Simulating association between training load and injury using the acute: chronic workload ratio and Bayesian methods in youth football.

Previous research has examined the relationship between relative workload and injury, where acute training load is expressed in relation to chronic training load using simple ratio scaling or non-linear models including the exponentially weighted moving average (EWMA). Research has demonstrated that higher relative workloads are associated with greater injury risk; however, statistical models generally report non-intuitive statistics such as odds ratios and as a result the practical consequences of increased player loading remain unclear. Here we combine training and injury data collected in youth football with a predictive simulation approach to model the number of injuries sustained across a range of seasonal workloads

Analysis and application of techniques to monitor training load in youth soccer players

Soccer is regarded as the world’s most popular sport, performance in which depends on a range of factors generally characterised as being technical, tactical, physical, or psychological. The lucrative nature of the sport has allowed clubs to invest in academies in the hope of developing future players. These academies are supported by a range of practitioners, alongside investment in further understanding talent identification and talent development. A key role of practitioners within clubs is monitoring the load undertaken by players, with the aim of supporting training prescription to optimise performance and reduce the risk of injury. This thesis develops around five projects, analysing commonly used objective and subjective measures of training load to establish their relationships, developing novel methods of analysing subjective load, and testing the implementation of these methods within the transition from academy to full-time professional soccer. The first data chapter aimed to describe and quantify relationships between subjective and external measures of training load in professional youth soccer players. Data from differential ratings of perceived exertion (dRPE) and seven measures of external load were collected from twenty youth professional soccer players over a 47-week season. Relationships were described via bivariate correlations and multivariate factor analysis methods. Results from these analyses suggested that there was a theoretical dispersion between measures which may be representative of volume, such as total distance covered, and measures which may be representative of intensity, such as sprint distance. Additionally, it was found that subjective measures of breathlessness and lower body muscle exertion provided limited additional insight over gestalt ratings of perceived exertion (sRPE) within the analysed population. The second data chapter investigated the influence of training theme or competition on previously described relationships. Subjective load data was collected via sRPE and seven external load measures. General characteristics of training sessions were categorised based on their proximity to match day, with match-play also included within the analyses. Similarly to the first data chapter, analysis presented two, or three, readily interpretably components. The first component was represented by measures of volume, whilst the second and third components were generally represented by measures of intensity. This supports the finding of study one, that the identification of multiple components indicate that load monitoring should comprise multiple variables. Whilst generally the findings of this study mirrored study one, there were minor differences which suggest that effective monitoring practices should account for the demands of different session types. The third data chapter assessed the relationship between subjective and external load measures whilst accounting for the impact of phase of season. Subjective load relationships were collected via RPE, whilst data were collected via microelectromechanical system (MEMS) devices to analyse seven external load variables. Data were collected across a 47-week season with phases categorised as being pre-season phase, or competitive phases. Interestingly, when performing principal component analysis and using an alternative method to determine component extraction, only one component was retained for the competitive phases, whilst two components were retained for the pre-season phase. However, if using previously utilised methods similar results would have been found as to the previous data chapters. These findings highlight the importance of clearly defined methodology within factor analysis. Additionally, these results highlight that factoring load based on measures of volume and intensity may be considered as worthwhile practice by practitioners. Given the collective results from the previous data chapters, the aim of the fourth data chapter was to investigate the structure of relationships between measures of training load and assess whether these can be modified through non-linear transformations. To control for the effects of session duration, sessions were categorised into short (≤ 60mins) or long (> 60mins), based on the mean session duration for both training and match-play. All sRPE were analysed in their raw form and with the inclusion of session duration (sRPE-TL). Additionally, sRPE and sRPE-TL was modified through nonlinear transformations by raising to a series of exponentials to provide a metric termed “modified RPE” (sRPEmod). Similarly, to previous data chapters, following PCA two components were retained which provided theoretical representations of volume or intensity. Non-linear transformations had little effect on loading profiles for long sessions. For short sessions the loading became more equal between intensity and volume for sRPE-TL, and more aligned to intensity for sRPE. The study demonstrated that sRPE and sRPE-TL predominantly reflect measures of training volume, however, these measures can be modified to better reflect intensity for training sessions less than 60mins in duration. A key issue within soccer is optimising the transition of players going from academy to full-time professional soccer, therefor the aim of the fifth data chapter was to investigate the load experienced by players undergoing this transition. Additionally, the chapter aimed to determine whether subjective measures of load can provide useful insight into training volume, training intensity, or a combination of the two constructs in an applied setting. Data were collected from 4 academy players who had been identified as transitioning into full-time soccer. Data were then collected the following pre-season from the pre-determined transitioning players, and current development squad players. Subjective data were collected via sRPE and sRPEmod, whilst external load measures were collected via MEMS devices. Results showed that there were significant differences between academy and transition phases for players with regards to sRPEmod and weekly sRPE and sRPEmod. There were no significant differences identified between the academy and transition phase for daily sRPE or sRPE-TL. With regards to external measures of load, there were no significant differences between transition and development players in either sessional or weekly measures. These findings suggest that using a proposed modified subjective measure to identify differences in the load experienced by transition, academy, and development players, however the exact nature of these differences is unknown. The collective findings in this thesis highlight relationships between subjective and external measures of load within youth soccer players. The results highlight the lack of additional information provided by dRPE, questioning the use of this measure within this population. Additionally, the results highlight that it appears logical to factor load based on volume and intensity, and that these relationships appear to remain relatively consistent regardless of training theme or stage of season. This thesis also highlights complexities involved in modifying subjective measures of load to provide a greater representation of intensity to allow practitioners who may not have access to external load measures to greater account for this. Whilst the methods proposed showed the relationship between subjective and external measures could be modified, this was only for short duration sessions. Finally, when monitoring the transition of players from academy to full-time professional soccer it was shown that sRPEmod highlighted differences within players undergoing a transition, however the exact nature of this was unclear. These findings can be used to enhance the monitoring approaches of practitioners working within professional soccer. Additionally, these findings provide evidence that practitioners who are limited to subjective measures of load should consider alternative methods if monitoring training intensity is required. Further research is required to investigate modifying subjective measures of load to greater represent intensity. Additionally, further research is required to understand the load experienced by players undergoing a transition from academy to full-time professional environments

Relationship between subjective and external training load variables in youth soccer players.

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 and seven 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 (0.44 ≤ r ≤ 0.99; p< 0.001) 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 two components that described 83.3% of variance. The first component, which described 72.9% of variance, was heavily loaded by all measures of training load, whilst 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 four theoretical factors with correlations between factors ranging from 0.5 to 0.8 These factors could be theoretically described as; objective volume, subjective volume, objective running and objective high intensity measures. Removing dRPE measures from analysis altered the structure of the model, providing a three factor solution. Conclusions: Differential RPE 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 influence of season phase on multivariate load relationships in professional youth soccer.

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±1.3yrs, 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

Locomotor activities and subjective load differences between professional youth soccer players and professional development loans: a comparative analysis.

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), PlayerLoadTM (au), low intensity running (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

Time-course analysis following initial warm-up to inform pre-pitch entry preparations of soccer substitutes.

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-minutes of inactivity. Physical performance was assessed by jump height and calculation of reactive strength index (RSI). Hierarchical generalized 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 minutes. 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-minutes prior to pitch entry to maintain performance capabilities

Physiological and perceptual responses of youth soccer players to an intensified period of competition.

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 (n1=18, n2=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 (χ_4^2≤ 6.5; p≥ .225). CMJ height and power remained consistent across both tournaments (χ_4^2≤ 5.3; p≥ .262). In contrast, significant (χ_4^2≥ 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 (χ_4^2 ≥ 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

Examination of differential ratings of perceived exertion (dRPE) during bio-banded small-sided games.

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

Interpreting magnitude of change in strength and conditioning: effect size selection, threshold values and Bayesian updating.

The magnitude of change following strength and conditioning (S&C) training can be evaluated comparing effect sizes to threshold values. 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. Four-level 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