Quantifying Sub-Elite Youth Football Weekly Training Load and Recovery Variation

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Abstract

Monitoring the training load in football is an important strategy to improve athletic performance and an effective training periodization. The aim of this study was two-fold: (1) to quantify the weekly training load and recovery status variations performed by under-15, under-17 and under-19 sub-elite young football players; and (2) to analyze the influence of age, training day, weekly microcycle, training and playing position on the training load and recovery status. Twenty under-15, twenty under-17 and twenty under-19 players were monitored over a 2-week period during the first month of the 2019–2020 competitive season. Global positioning system technology (GPS) was used to collect external training loads: total distance covered, average speed, maximal running speed, relative high-speed running distance, high metabolic load distance, sprinting distance, dynamic stress load, accelerations and decelerations. Internal training load was monitored using ratings of perceived exertion (RPE) and session rating of perceived exertion (sRPE). Recovery status was obtained using the total quality recovery (TQR) scale. The results show an age-related influence for external training load (p ≤ 0.001; d = 0.29–0.86; moderate to strong effect), internal training load (p ≤ 0.001, d = 0.12–0.69; minimum to strong effect) and recovery status (p ≤ 0.001, d = 0.59; strong effect). The external training load presented differences between training days (p < 0.05, d = 0.26–0.95; moderate to strong effect). The playing position had a minimum effect on the weekly training load (p < 0.05; d = 0.06–0.18). The weekly microcycle had a moderate effect in the TD (p < 0.05, d = 0.39), RPE (p < 0.05; d = 0.35) and sRPE (p < 0.05, d = 0.35). Interaction effects were found between the four factors analyzed for deceleration (F = 2.819, p = 0.017) and between inter-day, inter-week and age for total covered distance (F = 8.342, p = 0.008). This study provided specific insights about sub-elite youth football training load and recovery status to monitor training environments and load variations. Future research should include a longer monitoring period to assess training load and recovery variations across different season phases.

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Progressive statistics for studies in sports medicine and exercise science.

WILLIAM HOPKINS, STEPHEN W. MARSHALL, ALAN M. BATTERHAM … (2009)

Statistical guidelines and expert statements are now available to assist in the analysis and reporting of studies in some biomedical disciplines. We present here a more progressive resource for sample-based studies, meta-analyses, and case studies in sports medicine and exercise science. We offer forthright advice on the following controversial or novel issues: using precision of estimation for inferences about population effects in preference to null-hypothesis testing, which is inadequate for assessing clinical or practical importance; justifying sample size via acceptable precision or confidence for clinical decisions rather than via adequate power for statistical significance; showing SD rather than SEM, to better communicate the magnitude of differences in means and nonuniformity of error; avoiding purely nonparametric analyses, which cannot provide inferences about magnitude and are unnecessary; using regression statistics in validity studies, in preference to the impractical and biased limits of agreement; making greater use of qualitative methods to enrich sample-based quantitative projects; and seeking ethics approval for public access to the depersonalized raw data of a study, to address the need for more scrutiny of research and better meta-analyses. Advice on less contentious issues includes the following: using covariates in linear models to adjust for confounders, to account for individual differences, and to identify potential mechanisms of an effect; using log transformation to deal with nonuniformity of effects and error; identifying and deleting outliers; presenting descriptive, effect, and inferential statistics in appropriate formats; and contending with bias arising from problems with sampling, assignment, blinding, measurement error, and researchers' prejudices. This article should advance the field by stimulating debate, promoting innovative approaches, and serving as a useful checklist for authors, reviewers, and editors.

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A New Approach to Monitoring Exercise Training

CARL FOSTER, JESSICA A. FLORHAUG, JODI FRANKLIN … (2001)

The ability to monitor training is critical to the process of quantitating training periodization plans. To date, no method has proven successful in monitoring training during multiple types of exercise. High-intensity exercise training is particularly difficult to quantitate. In this study we evaluate the ability of the session rating of perceived exertion (RPE) method to quantitate training during non-steady state and prolonged exercise compared with an objective standard based on heart rate (HR). In a 2-part design, subjects performed steady state and interval cycle exercise or practiced basketball. Exercise bouts were quantitated using both the session RPE method and an objective HR method. During cycle exercise, the relationship between the exercise score derived using the session RPE method and the HR method was highly consistent, although the absolute score was significantly greater with the session RPE method. During basketball, there was a consistent relationship between the 2 methods of monitoring exercise, although the absolute score was also significantly greater with the session RPE method. Despite using different subjects in the 2 parts of the study, the regression relationships between the session RPE method and the HR method were nearly overlapping, suggesting the broad applicability of this method. We conclude that the session RPE method is a valid method of quantitating exercise training during a wide variety of types of exercise. As such, this technique may hold promise as a mode and intensity-independent method of quantitating exercise training and may provide a tool to allow the quantitative evaluation of training periodization plans.