This study quantified and compared the weekly locomotor activity and subjective load between elite and development loan youth soccer players registered to a primary club. Development loan players were loaned to a lower-league club and trained part-time with their loan club whilst being available for development fixtures and training with the primary club. Data were collected in 16 squad players and 4 development loan players at loan clubs across a 41 week competitive phase of the 2018/2019 season. Analysis was completed on total distance (m), PlayerLoad TM (au), low intensity running (<14.4 km·h −1 , m), running (19.8–24.98 km·h −1 , m), sprinting (>24.98 km·h −1 , m), accelerations (>2 m·s −2 count) and decelerations (<−2 m·s −2 , count). Point estimates for the development loan players consistently showed lower weekly values than squad players for all variables ranging from 5.2% (weekly sRPE) to 16.8% (weekly sprint distance covered). Differences, however, were not found to be statistically significant ( p ≥ 0.07). Variance ranged from 23.6% (weekly distance) to 37.7% (weekly high-intensity accelerations). Although the goals of a development loan are likely to be multifactorial, this is the first study to quantify and compare locomotor activities and subjective loading of players within the development loan environment.

Introduction: academy soccer practitioners have a responsibility to prepare youth players for the demands of first team. The development of physical capabilities to sustain the high intensity locomotor activities that have been reported in elite soccer is essential. Challenges exist monitoring locomotor targets as resource limitations mean that often academies will not have locomotor data, instead relying on physiological testing to assess whether a player is ready for first team transition. Physiological testing results have a direct relationship with locomotor activity. Physical development has been shown over various longitudinal periods with established progression in speed, change of direction, lower body power and endurance in elite Austrian youths, increases in VO2max in an elite regional French academy and in the interval shuttle run test of over 50% in elite Dutch academy. The success of a club’s academy can lead to increased resource allocation however some organisational challenges such as relegation can have a severe financial impact. The initial aim of the present study was to establish whether previously observed changes in physical capacity were observed in a professional Scottish soccer academy over a ten-year period. A further aim was to assess the impact of first team relegation on academy physical profiles considering the resource implications of relegation. Methodology: a retrospective analysis was completed where Linear Mixed Effect (LME) Models were fitted to explain variation across each measure of physical capacity. Model selection was undertaken with Likelihood Ratio Tests where initial complex models were compared to simpler nested models to arrive at the final model by maximum likelihood. The impact of relegation was assessed by LME models to assess whether physical capacity measures changed post relegation. Ethical approval was granted. Results: 5 m best time reduced by 0.0055 s per year (t = −11.8, p < 0.001), 10 m best time reduced by 0.008 s per year (t = −9.2, p < 0.001), 20 m best time reduced by 0.011 s per year (t = −7.8, p < 0.001). CMJ increased each year depended on age group with the older cohorts showing greater improvement and the YYIR1 distance increased each year varying across age group. Performance of aforementioned physical capacity measures significantly reduced with relegation, except 20 m best time (t = −1.4, p = 0.16). Application: reference values within clubs that establish first team requirements will contribute to appropriate transition strategies. By conducting analyses related to uncontrollable challenges, practitioners can use these results to protect against criticism and withdrawal of resource when physical progression is negatively impacted.

Background:Increases in high-intensity locomotor activity of match play have been recorded in elite soccer. This places an onus on academy practitioners to develop players for the future demands of the game. At an academy level, locomotor data are not available for analysis over a longitudinal period, and thus changes can only be assessed with physical attribute assessment. The aim of the present study is to establish if changes in physical capacity were observed in a professional Scottish soccer academy over a ten-year period. Methods:A retrospective analysis was completed where linear mixed effect (LME) models were individually fitted to explain variation across each measure of physical capacity. Model selection was undertaken with likelihood ratio tests where the initial complex models were compared to simpler nested models to arrive at the final model by maximum likelihood. Results:The main findings were that most recent players' sprint test data revealed a significant improvement in 5m, 10m and 20m sprint performance, greater increases in CMJ performance in older age groups, and greater increases in YYIR1 performance at U13 and U14. Most physical results showed increased performance with greater relative height and weight. Conclusion:Players recruited more recently to academies are fitter than they were previously. Reference values within clubs that establish first team requirements will contribute to appropriate planning and implementation of training.

The purpose of this study was to investigate the structure of relationships between measures of training load and assess whether these can be modified through non-linear transformations. Ratings of perceived exertion (RPE) and seven external load measures (total distance covered, PlayerLoad, low-intensity running distance, high-speed running distance, sprinting distance, accelerations, and decelerations) were collected from 20 academy soccer players (age = 17.4 ± 1.3 years, stature = 178.0 ± 8.1 cm, body-mass = 71.8 ± 7.2 kg), with 3220 recordings taken across a 47-week season. To control for the effects of session duration, sessions were categorised as short (≤60 min) or long (>60 min). All RPE and sessional RPE-training load (sRPE-TL; RPE multiplied by session duration) were analysed in their raw form and through raising to a series of exponentials. The underlying structure of the data was investigated using principal component analysis. Two components were retained for each analysis and varimax rotation was performed. The first rotated component (RC) was best represented as a measure of volume (RCvolume) with high loadings for RPE and sRPE-TL, whilst the second RC was best represented as a measure of intensity (RCintensity). Non-linear transformations had little effect on loading of modified measures for long sessions for sRPE-TL (RCvolume: 0.87–0.8; RCintensity: 0.27–0.13), and for RPE (RCvolume: 0.76–0.79; RCintensity: 0.17–0.10). For short sessions, the loading became more equal between intensity and volume for sRPE-TL (RCvolume: 0.88–0.41; RCintensity: 0.32–0.36) and more aligned to intensity (RCintensity: 0.52–0.61) compared with volume (RCvolume: 0.44–0.23) for RPE. The present study demonstrates that RPE and sRPE-TL predominantly reflect measures of training volume, however, they can be modified to better reflect intensity for training sessions <60 min in duration.

The aims of the current study were to investigate the use of dRPE with academy soccer players to: 1) examine the effect of bio-banded and non-bio-banded maturity groups within SSG on players dRPE; 2) describe the multivariate relationships between dRPE measures investigating the sources of intra and inter-individual variation, and the effects of maturation and bio-banding. Using 32 highly trained under (U) 12 to U14 soccer players (mean (SD) age 12.9 (0.9) years, body mass 46.4 (8.5) kg and stature 158.2 (14.9) cm) academy soccer players from two English professional male soccer academies. Players were categorised according to somatic maturity status using estimated percentage of adult stature attainment, with players randomly assigned into teams to play 4v4 SSG. The study used a repeated measures design, whereby the selected players participated within 6 bio-banded (maturity matched [pre-PHV Vs pre-PHV and post-PHV vs post PHV] and miss-matched [pre-PHV vs post-PHV] and 6 mixed maturity SSG at their respective clubs. Using mixed and fixed effect regression models, it was established hat pre-PHV players exhibited higher dRPE compared with their post-PHV counterparts. Mixed bio-banded games reported higher dRPE outputs overall. Variation in dRPE measures across a series of bio-banded games are caused by both between and within sources of variation in relatively equal amounts. Across a series of bio-banded games, the four dRPE measures do not provide unique information, and between variation is best expressed by one or two highly correlated components, with within variation best explained by a single equally loaded component. Using a bio-banding SSG design study, we have shown that pre-PHV players report higher subjective measures of exertion than post-PHV players during. Additionally, when evenly mixing players based on measures of maturation, higher measures of perceived exertion were generally reported.

The magnitude of change following strength and conditioning (S&C) training can be evaluated comparing effect sizes to thresholds. This study conducted a series of meta-analyses and compiled results to identify thresholds specific to S&C, and create prior distributions for Bayesian updating. Pre- and post-training data from S&C interventions were translated into standardised mean difference (SMDpre) and percentage improvement (%Improve) effect sizes. Bayesian hierarchical meta-analysis models were conducted to compare effect sizes, develop prior distributions, and estimate 0.25-, 0.5-, and 0.75-quantiles to determine small, medium, and large thresholds, respectively. Data from 643 studies comprising 6574 effect sizes were included in the analyses. Large differences in distributions for both SMDpre and %Improve were identified across outcome domains (strength, power, jump and sprint performance), with analyses of the tails of the distributions indicating potential large overestimations of SMDpre values. Future evaluations of S&C training will be improved using Bayesian approaches featuring the information and priors developed in this study. To facilitate an uptake of Bayesian methods within S&C, an easily accessible tool employing intuitive Bayesian updating was created. It is recommended that the tool and specific thresholds be used instead of isolated effect size calculations and Cohen's generic values when evaluating S&C training.

The purpose of this study was to investigate the time-course of decrements in physical performance following a pre-match warm-up in soccer players. Knowledge of this information could be used to inform re-warm-ups and pre-pitch entry practices of soccer substitutes. Data were collected over five sessions with 12 male youth professionals (15–17 yrs). Across the five sessions each player performed countermovement jumps (CMJ) and drop jumps (30 and 40 cm), pre-warm-up, immediately post-warm-up, and following 10-, 20-, 30-, 40-, and 50-min of inactivity. Physical performance was assessed by jump height and calculation of reactive strength index (RSI). Hierarchical generalised linear models (HGLMs) were fitted within a Bayesian framework to identify plausible time to achieve 10 to 50% decrements of the initial pre to post warm-up improvement. Mean improvements of 5.4 cm (95%CrI: 4.8 to 6.0), 0.24 ms −1 (95%CrI: 0.19 to 0.29), and 0.32 ms −1 (0.27 to 0.36) were obtained for the CMJ, and RSI measured from the 30 and 45 cm box, respectively. Decrements for all assessments were non-linear with the steepest rates of decline measured in the initial periods following warm-up. High probabilities were calculated ( p ≥ 0.979) that up to 50% of the initial warm-up improvement for the CMJ would be lost between 20 and 30 min. The results of this study provide a guide for future research and practitioners managing the pre-pitch entry of soccer substitutes. It is suggested that practitioners consider and assess the effectiveness of exposing players to a re-warm-up between 20- and 30-min prior to pitch entry to maintain performance capabilities.

The purpose of this research was to assess relationships between subjective and external measures of training load in professional youth footballers, whilst accounting for the effect of the stage of the season. Data for ratings of perceived exertion (RPE) and seven global positioning systems (GPS) derived measures were collected from 20 players (age = 17.4 +/- 1.3 yrs, height = 178.0 +/- 8.1 cm, mass = 71.8 +/- 7.2 kg) across a 47-week season. The season was categorised by a pre-season phase, and two competitive phases (Comp1, Comp2). The structure of the data were investigated using principal component analysis. An extraction criterion of component with eigenvalues >= 1.0 was used. Two components were retained for the pre-season period explaining a cumulative variance of 77.1%. Single components were retained for both Comp1 and Comp2 explaining 73.3% and 74.3% of variance, respectively. Identification of single components may suggest that measures are related and can be used interchangeably, however these interpretations should be considered with caution. The identification of multiple components in the pre-season phase suggests that univariate measures may not be sufficient when considering load experienced. These results suggest that factoring load based on measures of volume and intensity should be considered.

PURPOSE:To quantify and describe relationships between subjective and external measures of training load in professional youth soccer players.METHODS:Data from differential ratings of perceived exertion (dRPE) and 7 measures of external training load were collected from 20 professional youth soccer players over a 46-week season. Relationships were described by repeated-measures correlation, principal component analysis, and factor analysis with oblimin rotation.RESULTS:Significant positive (.44 ≤ r ≤ .99; P < .001) within-individual correlations were obtained across dRPE and all external training load measures. Correlation magnitudes were found to decrease when training load variables were expressed per minute. Principal component analysis provided 2 components, which described 83.3% of variance. The first component, which described 72.9% of variance, was heavily loaded by all measures of training load, while the second component, which described 10.4% of the variance, appeared to have a split between objective and subjective measures of volume and intensity. Exploratory factor analysis identified 4 theoretical factors, with correlations between factors ranging from .5 to .8. These factors could be theoretically described as objective volume, subjective volume, objective running, and objective high-intensity measures. Removing dRPE measures from the analysis altered the structure of the model, providing a 3-factor solution.CONCLUSIONS:The dRPE measures are significantly correlated with a range of external training load measures and with each other. More in-depth analysis showed that dRPE measures were highly related to each other, suggesting that, in this population, they would provide practitioners with similar information. Further analysis provided characteristic groupings of variables.

The purpose of this study was to quantify load across an entire season for professional youth football players and assess the effects of stage of season, playing position and training day relative to match day (MD). Data from ratings of perceived exertion and seven global positioning system (GPS) derived measures of external training load were collected from 20 players across a 47-week season. Mixed linear models were used to assess the effects of stage of season, training proximity to match day (e.g. MD-1, MD-2) and position across each dependent variable. Training proximity to match day was found to have the most substantive effect with effect sizes ranging from small ([Formula: see text] to large ([Formula: see text]. Across training load measures, mean values collected on match day were on average 47% higher than all other sessions. Whilst significant regression coefficients were obtained for playing position (p ≤ 0.003) and stage of season (p ≤ 0.049), effect sizes were close to zero ([Formula: see text]in each instance. This study provides insight into the season-long training and match-play demands of a professional youth football team. It highlights the significant impact of match-play on load and supports the use of multiple methods of collecting training load data. Overall, there was limited variation in mean values of dependent variables across playing position, stage of the season and loading during midweek training. These findings highlight the need for future research to investigate whether greater systematic variations in training load can be used to increase physical fitness and maximise physical performance during competition.

Abstract This study aims to investigate the relationship between subjective and external measures of load in professional youth football players whilst accounting for the effect of training theme or competition. Data from ratings of perceived exertion and global positioning system-derived measures of external training load were collected from 20 professional youth players (age=17.4±1.3 yrs) across a 46-week season. General characteristics of training sessions were categorised based on their proximity to match day. The underlying structure of the data was investigated with principal component analysis. An extraction criterion comprising eigenvalues >1 was used to identify which components to retain. Three components were retained for training performed three days prior to match day (80.2% of variance), with two components (72.9–89.7% of variance) retained for all other modes. Generally, the first component was represented by measures of volume (Total Distance, PlayerLoad and low intensity running) whilst the second and third components were characterised by measures of intensity. Identification of multiple components indicates that load monitoring should comprise multiple variables. Additionally, differences in the underlying structure across training days that reflected different goals suggest that effective monitoring should be specific to the demands of different session types.

Intensified periods of competition create large increase in physical workload and can expose soccer players to numerous playing styles. The purpose of the study was to investigate the response of youth soccer players to an intensified period of competition and assess whether initial fitness influenced outcomes. Elite males across two consecutive years (n 1 = 18, n 2 = 18) were assessed for lower body strength and high-intensity endurance. Objective and subjective measures of fatigue were collected throughout five-day international tournaments using countermovement jumps (CMJ), a perceptual wellness questionnaire and match GPS data. Mixed effects models quantified the effects of time and fitness on outcomes. In general, results were consistent across both years. No significant interaction effects were obtained between time and fitness variables for any outcome ([Formula: see text] ≤ 6.5; p ≥ .225). CMJ height and power remained consistent across both tournaments ([Formula: see text] ≤ 5.3; p ≥ .262). In contrast, significant ([Formula: see text] ≥ 17.7; p < .003) effects of time were obtained for GPS data with metrics exhibiting U-shape patterns with values returning to initial levels during final games. Greater variation was obtained for perceptual wellness data; however, responses to general muscle soreness and stress levels showed consistent decreases across both years ([Formula: see text] ≥ 12.7; p ≤ .013). Practitioners should be aware that basic measures collected from CMJ and GPS data may not be sensitive to fatigue accrued in youth soccer players across intensified periods of competition. In contrast, simple perceptual measures including general muscle soreness and stress may be more sensitive and assist with implementation of active recovery or load management strategies.