Optimizing Performance: The Dynamics of Health and Exertion in Professional Football

Year 2024, Issue: 24, 1140 - 1149, 30.12.2024

Çağlar Soylu , Zeki Akyıldız , Emre Altundağ

https://doi.org/10.38079/igusabder.1555100

Abstract

Aim: This study aims to comprehensively examine health and Rating of Perceived Exertion (RPE) parameters in professional football players on match days. The research seeks to identify the relationships between these two crucial variables, offering practical guidance to enhance sports science and coaching practices and ultimately improve player performance.
Method: The study was conducted on 21 professional football players who participated in 35 league matches during the 2022-2023 season. The participants had an average age of 26.37 years, an average height of 182.52 cm, and an average weight of 74.14 kg, with 11 being foreign players and 10 being Turkish. The relationships between internal load (RPE) and variables such as sleep quality, fatigue perception, and muscle soreness (DOMS) were analyzed using a correlational research design.
Results: According to the results of the Spearman correlation analysis, no significant correlation was found between health measures and RPE parameters.
Conclusion: The absence of statistically significant relationships in the findings highlights the complexity of accurately capturing the interaction between wellness and RPE parameters. This result underscores the need for further research to explore whether alternative or supplementary methods might provide more nuanced insights. Sports scientists and coaches should remain cautious when adjusting training loads, recognizing the potential limitations of relying solely on RPE methods. Future studies could analyze the RPE and health data collected during different periods of the season from a long-term perspective, providing a clearer understanding of the changes between athletic performance and wellness.

Keywords

Soccer, wellness, rating of perceived exertion, training load, internal load

Performansı Optimize Etme: Profesyonel Futbolda Sağlık ve Eforun Dinamikleri

Abstract

Amaç: Bu çalışma, profesyonel futbolcularda maç günlerindeki sağlık ve Algılanan Zorluk Derecesi (RPE) parametrelerini kapsamlı bir şekilde incelemeyi amaçlamaktadır. Araştırma, bu iki önemli değişken arasındaki ilişkileri belirlemeyi hedefleyerek, spor bilimi ve antrenörlük uygulamalarını geliştirmek ve nihayetinde oyuncu performansını artırmak için pratik rehberlik sunmaktadır.
Yöntem: Çalışma, 2022-2023 sezonunda 35 lig maçında forma giyen 21 profesyonel futbolcu üzerinde gerçekleştirilmiştir. Katılımcıların yaş ortalaması 26,37 yıl, boy ortalaması 182,52 cm ve kilo ortalaması 74,14 kg olup, 11’i yabancı, 10’u ise Türk oyunculardan oluşmaktadır. Araştırmada, iç yük (RPE) ile uyku kalitesi, yorgunluk algısı ve kas ağrısı (DOMS) arasındaki ilişkiler korelasyonel bir araştırma tasarımı kullanılarak analiz edilmiştir.
Bulgular: Spearman korelasyon analizi sonuçlarına göre, sağlık değerleri ile RPE parametreleri arasında istatistiksel olarak anlamlı bir ilişki bulunamamıştır.
Sonuç: Sonuçlarda istatistiksel olarak anlamlı ilişkilerin bulunmaması, wellness ve RPE parametreleri arasındaki etkileşimin doğru bir şekilde yakalanmasının zorluğunu vurgulamaktadır. Bu durum, alternatif veya tamamlayıcı yöntemlerin daha ayrıntılı içgörüler sağlayıp sağlayamayacağını araştırmak için daha fazla çalışmaya ihtiyaç olduğunu ortaya koymaktadır. Antrenörler ve spor bilimciler, antrenman yüklerini düzenlerken yalnızca RPE yöntemine güvenmenin potansiyel sınırlamalarını göz önünde bulundurmalı ve dikkatli olmalıdır. Gelecekteki çalışmalar, sezonun farklı dönemlerinde toplanan RPE ve sağlık verilerini uzun vadeli bir perspektifle analiz ederek, atletik performans ve welness hali arasındaki değişimleri daha net bir şekilde ortaya koyabilir.

Keywords

Futbol, wellnes, algılanan zorluk derecesi, antrenman yükü, iç yük

References

• 1. Thorpe RT, Strudwick AJ, Buchheit M, Atkinson G, Drust B, Gregson W. Monitoring fatigue during the in-season competitive phase in elite soccer players. Int J Sports Physiol Perform. 2015;10(8):958-964.
• 2. Impellizzeri FM, Marcora SM, Coutts AJ. Internal and external training load: 15 years on. Int J Sports Physiol Perform. 2019;14(2):270-273.
• 3. Foster C. Monitoring training in athletes with reference to overtraining syndrome. Medicine and Science in Sports and Exercise. 1998;30(7):1164-1168.
• 4. Saw AE, Main LC, Gastin PB. Monitoring the athlete training response: subjective self-reported measures trump commonly used objective measures: a systematic review. Br J Sports Med. 2016;50(5):281-291
• 5. Fessi MS, Moalla W. Postmatch perceived exertion, feeling, and wellness in professional soccer players. Int J Sports Physiol Perform. 2018;13(5):631-637.
• 6. Jaspers A, Brink MS, Probst SG, Frencken WG, Helsen WF. Relationships between training load indicators and training outcomes in professional soccer. Sport Med. 2017;47:533-544.
• 7. Malone S, Owen A, Newton M, et al. Wellbeing perception and the impact on external training output among elite soccer players. J Sci Med Sport. 2018;21(1):29-34.
• 8. Meeusen R, Duclos M, Foster C, et al. Prevention, diagnosis, and treatment of the overtraining syndrome: joint consensus statement of the European College of Sport Science and the American College of Sports Medicine. Medicine and Science in Sports and Exercise. 2013;45(1):186-205.
• 9. Foster C, Florhaug JA, Franklin J. A new approach to monitoring exercise training. J Strength Cond Res. 2021;15(1):109-115.
• 10. Foster C, Boullosa D, McGuigan M, et al. 25 years of session rating of perceived exertion: historical perspective and development. Int J Sports Physiol Perform. 2021;16(5):612-621.
• 11. Hooper SL, Mackinnon LT, Howard A, Gordon RD, Bachmann AW. Markers for monitoring overtraining and recovery. Medicine and Science in Sports and Exercise. 1995;27(1):106-112.
• 12. Buchheit M, Simpson M, Al Haddad H, Bourdon P, Mendez-Villanueva A. Monitoring changes in physical performance with heart rate measures in young soccer players. Eur J Appl Physiol. 2012;112:711-723.
• 13. Kalkhoven JT, Watsford ML, Coutts AJ, Edwards WB, Impellizzeri FM. Training load and injury: causal pathways and future directions. Sports Medicine. 2021;51:1137-1150.
• 14. Foster C, Rodriguez-Marroyo JA, De Koning JJ. Monitoring training loads: the past, the present, and the future. Int J Sports Physiol Perform. 2017;12(s2):2-8.
• 15. Govus AD, Coutts A, Duffield R, Murray A, Fullagar H. Relationship between pretraining subjective wellness measures, player load, and rating-of-perceived-exertion training load in American college football. Int J Sports Physiol Perform. 2018;13(1):95-101.
• 16. Cunanan AJ, DeWeese BH, Wagle JP, et al. The general adaptation syndrome: a foundation for the concept of periodization. Sport Med. 2018;48:787-797.
• 17. Bourdon PC, Cardinale M, Murray A, et al. Monitoring athlete training loads: consensus statement. Int J Sports Physiol Perform. 2017;12(s2):161- 170.
• 18. Gallo TF, Cormack SJ, Gabbett TJ, Lorenzen CH. Pre-training perceived wellness impacts training output in Australian football players. Journal of Sports Science. 2016;34(15):1445-1451.
• 19. Vardakis L, Koutsokosta M, Michailidis Y, Zelenitsas C, Topalidis P, Metaxas TI. Correlation between perceived exertion, wellness scores, and training load in professional football across microcycle durations. Applied Sciences. 2024;14(15):6767.