haff, G. G. (2022). Strength training in swimming. International Journal of Environmental Research and Public Health, 19(9), 5369. https://doi.org/10.3390/ijerph....
Share
RELATED ARTICLE
| eISSN: | 1899-7562 |
| ISSN: | 1640-5544 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
