The Individual and Combined Effects of Multiple Factors on the Risk of Soft Tissue Non-contact Injuries in Elite Team Sport Athletes

The usefulness of balance test in preseason evaluation of injuries in amputee football players: a pilot prospective observational study

Background

Low balance ability is generally associated with an increased risk of ligament injuries. It seems that assessing the level of stability in amputee football players can help evaluate the accompanying risk of sports injuries. Thus, the study aimed to examine the usefulness of the balance test in preseason evaluation by calculating between-group differences in stability parameters between injured and non-injured amputee players.

Methods

The study was designed as a pilot prospective observational study. Twenty-five elite amputee football players representing the Polish National Team and the highest division in Polish League completed one-leg preseason balance tests on the Biodex Balance System before the start of the football season. All players in this study were male, with an average age of 29 years (SD = 7.9), a stature of 174.2 cm (SD 5.2) and a body mass of 80.1 kg (SD = 13.1). Then, players were prospectively observed over one football season, and lower leg injury data were prospectively collected through the nine months. The between-group differences were tested using the non-parametric Mann-Whitney U test for players who sustained an injury (yes) and those who did not within the analysed season (no). Overall (OSI), medial-lateral (MLSI), and anterior-posterior stability index (APSI) were analysed as primary outcomes.

Results

The preseason values of the balance tests were not predictive (p > 0.05) regarding sustaining an injury during the season. No between-group differences were noted for any analysed outcomes (p values ranged from 0.093 to 0.453).

Conclusions

Although static balance tasks offer a chance to make a preliminary assessment of injury prediction in amputee footballers, in overall, the balance test results cannot be regarded as the sole predictive injury risk factor in amputee football.

Traumatic muscle injury

Traumatic muscle injury represents a collection of skeletal muscle pathologies caused by trauma to the muscle tissue and is defined as damage to the muscle tissue that can result in a functional deficit. Traumatic muscle injury can affect people across the lifespan and can result from high stresses and strains to skeletal muscle tissue, often due to muscle activation while the muscle is lengthening, resulting in indirect and non-contact muscle injuries (strains or ruptures), or from external impact, resulting in direct muscle injuries (contusion or laceration). At a microscopic level, muscle fibres can repair focal damage but must be completely regenerated after full myofibre necrosis. The diagnosis of muscle injury is based on patient history and physical examination. Imaging may be indicated to eliminate differential diagnoses. The management of muscle injury has changed within the past 5 years from initial rest, immobilization and (over)protection to early activation and progressive loading using an active approach. One challenge of muscle injury management is that numerous medical treatment options, such as medications and injections, are often used or proposed to try to accelerate muscle recovery despite very limited efficacy evidence. Another challenge is the prevention of muscle injury owing to the multifactorial and complex nature of this injury.

Team's average acute:chronic workload ratio correlates with injury risk in NCAA men's soccer team

BACKGROUND

Research in multiple sports has shown that an individual's acute:chronic workload ratio (ACWR) correlates with injury. However, tailoring team trainings to each individual's ACWR is technically challenging and has not been found to decrease injury risk.

OBJECTIVE

To establish a more feasible method of utilizing the ACWR for injury prevention in soccer. In a National Collegiate Athletic Association (NCAA) men's soccer team, we assessed whether the team's average ACWR, as opposed to that of each individual, correlated with injuries sustained throughout the season.

DESIGN

Injury and workload data were retrospectively evaluated for all players (n = 23) of an NCAA men's soccer team during one 18-week season. Workload data for five global positioning system (GPS)-derived workload variables (total distance, high-speed distance, accelerations, player load, and average velocity) were used to calculate the team's average daily acute and chronic workloads (accumulated load for each variable during the past 3 and 28 days, respectively), and uncoupled ACWRs (acute workload divided by chronic workload for each variable). A retrospective cohort design was used to compare the team's workloads and ACWRs on days where ≥1 injury occurred versus days where zero injuries occurred using binary logistic regression models.

RESULTS

Trainings/games with injuries had higher acute workloads, lower chronic workloads, and higher ACWRs for all five workload variables. In multivariable analysis, risk factors for injury included a low chronic workload for total distance (odds ratio [OR] 7.23, p = .024) and an ACWR >1.4 for accelerations (OR 4.34, p = .029).

CONCLUSIONS

The team's injury risk was greater with low distance accumulation during the chronic period and with an elevated ACWR for accelerations. Future intervention-based studies aimed at using ACWR load-management principles as a method of decreasing injury risk in soccer can consider tracking the team's average values with the goal of maintaining a consistent chronic workload for total distance and avoiding elevations in the ACWR for accelerations.

Noncontact Injury Distribution and Relationship With Preseason Training Load and Nonmodifiable Risk Factors in Rugby Union Players Across Multiple Seasons

ABSTRACT

Evans, SL, Whittaker, G, Elphinstone Davis, E, Jones, ES, Hardy, J, and Owen, JA. Noncontact injury distribution and relationship with preseason training load and non-modifiable risk factors in Rugby Union players across multiple seasons. J Strength Cond Res 37(7): 1456-1462, 2023-This study examined the distribution of noncontact injury during phases of the competitive season and the association between preseason training load (TL) and nonmodifiable risk factors on injury risk during these phases. Injury data were recorded from 1 senior academy team over 3 seasons (2017-2020) and analyzed across early-season, midseason, and late-season phases. A generalized estimating equation was used to model risk factors with noncontact injury for selected phases. The highest noncontact injury incidence occurred in the late-season phase (22.2 per 1,000 hours) compared with early (13.7 per 1,000 hours, p < 0.001) and midseason phases (15.5 per 1,000 hours, p = 0.001). Low preseason TL (8,949-12,589 arbitrary units; odds ratio [OR], 95% confidence interval [CI] = 4.7, 1.0-21.6; p = 0.04) and low preseason TL combined with high early-season TL and injury in the early-season phase (OR, 95% CI = 6.5, 1.1-35.5; p = 0.03) were associated with greater midseason noncontact injury risk. In addition, low preseason TL combined with previous injury was associated with increased risk of noncontact injury risk in the late season (OR, 95% CI = 12.2, 0.9-15.6, p = 0.05). Our results suggest players are at a greater injury risk during the late-season phase, with low preseason cumulative loads combined with a history of previous injury associated with increased in-season injury risk. Strength and conditioning coaches should therefore monitor cumulative preseason TL alongside screening for previous injury history to identify athletes at greater risk of noncontact injury risk during the competitive season.

Comparing Two Methods of Acute: Chronic Workload Calculations in Girls’ Youth Volleyball

Monitoring training load using acute:chronic workload ratio (ACWR) enables coaches to maximize fitness potential while mitigating injury risks by maintaining an optimal ACWR range. There are two methods of determining ACWR: rolling average (RA) and exponentially weighted moving average (EWMA). This study aimed to (1) compare weekly changes in kinetic energy (KE) output in female youth athletes (n = 24) during the high school (HSVB) and club volleyball (CVB) seasons and (2) evaluate the agreement in RA and EWMA ACWR calculations during the HSVB and CVB seasons. Weekly load was measured using a wearable device, and RA and EWMA ACWRs were calculated using KE. The HSVB data showed spikes in ACWR at the onset of the season and during one week mid-season (p = 0.001–0.015), but most weeks were in the optimal ACWR range. The CVB data had greater weekly variations throughout the season (p < 0.05), and many weeks were outside of the optimal ACWR range. There were moderate correlations between the two ACWR methods (HSVB: r = 0.756, p < 0.001; CVB: r = 0.646, p < 0.001). Both methods can be used as a monitoring tool for consistent training like that in HSVB, but more research is needed to investigate appropriate methods for an inconsistent season like that of CVB.

The Use of Wearable Sensors for Preventing, Assessing, and Informing Recovery from Sport-Related Musculoskeletal Injuries: A Systematic Scoping Review

Wearable technologies are often indicated as tools that can enable the in-field collection of quantitative biomechanical data, unobtrusively, for extended periods of time, and with few spatial limitations. Despite many claims about their potential for impact in the area of injury prevention and management, there seems to be little attention to grounding this potential in biomechanical research linking quantities from wearables to musculoskeletal injuries, and to assessing the readiness of these biomechanical approaches for being implemented in real practice. We performed a systematic scoping review to characterise and critically analyse the state of the art of research using wearable technologies to study musculoskeletal injuries in sport from a biomechanical perspective. A total of 4952 articles were retrieved from the Web of Science, Scopus, and PubMed databases; 165 were included. Multiple study features-such as research design, scope, experimental settings, and applied context-were summarised and assessed. We also proposed an injury-research readiness classification tool to gauge the maturity of biomechanical approaches using wearables. Five main conclusions emerged from this review, which we used as a springboard to propose guidelines and good practices for future research and dissemination in the field.

Training load monitoring in team sports: a practical approach to addressing missing data

Training load (TL) is a modifiable risk factor that may provide practitioners with opportunities to mitigate injury risk and increase sports performance. A regular problem encountered by practitioners, however, is the issue of missing TL data. The purpose of this study was to examine the impact of missing TL data in team sports and to offer a practical and effective method of missing value imputation (MVI) to address this. Session rating of perceived exertion (sRPE) data from 10 male professional soccer players (age, 24.8 ± 5.0 years; height, 181.2 ± 5.1 cm; mass, 78.7 ± 6.4 kg) were collected over a 32-week season. Data were randomly removed at a range of 5-50% in increments of 5% and data were imputed using 12 MVI methods. Performance was measured using the normalized root-mean-square error and mean of absolute deviations. The best-fitting MVI method across all levels of missingness was Daily Team Mean (DTMean). Not addressing missing sRPE data may lead to more inaccurate calculations of other TL metrics (e.g., acute chronic workload ratio, training monotony, training strain). The DTMean MVI method may provide practitioners with a practical and effective approach to addressing the negative consequences of missing TL data.

Evolution of Physical Demands of Australian Football League Matches from 2005 to 2017: A Systematic Review and Meta-Regression

BACKGROUND

There is extensive research investigating the match demands of players in the Australian Football League (AFL).

OBJECTIVE

This systematic literature review and meta-regression sought to analyse the evolution of in-game demands in AFL matches from 2005 to 2017, focusing on the relationship between volume and intensity.

METHODS

A systematic search of Ovid MEDLINE, Embase, Emcare, Scopus, SPORTDiscus, and Cochrane Library databases was conducted. Included studies examined the physical demands of AFL matches utilising global positioning system (GPS) technology. Meta-regression analysed the shift in reported volume (total distance and total match time) and intensity (metres per minute [m.min^-1], sprint duration and acceleration) metrics for overall changes, across quarters and positional groups (forwards, nomadics and defenders) from 2005 to 2017 inclusive and for each year between 2005 and 2007, 2007 and 2010, 2010 and 2012, and 2012 and 2015/2017 breakpoints.

RESULTS

Distance (p = 0.094), m.min^-1 (p = 0.494), match time (p = 0.591), time over 18 km·h^-1 (p = 0.271), and number of accelerations greater than 4 km·h^-1 (p = 0.498) and 10 km·h^-1 (p = 0.335) in 1 s did not change from 2005 to 2017. From 2005 to 2007 volume decreased (- 6.10 min of match time; p = 0.010) and intensity increased (6.8 m.min^-1 increase; p = 0.023). Volume and intensity increased from 2007 to 2010, evidenced by increases in total distance (302 m; p = 0.039), time over 18 km·h^-1 (0.31 min; p = 0.005), and number of accelerations greater than 4 km·h^-1 (41.1; p = 0.004) and 10 km·h^-1 (3.6; p = 0.005) in 1 s. From 2010 to 2012, intensity decreased, evidenced by reductions in metres per minute (- 4.3; p = 0.022), time over 18 km·h^-1 (- 0.93 min; p < 0.001), and number of accelerations greater than 4 km·h^-1 (- 104.4; p < 0.001) and 10 km·h^-1 (- 8.3; p < 0.001) in 1 s, whilst volume stabilised with no changes in distance (p = 0.068) and match time (p = 0.443). From 2012 to 2015/2017 volume remained stable and intensity increased with time over 18 km·h^-1 (0.27 min; p = 0.008) and number of accelerations greater than 4 km·h^-1 (31.6; p = 0.016) in 1 s increasing.

CONCLUSIONS

Changes in volume and intensity of AFL match demands are defined by discrete periods from 2007 to 2010 and 2010 to 2012. The interaction of rule and interpretation changes and coaching strategies play a major role in these evolutionary changes. In turn, modified game styles impact player game demands, training, and selection priorities. Standardisation and uniformity of GPS data reporting is recommended due to inconsistencies in the literature.

Magnitude, Frequency, and Accumulation: Workload Among Injured and Uninjured Youth Basketball Players

Overuse injuries are common in basketball. Wearable technology enables the workload to be monitored in sport settings. However, workload-injury models lack a biological basis both in the metrics recorded and how workload is accumulated. We introduce a new metric for monitoring workload: weighted jump height, where each jump height is weighted to represent the expected effect of the jump magnitude on damage to the tendon. The objectives of this study were to use principal components analysis to identify distinct modes of variation in all workload metrics accumulated over 1, 2, 3, and 4 weeks and to examine differences among the modes of variation in workload metrics between participants before the injury and uninjured participants. Forty-nine youth basketball players participated in their typical basketball practices and games, and lower extremity injuries were classified as patellar or Achilles tendinopathy, other overuse, or acute. An inertial measurement unit recorded the number and height of all jumps, and session rating of perceived exertion was recorded. The previous 1-, 2-, 3-, and 4-week workloads of jump count, jump height, weighted jump height, and session rating of perceived exertion were summed for each participant-week. Principal components analysis explained the variance in the accumulated workload variables. Using the retained principal components, the difference between the workload of injured participants in the week before the injury and the mean workload of uninjured participants was described for patellar or Achilles tendinopathy, overuse lower extremity injury, and any lower extremity injury. Participants with patellar or Achilles tendinopathy and overuse lower extremity injuries had a low workload magnitude for all variables in the 1, 2, 3, and 4 weeks before injury compared with the weeks before no injury. Participants with overuse lower extremity injuries and any lower extremity injury had a high previous 1-week workload for all variables along with a low previous 3- and 4-week jump count, jump height, and weighted jump height before injury compared with the weeks before no injury. Weighted jump height represents the cumulative damage experienced by tissues due to repetitive loads. Injured youth basketball athletes had a low previous 3- and 4-week workloads coupled with a high previous 1-week workload.

Is the Acute: Chronic Workload Ratio (ACWR) Associated with Risk of Time-Loss Injury in Professional Team Sports? A Systematic Review of Methodology, Variables and Injury Risk in Practical Situations

BACKGROUND

The acute: chronic workload ratio (ACWR) is an index of the acute workload relative to the cumulative chronic workloads. The monitoring of physical workloads using the ACWR has emerged and been hypothesized as a useful tool for coaches and athletes to optimize performance while aiming to reduce the risk of potentially preventable load-driven injuries.

OBJECTIVES

Our goal was to describe characteristics of the ACWR and investigate the association of the ACWR with the risk of time-loss injuries in adult elite team sport athletes.

DATA SOURCES

PubMed, EMBASE and grey literature databases; inception to May 2019.

ELIGIBILITY CRITERIA

Longitudinal studies that assess the relationship of the ACWR and time-loss injury risk in adult professional or elite team sports.

METHODS

We summarized the population characteristics, workload metrics and ACWR calculation methods. For each workload metric, we plotted the risk estimates for the ACWR in isolation, or when combined with chronic workloads. Methodological quality was assessed using a modified version of the Downs and Black scale.

RESULTS

Twenty studies comprising 2375 injuries from 1234 athletes (all males and mean age of 24 years) from different sports were included. Internal (65%) and external loads (70%) were collected in more than half of the studies and the session-rating of perceived exertion and total distance were the most commonly collected metrics. The ACWR was commonly calculated using the coupled method (95%), 1:4 weekly blocks (95%) and subsequent week injury lag (80%). There were 14 different binning methods with almost none of the studies using the same binning categories.

CONCLUSION

The majority of studies suggest that athletes are at greater risk of sustaining a time-loss injury when the ACWR is higher relative to a lower or moderate ACWR. The heterogenous methodological approaches not only reflect the wide range of sports studied and the differing demands of these activities, but also limit the strength of recommendations.

PROSPERO REGISTRATION NUMBER

CRD42017067585.

A Cherry, Ripe for Picking: The Relationship Between the Acute-Chronic Workload Ratio and Health Problems

OBJECTIVE

To investigate whether the relationship between the acute-chronic workload ratio (ACWR) and health problems varies when different methodological approaches are used to quantify it.

DESIGN

Prospective cohort study.

METHODS

An online questionnaire was used to collect daily health and training information from 86 elite youth footballers for 105 days. The relationship between players' training load and health was analyzed using a range of different definitions of ACWR and health problems. We used 21-day and 28-day chronic periods, coupled and uncoupled calculations, and the exponentially weighted moving average and rolling average. Acute-chronic workload ratio data were categorized as low, medium, or high, using predefined categories and z scores. We compared medium to high, medium to low, and low to high categories. The outcome was defined in 3 ways: "all health problems," "all injuries," and "new noncontact injuries." We performed random-effects logistic regression analyses of all combinations, for a total of 108 analyses.

RESULTS

We recorded 6250 athlete-days and 196 health problems. Of the 108 analyses performed, 23 (21%) identified a statistically significant (P<.05) association between the ACWR and health problems. A greater proportion of significant associations were identified when using an exponentially weighted moving average (44% of analyses), when comparing low to high categories (33%), and when using the "all health problems" definition (33%).

CONCLUSION

The relationship between the ACWR and health problems was dependent on methodological approach. J Orthop Sports Phys Ther 2021;51(4):162-173. Epub 20 Jan 2021. doi:10.2519/jospt.2021.9893.

Evaluating Methods for Imputing Missing Data from Longitudinal Monitoring of Athlete Workload

Missing data can influence calculations of accumulated athlete workload. The objectives were to identify the best single imputation methods and examine workload trends using multiple imputation. External (jumps per hour) and internal (rating of perceived exertion; RPE) workload were recorded for 93 (45 females, 48 males) high school basketball players throughout a season. Recorded data were simulated as missing and imputed using ten imputation methods based on the context of the individual, team and session. Both single imputation and machine learning methods were used to impute the simulated missing data. The difference between the imputed data and the actual workload values was computed as root mean squared error (RMSE). A generalized estimating equation determined the effect of imputation method on RMSE. Multiple imputation of the original dataset, with all known and actual missing workload data, was used to examine trends in longitudinal workload data. Following multiple imputation, a Pearson correlation evaluated the longitudinal association between jump count and sRPE over the season. A single imputation method based on the specific context of the session for which data are missing (team mean) was only outperformed by methods that combine information about the session and the individual (machine learning models). There was a significant and strong association between jump count and sRPE in the original data and imputed datasets using multiple imputation. The amount and nature of the missing data should be considered when choosing a method for single imputation of workload data in youth basketball. Multiple imputation using several predictor variables in a regression model can be used for analyses where workload is accumulated across an entire season.

Training Load and Its Role in Injury Prevention, Part 2: Conceptual and Methodologic Pitfalls

In part 2 of this clinical commentary, we highlight the conceptual and methodologic pitfalls evident in current training-load-injury research. These limitations make these studies unsuitable for determining how to use new metrics such as acute workload, chronic workload, and their ratio for reducing injury risk. The main overarching concerns are the lack of a conceptual framework and reference models that do not allow for appropriate interpretation of the results to define a causal structure. The lack of any conceptual framework also gives investigators too many degrees of freedom, which can dramatically increase the risk of false discoveries and confirmation bias by forcing the interpretation of results toward common beliefs and accepted training principles. Specifically, we underline methodologic concerns relating to (1) measure of exposures, (2) pitfalls of using ratios, (3) training-load measures, (4) time windows, (5) discretization and reference category, (6) injury definitions, (7) unclear analyses, (8) sample size and generalizability, (9) missing data, and (10) standards and quality of reporting. Given the pitfalls of previous studies, we need to return to our practices before this research influx began, when practitioners relied on traditional training principles (eg, overload progression) and adjusted training loads based on athletes' responses. Training-load measures cannot tell us whether the variations are increasing or decreasing the injury risk; we recommend that practitioners still rely on their expert knowledge and experience.

Training Load and Injury: Causal Pathways and Future Directions

Causal pathways between training loads and the mechanisms of tissue damage and athletic injury are poorly understood. Here, the relation between specific training load measures and metrics, and causal pathways of gradual onset and traumatic injury are examined. Currently, a wide variety of internal and external training load measures and metrics exist, with many of these being commonly utilized to evaluate injury risk. These measures and metrics can conceptually be related to athletic injury through the mechanical load-response pathway, the psycho-physiological load-response pathway, or both. However, the contributions of these pathways to injury vary. Importantly, tissue fatigue damage and trauma through the mechanical load-response pathway is poorly understood. Furthermore, considerable challenges in quantifying this pathway exist within applied settings, evidenced by a notable absence of validation between current training load measures and tissue-level mechanical loads. Within this context, the accurate quantification of mechanical loads holds considerable importance for the estimation of tissue damage and the development of more thorough understandings of injury risk. Despite internal load measures of psycho-physiological load speculatively being conceptually linked to athletic injury through training intensity and the effects of psycho-physiological fatigue, these measures are likely too far removed from injury causation to provide meaningful, reliable relationships with injury. Finally, we used a common training load metric as a case study to show how the absence of a sound conceptual rationale and spurious links to causal mechanisms can disclose the weaknesses of candidate measures as tools for altering the likelihood of injuries, aiding the future development of more refined injury risk assessment methods.

A League-Wide Evaluation of Factors Influencing Match Activity Profile in Elite Australian Football

Introduction: Accurate interpretation of activity profile data requires an understanding of the variables influencing player movement during matches.

Methods: Over 65,000 stints (player rotations) from all 207 matches of the 2018 Australian Football League (AFL) season were evaluated. The relative activity profile including total distance per minute (TD), high-speed running distance per minute (HSR) and Player Load^TM per minute (PL) was determined for each stint and analysed against a range of match-related, player-related and environment-related predictor variables using multivariate linear mixed modelling. Effect size statistics along with the uncertainty in the estimates (95% confidence interval) were used to interpret the findings.

Results: The smallest important effects on TD, HSR, and PL were calculated as 1.5%, 5.5%, and 2.4%, respectively. Stint duration had small to moderate negative effects on TD (−6%), PL (−7.7%), and HSR (−13%), while recovery duration between stints had a small positive effect on HSR (+7%). There were moderate reductions in TD (−8%), HSR (−23%), and PL (−9.6%) in the last quarter compared to the first quarter of matches, while similar reductions existed in subsequent stints compared to the first stint in each quarter. Moderate to large differences of up to 9% in TD, 48% in HSR and 12% in PL existed between positions. The TD of less experienced players was slightly higher than their more experienced counterparts (2–3%). A 5% increase in body mass was associated with a small reduction in HSR (−5.5%). There were small reductions in TD (−2%), HSR (−10%), and PL (−3%) during the Finals Series compared to the Premiership Season. Moderate levels of rainfall during matches and higher apparent temperatures had small negative effects on TD (−2%) and HSR (−6 and −9%). The number of days break between matches, score margin, match outcome, ground hardness, ground size, and traveling for the current or the previous match had trivial effects on the activity profile.

Conclusion: Player position and stage of the match (quarter) had the largest effects on match activity profile while stint duration, recovery duration, stint timing, professional experience, body mass, stage of the season, and weather conditions also had substantial effects.

Training Load and Injury Risk in Elite Rugby Union: The Largest Investigation to Date

Training load monitoring has grown in recent years with the acute:chronic workload ratio (ACWR) widely used to aggregate data to inform decision-making on injury risk. Several methods have been described to calculate the ACWR and numerous methodological issues have been raised. Therefore, this study examined the relationship between the ACWR and injury in a sample of 696 players from 13 professional rugby clubs over two seasons for 1718 injuries of all types and a further analysis of 383 soft tissue injuries specifically. Of the 192 comparisons undertaken for both injury groups, 40% (all injury) and 31% (soft tissue injury) were significant. Furthermore, there appeared to be no calculation method that consistently demonstrated a relationship with injury. Some calculation methods supported previous work for a "sweet spot" in injury risk, while a substantial number of methods displayed no such relationship. This study is the largest to date to have investigated the relationship between the ACWR and injury risk and demonstrates that there appears to be no consistent association between the two. This suggests that alternative methods of training load aggregation may provide more useful information, but these should be considered in the wider context of other established risk factors.

Does load management using the acute:chronic workload ratio prevent health problems? A cluster randomised trial of 482 elite youth footballers of both sexes

BACKGROUND

The acute:chronic workload ratio (ACWR) is commonly used to manage training load in sports, particularly to reduce injury risk. However, despite its extensive application as a prevention intervention, the effectiveness of load management using ACWR has never been evaluated in an experimental study.

AIM

To evaluate the effectiveness of a load management intervention designed to reduce the prevalence of health problems among elite youth football players of both sexes.

METHODS

We cluster-randomised 34 elite youth football teams (16 females, 18 males) to an intervention group (18 teams) and a control group (16 teams). Intervention group coaches planned all training based on published ACWR load management principles using a commercially available athlete management system for a complete 10-month season. Control group coaches continued to plan training as normal. The prevalence of health problems was measured monthly in both groups using the Oslo Sports Trauma Research Centre Questionnaire on Health Problems.

RESULTS

The between-group difference in health problem prevalence (primary outcome) was 1.8%-points (-4.1 to 7.7 %-points; p=0.55) with no reduction in the likelihood of reporting a health problem in the intervention group (relative risk 1.01 (95% CI 0.91 to 1.12); p=0.84) compared with the control group.

CONCLUSIONS

We observed no between-group difference, suggesting that this specific load management intervention was not successful in preventing health problems in elite youth footballers.

TRIAL REGISTRATION NUMBER

ISRCTN18177140.

Workload a-WEAR-ness: Monitoring Workload in Team Sports With Wearable Technology. A Scoping Review

OBJECTIVES

To (1) identify the wearable devices and associated metrics used to monitor workload and assess injury risk, (2) describe the situations in which workload was monitored using wearable technology (including sports, purpose of the analysis, location and duration of monitoring, and athlete characteristics), and (3) evaluate the quality of evidence that workload monitoring can inform injury prevention.

DESIGN

Scoping review.

LITERATURE SEARCH

We searched the CINAHL, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Embase, HealthSTAR, MEDLINE, PsycINFO, SPORTDiscus, and Web of Science databases.

STUDY SELECTION CRITERIA

We included all studies that used wearable devices (eg, heart rate monitor, inertial measurement units, global positioning system) to monitor athlete workload in a team sport setting.

DATA SYNTHESIS

We provided visualizations that represented the workload metrics reported, sensors used, sports investigated, athlete characteristics, and the duration of monitoring.

RESULTS

The 407 included studies focused on team ball sports (67% soccer, rugby, or Australian football), male athletes (81% of studies), elite or professional level of competition (74% of studies), and young adults (69% of studies included athletes aged between 20 and 28 years). Thirty-six studies of 7 sports investigated the association between workload measured with wearable devices and injury.

CONCLUSION

Distance-based metrics derived from global positioning system units were common for monitoring workload and are frequently used to assess injury risk. Workload monitoring studies have focused on specific populations (eg, elite male soccer players in Europe and elite male rugby and Australian football players in Oceania). Different injury definitions and reported workload metrics and poor study quality impeded conclusions regarding the relationship between workload and injury. J Orthop Sports Phys Ther 2020;50(10):549-563. doi:10.2519/jospt.2020.9753.

How Has Workload Been Defined and How Many Workload-Related Exposures to Injury Are Included in Published Sports Injury Articles? A Scoping Review

OBJECTIVE

To describe how workload-related exposure variables have been defined in sports injury articles, and to identify the number of workload-related exposure variables included in comparative analyses.

DESIGN

Scoping review.

LITERATURE SEARCH

PubMed, SPORTDiscus, and Scopus were systematically searched on March 13, 2020. Two reviewers independently screened the retrieved literature and selected articles for inclusion.

STUDY SELECTION CRITERIA

Prospective cohort studies using workload-related variables as the primary exposure to sports injury were eligible for inclusion.

DATA SYNTHESIS

The type (eg, distance, balls bowled) and construct of workload-related exposure variables (eg, acute-chronic workload ratio) were extracted and summarized in frequency tables.

RESULTS

A total of 648 articles were identified, and 45 were eligible for inclusion. Workload definition differed greatly, as sports- and workload-related exposure variables could be, but were not limited to, distance, balls bowled, session rating of perceived exertion, accelerations, soreness, and sleep. Within and across articles, authors used different constructs for workload-related exposure variables. For example, distance was represented as total distance, distance per week, distance per 2 weeks, and acute-chronic workload ratio. The number of workload-related exposure variables included in comparative analyses ranged from 1 to 336.

CONCLUSION

Studies used different definitions of workload-related exposure variables. The number of workload-related exposure variables in a single study ranged from 1 to 336. J Orthop Sports Phys Ther 2020;50(10):538-548. doi:10.2519/jospt.2020.9766.

Accelerometry as a method for external workload monitoring in invasion team sports. A systematic review

Accelerometry is a recent method used to quantify workload in team sports. A rapidly increasing number of studies supports the practical implementation of accelerometry monitoring to regulate and optimize training schemes. Therefore, the purposes of this study were: (1) to reflect the current state of knowledge about accelerometry as a method of workload monitoring in invasion team sports according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines, and (2) to conclude recommendations for application and scientific investigations. The Web of Science, PubMed and Scopus databases were searched for relevant published studies according to the following keywords: "accelerometry" or "accelerometer" or "microtechnology" or "inertial devices", and "load" or "workload", and "sport". Of the 1383 studies initially identified, 118 were selected for a full review. The main results indicate that the most frequent findings were (i) devices' body location: scapulae; (b) devices brand: Catapult Sports; (iii) variables: PlayerLoadTM and its variations; (iv) sports: rugby, Australian football, soccer and basketball; (v) sex: male; (vi) competition level: professional and elite; and (vii) context: separate training or competition. A great number of variables and devices from various companies make the comparability between findings difficult; unification is required. Although the most common location is at scapulae because of its optimal signal reception for time-motion analysis, new methods for multi-location skills and locomotion assessment without losing tracking accuracy should be developed.

Relationships Among PlayerLoad, High-Intensity Intermittent Running Ability, and Injury Risk in Professional Rugby League Players

PURPOSE

To examine relationships among physical performance, workload, and injury risk in professional rugby league players.

METHODS

Maximal-effort (n = 112) and submaximal (n = 1084) running performances of 45 players were recorded from 1 club over 2 consecutive seasons. Poorer and better submaximal running performance was determined by higher and lower exercise heart rates, respectively. Exponentially weighted moving averages and daily rolling averages were used to assess microtechnology-derived acute and chronic field-based workloads. The associations among within-individual submaximal running performance, workload, and noncontact lower-limb injury were then investigated.

RESULTS

The injury risk associated with poorer submaximal performance was "likely" greater than stable (relative risk = 1.8; 90% confidence interval, 0.9-3.7) and better submaximal performance (relative risk = 2.0; 90% confidence interval, 0.9-4.4). Compared with greater submaximal performance, poorer performance was associated with lower chronic workloads (effect size [d] = 0.82 [0.13], large) and higher acute:chronic workload ratios (d = 0.49 [0.14], small). Chronic workload demonstrated a "nearly perfect" positive relationship with maximal-effort running performance (exponentially weighted moving average, R2 = .91 [.15]; rolling average, R2 = .91 [.14]). At acute:chronic workload ratios >1.9, no differences in injury risk were found between rolling average and exponentially weighted moving average methods (relative risk = 1.1; 90% confidence interval, 0.3-3.8; unclear).

CONCLUSIONS

Reductions in submaximal running performance are related with low chronic workloads, high acute:chronic workload ratios, and increased injury risk. These findings demonstrate that a submaximal running assessment can be used to provide information on physical performance and injury risk in professional rugby league players.

The Relationship Between Acute: Chronic Workload Ratios and Injury Risk in Sports: A Systematic Review

PURPOSE

Low injury rates have previously been correlated with sporting team success, highlighting the importance of injury prevention programs. Recent methods, such as acute:chronic workload ratios (ACWR) have been developed in an attempt to predict and manage injury risk; however, the relation between these methods and injury risk is unclear. The aim of this systematic review was to identify and synthesize the key findings of studies that have investigated the relationship between ACWR and injury risk.

METHODS

Included studies were critically appraised using the Downs and Black checklist, and a level of evidence was determined. Relevant data were extracted, tabulated, and synthesized.

RESULTS

Twenty-seven studies were included for review and ranged in percentage quality scores from 48.2% to 64.3%. Almost perfect interrater agreement (κ = 0.885) existed between raters. This review found a high variability between studies with different variables studied (total distance versus high speed running), as well as differences between ratios analyzed (1.50-1.80 versus ≥1.50), and reference groups (a reference group of 0.80-1.20 versus ≤0.85).

CONCLUSION

Considering the high variability, it appears that utilizing ACWR for external (eg, total distance) and internal (eg, heart rate) loads may be related to injury risk. Calculating ACWR using exponentially weighted moving averages may potentially result in a more sensitive measure. There also appears to be a trend towards the ratios of 0.80-1.30 demonstrating the lowest risk of injury. However, there may be issues with the ACWR method that must be addressed before it is confidently used to mitigate injury risk. Utilizing standardized approaches will allow for more objective conclusions to be drawn across multiple populations.