Correlation between Perceived Exertion, Wellness Scores, and Training Load in Professional Football across Microcycle Durations

Author:

Vardakis Lazaros1ORCID,Koutsokosta Marianthi1,Michailidis Yiannis1ORCID,Zelenitsas Charalambos2,Topalidis Panagiotis1,Metaxas Thomas I.1ORCID

Affiliation:

1. Laboratory of Evaluation of Human Biological Performance, Department of Physical Education and Sports Sciences, Aristotle University of Thessaloniki, 57001 Thessaloniki, Greece

2. Section of Sport Medicine and Biology of Exercise, School of Physical Education and Sport Science, National and Kapodistrian University of Athens, 15784 Athens, Greece

Abstract

Perceived exertion (RPE, RPEdur) and wellness scores (Hooper) are common methods to assess the training load and readiness in football. However, in professional football, there is a lack of data concerning the application of these tools in microcycles of different durations. Therefore, the purpose of this study was to explore the correlations between (a) RPE, RPEdur, and weekly external load (EXLD) and (b) Hooper and EXLD within microcycles of different durations. Independent of the microcycle’s length, RPE and RPEdur correlated with the EXLD. In MIC5, RPE and RPEdur correlated with the EXLD, except for accelerations > 3 m/s2 (ACh) and distance > 25.5 km/h (SPvh). In MIC6, RPE and RPEdur correlated with the EXLD, except Ach (with RPE). In MIC7 and MIC9, RPE and RPEdur correlated with the EXLD, except RPE with ACh. For Hooper variables, independent of the microcycle duration, SRN and FTG had more correlations in comparison to SLP; the same finding was observed in MIC7 and MIC9, but SRN and SLP in MIC5 and MIC6, respectively, had no correlations. Multiple regression analysis showed that for RPE, the main predictors are total distance (TD), metabolic power distance > 50 w/kg (PWvh), and ACh, which can explain 31% of the variance, but for RPEdur, 58% can be explained by DUR, TD, and PWvh. For SLP, the predictors FTG and SRN can explain a very small percentile of the variance (1%, 4%, and 6%, respectively). The main findings were the multiple correlations between RPE, RPEdur, Hooper, and microcycles of different durations; most of them were found for long durations. This tendency is similar to that described in the literature for microcycles of the same duration. (a) EXLD has a stronger correlation with RPEdur than with RPE, and (b) FTG and SRN are the best predictors of the EXLD during the upcoming training session. It is recommended that fitness coaches use these tools to assess and forecast the training load; thus, they will be able to prepare more effective sessions during microcycles of different durations.

Publisher

MDPI AG

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