Analyzing Activity and Injury: Lessons Learned from the Acute:Chronic Workload Ratio

Law enforcement recruit fitness: Changes across the fitness spectrum

BACKGROUND

Law enforcement is a profession of sedentary physical activity interspersed with physically demanding activity that requires high levels of fitness. It is imperative that agencies training law enforcement recruits maximise their fitness during their time at the academy.

OBJECTIVE

The aim of this study was to investigate changes in physical fitness during academy training.

METHODS

Retrospective data for 10 academy recruit classes, totalling 715 participants, were collected from a US law enforcement agency. The change in performance on two standardised tests were used as outcome measures. Comparisons were made between percentiles utilising one-way ANOVA and a linear mixed model (LMM).

RESULTS

Overall, higher percentiles were found to have smaller improvements in physical fitness than lower percentiles. The results of the LMM support this supposition, showing that lower physical fitness scores resulted in greater improvements in a generalised fitness assessment (value = -0.45, standard error 0.02, p <  0.001) and an occupational assessment (value = -0.49, standard error = 0.02, p <  0.001).

CONCLUSION

The results of this study suggest that recruits with lower physical fitness will see greater improvements during academy training. This could be due to a ceiling effect for the more fit but may also be due to recruits of higher physical fitness being under trained during academy. Utilising ability-based training and prescribing an appropriate workload to recruits of higher fitness may improve overall recruit fitness upon graduation.

Dose-Response Relationship for External Workload and Neuromsuclar Performance Over a Female, Collegiate, Basketball Season

ABSTRACT

Philipp, NM, Cabarkapa, D, Blackburn, SD, and Fry, AC. Dose-response relationship for external workload and neuromsuclar performance over a female, collegiate, basketball season. J Strength Cond Res 38(5): e253-e263, 2024-The aim of this study was to investigate the relationship between external workload exposure and changes in countermovement jump force-time characteristics over the course of an entire basketball season, in a sample of National Collegiate Athletic Association Division I, female, basketball players. Data for 12 players were retrospectively analyzed, with external workload being quantified by means of an exponentially weighted, acute, and chronic workload, as well as an acute:chronic workload ratio derived from an inertial measurement unit-based system worn by athletes for all practices and games during the regular season. Countermovement jumps were performed on a total of 26 test days over the span of the in-season competitive period. To statistically analyze these relationships, and to account for multiple observations of the same athletes in a data set, linear mixed-effects models with athlete identity (ID) intercept as the random effect were used. Study findings suggested that associations between external workload exposure and respective force-time characteristics after controlling for the random effect of athlete ID were dependent on the specific metric or metric subgroup used, as well as the type of workload exposure (e.g., acute vs. chronic). Force-time signatures from the braking phase (e.g., average braking force) seemed to be particularly associated with higher degrees of acute workload exposure, whereas strategy-based metrics such as countermovement depth showed significant associations with chronic workload exposure. Furthermore, model results suggested the importance of analyzing neuromuscular responses to external workload on an individual basis, rather than across an entire team. Findings might help practitioners in their selection process related to metrics of interest in monitoring neuromuscular fatigue and readiness.

Causal inference did not detect any effect of jump load on knee complaints in elite men's volleyball

The aim was to determine how jump load affects knee complaints in elite men's volleyball. We collected data from four men's premier league volleyball teams through three seasons in a prospective cohort study (65 players, 102 player-seasons). Vert inertial measurement devices captured the jump load (jump frequency and jump height) from 21 088 daily player sessions, and knee complaints were reported in 3568 weekly OSTRC-O questionnaires. Mixed complementary log-log regression models described the probability of (i) experiencing symptoms if players were currently asymptomatic, (ii) worsening symptoms if players had symptoms, and (iii) recovery from knee complaints. Based on our causal assumptions, weekly jump load was modeled as the independent variable, adjusted for age (years), weight (kg), position on volleyball team, and past jump load. No certain evidence of an association was found between weekly jump load and probability of (i) knee complaints (p from 0.10 to 0.32 for three restricted cubic splines of load), (ii) worsening symptoms if the player already had symptoms (p from 0.11 to 0.97), (iii) recovery (p from 0.36 to 0.63). The probability of knee complaints was highest for above-average weekly jump load (~1.2% for an outside hitter with mean age and height) compared with low loads (~1%) and very high loads (→ ~ 0%). The association between jump load and knee complaints risk remains unclear. Small differences in risk across observed jump load levels were observed. It would likely require substantially increased sample sizes to detect this association with certainty.

Externally validated machine learning algorithm accurately predicts medial tibial stress syndrome in military trainees: a multicohort study

Objectives

Medial tibial stress syndrome (MTSS) is a common musculoskeletal injury in both sporting and military settings. No reliable treatments exist, and reoccurrence rates are high. Prevention of MTSS is critical to reducing operational burden. Therefore, this study aimed to build a decision-making model to predict the individual risk of MTSS within officer cadets and test the external validity of the model on a separate military population.

Design

Prospective cohort study.

Methods

This study collected a suite of key variables previously established for predicting MTSS. Data were obtained from 107 cadets (34 women and 73 men). A follow-up survey was conducted at 3 months to determine MTSS diagnoses. Six ensemble learning algorithms were deployed and trained five times on random stratified samples of 75% of the dataset. The resultant algorithms were tested on the remaining 25% of the dataset, with models then compared for accuracy. The most accurate new algorithm was tested on an unrelated data sample of 123 Australian Navy recruits to establish external validity of the model.

Results

Calibrated random forest modelling was the most accurate in identifying a diagnosis of MTSS; (area under curve (AUC)=98%, classification accuracy (CA)=96%). External validation on a sample of Navy recruits resulted in comparable accuracy; (AUC=95%, CA=94%). When the model was tested on the combined datasets, similar accuracy was achieved; (AUC=92%, CA=91%).

Conclusion

This model is highly accurate in predicting those who will develop MTSS. The model provides important preventive capacity which should be trialled as a risk management intervention.

Predictive modeling of the ratings of perceived exertion during training and competition in professional soccer players

OBJECTIVES

Evaluate the ability of predicting the ratings of perceived exertion from the external load variables in professional soccer players through a chronological perspective (i.e., past features values are considered additional features) through machine learning models by considering the playing position.

DESIGN

Prospective cohort study.

METHODS

Thirty-eight elite soccer players aged 19-27 years were observed during 151 training sessions, 44 matches across a full season. External load variables (58 derived from Global Positioning System and 30 from accelerometers) and the internal load derived from ratings of perceived exertion were collected for each player and each session and match. Machine learning models (linear regression, K-NN, decision trees, random forest, elastic net regression, XGBoost) were compared and interpreted in order to deepen the relationship between external load variables and ratings of perceived exertion according to the player position in a predictive perspective.

RESULTS

Application of the machine learning models on the dataset provided enough predictive power to reduce the Root Mean Squared Error of 60 % from dummy predictions. The most accurate models (Root Mean Squared Error ≈ 1.1 for random forest and = 1 for XGBoost) highlighted a memory effect in subsequent ratings of perceived exertion values. Past ratings of perceived exertion values over one month were the strongest predicting factors of ratings of perceived exertion as compared to various external load indicators.

CONCLUSIONS

The tree-based machine learning models showed statistically significant predictive ability, indicating valuable information for understanding the training load responses based on ratings of perceived exertion changes.

Healthcare providers have insufficient up-to-date knowledge of lower limb sports injuries, and their knowledge is similar to that of athletes

BACKGROUND

Being up-to-date with evidence-based knowledge of lower limb sports injuries is essential for Healthcare professionals (HCPs).

PURPOSE

To assess whether HCPs possess up-to-date knowledge of lower limb sports injuries by comparing their knowledge to that of athletes.

METHODS

With an expert panel, we developed an online quiz of 10 multiple-choice questions on various topics related to lower-limb sports injuries. Maximal score was 100. We used social media to invite HCPs (5 groups: Physiotherapists, Chiropractors, Medical Doctors, Trainers, and Other therapists) and athletes of all levels (amateur, semi-pro, and pro) to participate. We drafted the questions according to conclusions from the latest systematic reviews and meta-analyses.

RESULTS

1526 participants completed the study. Final quiz scores ranged from zero (n = 28, 1.8%) to 100 (n = 2, 0.1%) and were distributed normally with a mean score of 45.4 ± 20.6. None of the 6 groups' means surpassed the set threshold of 60 points. Multiple linear regressions of covariates indicated that age, gender, engagement in physical activity, learning hours per week, reading scientific journals, reading popular magazines and blogs, trainers, and other therapists' groups explained 19% of the variances (-5.914<β < 15.082, 0.000<p < 0.038).

CONCLUSIONS

HCPs have insufficient up-to-date knowledge of lower limb sports injuries, and their knowledge is similar to that of athletes of all levels. HCPs probably do not possess the proper tools to assess scientific literature Academic and sports medicine societies should look into ways to improve the scientific knowledge integration of HCPs.

"I lied a little bit." A qualitative study exploring the perspectives of elite Australian athletes on self-reported data

OBJECTIVES

Explore the perceptions and experiences of elite Australian athletes' engagement with reporting data in surveillance systems.

DESIGN

Qualitative Descriptive.

SETTING

Semi-structured interviews conducted using Zoom.

PARTICIPANTS

We recruited 13 elite Australian athletes competing at a national or international level for semi-structured interviews.

MAIN OUTCOME MEASURES

Audio recordings were transcribed using DeScript, checked for errors and imported into QSR NVIVO. Thematic analysis using QSR NVIVO was used to determine key themes from transcripts.

RESULTS

Thematic analysis uncovered four key themes: 'the paradox of reporting', 'data for data's sake', 'eyes on reporting' and 'athlete friendly reporting'.

CONCLUSION

Athletes perceived reporting as a burden and the athlete management system presented numerous technological difficulties which led to athletes to backfill data entries and compromise data accuracy. Athletes had little knowledge on how their data was used and managed and often received minimal feedback from staff accessing the data. Athletes were unaware of who has access to their data, which is of concern as sensitive information may be collected and athletes may be underage. As a result, many athletes chose to report dishonest data to avoid their performance being questioned.

Which of the Physiological vs. Critical Speed Is a Determinant of Modern Pentathlon 200 m Front Crawl Swimming Performance: The Influence of Protocol and Ergometer vs. Swimming Pool Conditions

BACKGROUND

Modern pentathlon includes horse riding, fencing, swimming, shooting and cross-country running. Events can last many hours during which the athletes face almost maximal energy and physiological demands, and fatigue. Early recognition and prevention of injuries and overuse syndromes can be achieved by refining the individual training loads. The purpose of the study was to determine which parameter could be the most accurate predictor of swimming working capacity determinants in pentathletes.

METHODS

Fourteen male pentathletes performed a continuous maximal incremental test in the swimming flume ergometer to measure peak oxygen uptake (VO₂peak), and five swimming tests in a 50 m swimming pool to detect critical velocity (CV); velocity at 2 and 4 mM·L^-1 of blood lactate (v2, v4) and energy cost (EC).

RESULTS

The 200 m swimming time was 2:18-2:32 m:s (340 FINA points). CV was 1.21 ± 0.04 m·s^-1, v2 was 1.14 ± 0.09 and v4 1.23 ± 0.08 m·s^-1. VO₂peak was 3540.1 ± 306.2 mL·min^-1 or 48.8 ± 4.6 mL·kg^-1·min^-1. EC at 1.24 m·s^-1 was 45.7 ± 2.4 mL·kg^-1·min^-1. Our main finding was the large correlation of CV with 200 m swimming performance; Conclusions: Among all the protocols analysed, CV is the most predictive and discriminative of individual swimming performance in this group of pentathletes. It appears as the most suitable test to constantly refine their swimming training loads for both performance enhancement and health promotion.

Is Cumulative Load Associated with Injuries in Youth Team Sport? A Systematic Review

Background

High cumulative external and internal load may predispose athletes to increased risk for injury across a variety of sports, competition levels, and age groups. However, evidence of an association between cumulative load and injury in youth sport remains inconclusive. The objective of this study was to determine the current evidence for cumulative load and injury risk relationships in youth team sport through a systematic review of the existing literature.

Methods

A systematic review of the literature was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Literature searches were conducted in PubMed, Web of Science, SCOPUS, and CINAHL for relevant articles published between January 2010 and April 2021. The authors conducted independent review and quality assessment of the eligible studies. Eleven articles evaluating youth (less than 18 years old) team sport were included for qualitative synthesis.

Results

Fifty-nine percent (n = 39/66) of the relationships assessed revealed an association between cumulative load and injury across the team sports studied, including the presence of load–injury associations in 84% (n = 16/19) of assessments in youth soccer. Of those relationships where an association was present, 79% (n = 31/39) were positive associations between cumulative load and injury. Risk of bias assessment scores ranged from three to six out of seven possible (median = 5) for cohort studies and from four to seven out of 10 possible (median = 5.5) for cross-sectional studies.

Conclusions

There is some evidence for a positive association between load and injury in youth team sport. Youth soccer was the most studied team sport, and a substantial number of positive load–injury associations were reported. Current evidence lacks consistency in the measures and metrics used in defining load–injury relationships.

Trial Registration PRISMA ID - CRD42020203622.

Association of Training and Game Loads to Injury Risk in Junior Male Elite Ice Hockey Players: A Prospective Cohort Study

BACKGROUND

Training and game loads are potential risk factors of injury in junior elite ice hockey, but the association of training and game loads to injuries is unknown.

PURPOSE

To investigate the association of chronic training and game loads to injury risk in junior male elite ice hockey players.

STUDY DESIGN

Cohort study; Level of evidence, 2.

METHODS

In this prospective cohort study, we monitored all health problems among 159 male junior ice hockey players (mean age, 16 years; range, 15-19 years) at sports-specific high schools during the 2018-2019 school year. Players reported their health problems every week using the Oslo Sports Trauma Research Center Overuse Questionnaire on Health Problems (OSTRC-H2). The number of training sessions and games was reported for 33 weeks. We calculated the previous 2-week difference in training/game loads as well as the cumulative training/game loads of the previous 2, 3, 4, and 6 weeks and explored potential associations between training/game loads and injury risk using mixed-effects logistic regression.

RESULTS

The players reported 133 acute injuries, 75 overuse injuries, and 162 illnesses in total, and an average of 8.8 (SD ±3.9) training sessions and 0.9 (SD ± 1.1) games per week. We found no association between the difference of the two previous weeks or the previous 2- 3- and 4-week cumulative, training or game load and acute injuries, nor the difference of the two previous weeks, or the previous 4- and 6-week cumulative, training or game load and overuse injuries (OR, ∼1.0; P > .05 in all models).

CONCLUSION

In the current study of junior elite ice hockey players, there was no evidence of an association between cumulative exposure to training/game loads and injury risk.

A Systematic Review of the Relationship between Workload and Injury Risk of Professional Male Soccer Players

The number of studies on the relationship between training and competition load and injury has increased exponentially in recent years, and it is also widely studied by researchers in the field of professional soccer. In order to provide practical guidance for workload management and injury prevention in professional athletes, this study provides a review of the literature on the effect of load on injury risk, injury prediction, and interpretation mechanisms. The results of the research show that: (1) It appears that short-term fixture congestion may increase the match injury incidence, while long-term fixture congestion may have no effect on both the overall injury incidence and the match injury incidence. (2) It is impossible to determine conclusively whether any global positioning system (GPS)-derived metrics (total distance, high-speed running distance, and acceleration) are associated with an increased risk of injury. (3) The acute:chronic workload ratio (ACWR) of the session rating of perceived exertion (s-RPE) may be significantly associated with the risk of non-contact injuries, but an ACWR threshold with a minimum risk of injury could not be obtained. (4) Based on the workload and fatigue recovery factors, artificial intelligence technology may possess good predictive power regarding injury risk.

The Influence of Weekly Sprint Volume and Maximal Velocity Exposures on Eccentric Hamstring Strength in Professional Football Players

Background: Hamstring strains are the most common moderate-major severity injuries in football. The majority of hamstring injuries occur during sprinting, with low eccentric hamstring strength being associated with an elevated risk. Objective: To examine the relationship between sprinting and eccentric hamstring strength by monitoring total weekly sprint distance and weekly efforts > 90% and >95% of maximum velocity. Methods: Fifty-eight professional male footballers were observed over one-and-a-half seasons. Players’ running was monitored during training and matches using GPS, and eccentric hamstring strength was measured weekly. Results: Weekly sprint distance (ρ = −0.13, p < 0.01) and weekly efforts >90% of maximum velocity (ρ = −0.08, p = 0.01) both displayed significant inverse relationships with the percentage change in eccentric hamstring strength; weekly efforts >95% of maximum velocity showed no relationship with hamstring strength (ρ = −0.02, p = 0.45). Only weekly efforts >90% of maximum velocity significantly influenced the mean percentage change in eccentric hamstring force, F(3,58) = 3.71, p = 0.01, with significant differences occurring when comparing 7−8 sprint efforts with 0−2 efforts (0.11%, p = 0.03) and 5−6 efforts (0.12%, p = 0.03). Conclusions: Eccentric hamstring strength levels significantly decrease when 7−8 weekly sprint efforts are completed at >90% of maximum velocity. Monitoring weekly sprint loading at velocities > 90% of maximum velocity may be valuable to help to reduce the risk of hamstring injuries in professional football.

Predicting Injury Risk Over Changes in Physical Activity in Children Using the Acute:Chronic Workload Ratio

Limited research exists on the relationship between changes in physical activity levels and injury in children. In this study, we investigated the prognostic relationship between changes in activity, measured by the acute:chronic workload ratio (ACWR), and injury in children. We used data from the Childhood Health, Activity, and Motor Performance School Study Denmark (2008-2014), a prospective cohort study of 1,660 children aged 6-17 years. We modeled the relationship between the uncoupled 5-week ACWR and injury, defined as patient-reported musculoskeletal pain, using generalized additive mixed models. These methods accounted for repeated measures, and they improved model fit and precision compared with previous studies that used logistic models. The prognostic model predicted an injury risk of approximately 3% between decreases in activity level of up to 60% and increases of up to 30%. Predicted risk was lower when activity decreased by more than 60% (minimum of 0.5% with no recreational activity). Predicted risk was higher when activity increased by more than 30% (4.5% with a 3-fold increase in activity). Girls were at significantly higher risk of injury than boys. We observed similar patterns but lower absolute risks when we restricted the outcome to clinician-diagnosed injury. Predicted increases in injury risk with increasing activity were much lower than those of previous studies carried out in adults.

Association Between Spikes in External Training Load and Shoulder Injuries in Competitive Adolescent Tennis Players: The SMASH Cohort Study

BACKGROUND

Few studies have examined the association between the acute:chronic workload ratio (ACWR) and complaints/injuries in young tennis players. Primary aims of this study were to investigate if accumulated external workload "spikes" in ACWR of tennis training, match play, and fitness training, and to see if high or low workload/age ratio were associated with the rate of shoulder complaints/injuries in competitive adolescent tennis players. Additional aims were to report the incidence of complaints/injuries stratified by sex and level of play and to describe shoulder injury characteristics.

HYPOTHESIS

Rapid increases in external workload are associated with the incidence of shoulder complaints and injuries.

STUDY DESIGN

A cohort study.

LEVEL OF EVIDENCE

Level 3.

METHODS

At baseline, 301 adolescent competitive tennis players, 13 to 19 years, were screened and followed weekly for 52 weeks with questionnaires, in the years 2018 to 2019. Information about time-varying accumulated external workload spikes (uncoupled ACWR >1.3), and workload/age ratio, in 252 uninjured players were used in Cox regression analyses with the outcomes shoulder complaints (≥20) and injuries (≥40) (Oslo Sports Trauma Research Center Overuse Injury Questionnaire).

RESULTS

For each additional workload spike in tennis training/match play, the hazard rate ratio (HRR) was 1.26 (95% CI, 1.13-1.40) for a shoulder complaint and 1.26 (95% CI, 1.15-1.39) for a shoulder injury. The HRR for fitness training was 1.11 (95% CI, 1.02-1.20) for a shoulder complaint and 1.18 (95% CI, 1.09-1.27) for a shoulder injury. Workload/age ratio was not associated with the rate of shoulder complaints or injuries.

CONCLUSION

Accumulated external workload spikes of tennis training, match play, and/or fitness training are associated with a higher rate of shoulder complaints and shoulder injuries in competitive adolescent tennis players.

CLINICAL RELEVANCE

Consistency in training load on a weekly basis is most likely more beneficial for adolescent tennis players regarding shoulder complaints/injuries than a training schedule comprising rapid increases (ie, spikes) in workload.

Chronic Workload, Subjective Arm Health, and Throwing Injury in High School Baseball Players: 3-Year Retrospective Pilot Study

BACKGROUND

Baseball workloads are monitored by pitch counts, appearances, innings per appearance, ball velocity, and distance, whereas current workload standards neglect throws made during nongame situations. The association between total workloads, subjective measures, and injury in baseball is poorly understood. The question remains whether baseball athletes are at higher risk of injury by throwing more often or if they generate injury resilience when appropriately transitioned into the higher demands of throwing.

HYPOTHESIS

Increased chronic load, along with subjective arm health measures, are related to decreased injury risk.

STUDY DESIGN

Clinical research.

LEVEL OF EVIDENCE

Level 3.

METHODS

A total of 49 male baseball players (age 17.9 ± 0.4 years, height 181.8 ± 6.8 cm, body mass 80.6 ± 9.1 kg) competing at the varsity high school level were included in this 3-year retrospective data analysis from 2016 to 2019. Players wore the motusTHROW sleeve and sensor during all throwing activities.

RESULTS

A total of 898,492 throws and 9455 athletic exposures were captured with the motusTHROW sensors. There were 24 injuries recorded throughout the 3-year analysis, with 11 throwing-related and 13 non-throwing related injuries. Results of the 1-way analysis of variance found chronic load was significantly related to throwing-injury occurrence (P < 0.01). Six of the throwing-related injuries occurred when athletes had a chronic load greater than 11.3, marking 75th percentile across all observations. There was a relationship between arm health and throwing arm-related injury occurrence (P < 0.01). Higher chronic load was associated with increased throwing-related injuries even when adjusted for arm health (P = 0.01). Specifically, injuries were more likely to occur in pitchers (either as a combination player or pitcher only) with a chronic load greater than 9.2.

CONCLUSION

This study revealed a significant relationship between chronic load, subjective arm health, and throwing-related injury in varsity high school baseball players. Contrary to our hypothesis, increased chronic load was associated with increased injury risk. However, subjective arm health measures remain a relevant factor in assessing injury risk. Normative data for this population also provide key information around positional demands along with overall demands of the sport during the competitive season and off-season.

Comparison of player-dependent and independent high-speed running thresholds to model injury risk in football

High-speed running (HSR) loads have been linked with non-contact injury risks in team-sports. This study investigated whether player-specific speed zones, reflecting individual fitness characteristics, impact the associations between non-contact injury and acute and chronic HSR loads. Semi-professional soccer players from two clubs (n = 47) were tracked over two seasons using 10 Hz GPS (5552 observations). HSR distances were calculated arbitrarily (≥5.5 m·s^-1), and in an individualised fashion based on the final speed of the 30-15 intermittent fitness test. Cumulative running loads were represented by exponentially weighted moving averages with 7-(acute) and 28-day (chronic) decay parameters. Physiotherapists collected non-contact, lower-limb, time-loss injury data (n = 101). Injury models using session type (training vs matches), coach, as well as arbitrary or individualised running loads were constructed via mixed-effect logistic regression. Session type had the largest effect on injury (training vs match OR = 0.28; 95%CI:0.17-0.44). Variations in individualised or arbitrary acute and chronic HSR loads within the mid-range of the observed data had negligible effects on predicted injury risk. However, the uncertainty of estimated effects at extreme values of acute and chronic HSR loads prevented any conclusive findings. Therefore, the efficacy of using customised speed thresholds in quantifying load for injury risk mitigation purposes remains unclear.

External Training Load and the Association With Back Pain in Competitive Adolescent Tennis Players: Results From the SMASH Cohort Study

Background:

In young tennis players, high loads on the spine and high training volumes in relation to age are associated with a high lifetime prevalence of back pain. The primary aim of this study was to investigate if accumulated external workload “spikes” in the acute:chronic workload ratio (ACWR) of tennis training, match play, and fitness training, and if high or low workload/age ratio were associated with back pain events in competitive adolescent tennis players. Additional aims were to report the incidence of back pain stratified by sex and level of play and to describe the characteristics of players with back pain.

Hypothesis:

Rapid increases in external workload are associated with the incidence of back pain.

Study Design:

Cohort study of 198 competitive tennis players, 13 to 19 years, with a weekly follow-up for 52 consecutive weeks.

Level of Evidence:

Level 3.

Methods:

Accumulated external workload spikes (uncoupled ACWR >1.3), and the workload/age ratio, were time-varying exposures in Cox regression analyses with the outcome back pain (pain intensity ≥2/10 in the lower back and/or in the upper back/neck with a pain-related disability).

Results:

For each additional workload spike in tennis training/match play, the hazard rate ratio (HRR) was 1.17 (95% CI, 1.06-1.28) for back pain. The corresponding HRR for fitness training was 1.13 (95% CI, 1.05-1.22). Training workload/age ratio was not related to back pain.

Conclusion:

Accumulated external workload spikes of tennis training, match play, and/or fitness training are associated with a higher rate of back pain events in competitive adolescent tennis players.

Clinical Relevance:

Back pain is a troublesome clinical problem that may affect the performance of talented young tennis players. Structuring the training schedule to minimize rapid increases (ie, spikes) of training load on a weekly basis may enhance performance and reduce back pain in adolescent tennis players.

Use of monitoring technology and injury incidence among recreational runners: a cross-sectional study

Background

Monitoring technology is increasingly accessible to recreational runners. Our aim was to examine patterns of technology use in recreational runners, and its potential association with injury.

Methods

We conducted a cross-sectional questionnaire study in a sample of adult runners. Recruitment took place at three different 5 km parkrun event across Northern Ireland. Demographics, technology use, running behaviour and running-related injury (RRI) history were examined. Regression analyses were performed to determine relationships between variables.

Results

Responses were obtained from 192 of 483 eligible finishers (39.8% response rate). Average age was 45.9 years (SD 10.3), with males (47.1 years SD 9.7) slightly older than females (44.8 years SD 10.8). On average, participants ran 3.0 days per week (SD 1.3), with an average weekly distance of 22.6 km (SD 19.7). Males typically ran further (MD 6.2 km/week; 95% CI 0.4 to 12.0) than females. Monitoring technology was used by 87.4% (153/175); with GPS watches the most common device (87.6% (134/153)). Runners using monitoring technology ran further (MD 14.4 km/week; 95% CI 10.3 to 18.5) and more frequently (MD 1.3 days/week; 95% CI 0.7 to 1.9) than those who did not use monitoring technology. There was no significant difference in average age between runners who used monitoring technology and those who did not (MD 4.0 years; 95% CI −0.7 to 8.7). RRI was reported by 40.6% (71/175) of participants in the previous 12 months. In a univariate analysis, none of the selected predictors (age, number of days run per week, distance run per week, or usage of technology to modify training pattern) (p > 0.1) were associated with RRI.

Conclusions

This study found a high prevalence of monitoring technology usage among recreational runners. While the incidence of RRI remains high, it is not associated with the usage of monitoring technology. Further prospective research should examine if monitoring technology can reduce RRI incidence among recreational runners in future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13102-021-00347-4.

Detecting Injury Risk Factors with Algorithmic Models in Elite Women's Pathway Cricket

This exploratory retrospective cohort analysis aimed to explore how algorithmic models may be able to identify important risk factors that may otherwise not have been apparent. Their association with injury was then assessed with more conventional data models. Participants were players registered on the England and Wales Cricket Board women's international development pathway (n=17) from April 2018 to August 2019 aged between 14-23 years (mean 18.2±1.9) at the start of the study period. Two supervised learning techniques (a decision tree and random forest with traditional and conditional algorithms) and generalised linear mixed effect models explored associations between risk factors and injury. The supervised learning models did not predict injury (decision tree and random forest area under the curve [AUC] of 0.66 and 0.72 for conditional algorithms) but did identify important risk factors. The best-fitting generalised linear mixed effect model for predicting injury (Akaike Information Criteria [AIC]=843.94, conditional r-squared=0.58) contained smoothed differential 7-day load (P<0.001), average broad jump scores (P<0.001) and 20 m speed (P<0.001). Algorithmic models identified novel injury risk factors in this population, which can guide practice and future confirmatory studies can now investigate.

Lower-limb injury in elite Australian football: A narrative review of kinanthropometric and physical risk factors

OBJECTIVE

This review aims to provide a succinct and critical analysis of the current physical and mechanical demands of elite Australian football while examining lower-limb injury and the associated physical and kinanthropometric risk factors.

METHODS

MEDLINE, PubMed, Web of Science and SPORTSDiscus electronic databases were searched for studies that investigated the playing demands, injury trends, and physical and kinanthropometric injury risk factors of elite Australian football. Articles from similar team sports including soccer and rugby (union and league) were also included.

RESULTS

While the physical demands of elite AF have steadied over the past decade, injury rates continue to rise with more than two-thirds of all injuries affecting the lower-limbs. Body composition and musculoskeletal morphological assessments are regularly adopted in many sporting settings with current research suggesting high and low body mass are both associated with heightened injury risk. However, more extensive investigations are required to determine whether the proportions of muscle and fat are linked. Repeated assessment of musculoskeletal morphology may also provide further insight into stress fracture rates.

CONCLUSIONS

While kinanthropometric and physical attributes are highly valued within elite sporting environments, establishing a deeper connection with injury may provide practitioners with more insight into current injury trends.

Not straightforward: modelling non-linearity in training load and injury research

OBJECTIVES

To determine whether the relationship between training load and injury risk is non-linear and investigate ways of handling non-linearity.

METHODS

We analysed daily training load and injury data from three cohorts: Norwegian elite U-19 football (n=81, 55% male, mean age 17 years (SD 1)), Norwegian Premier League football (n=36, 100% male, mean age 26 years (SD 4)) and elite youth handball (n=205, 36% male, mean age 17 years (SD 1)). The relationship between session rating of perceived exertion (sRPE) and probability of injury was estimated with restricted cubic splines in mixed-effects logistic regression models. Simulations were carried out to compare the ability of seven methods to model non-linear relationships, using visualisations, root-mean-squared error and coverage of prediction intervals as performance metrics.

RESULTS

No relationships were identified in the football cohorts; however, a J-shaped relationship was found between sRPE and the probability of injury on the same day for elite youth handball players (p<0.001). In the simulations, the only methods capable of non-linear modelling relationships were the quadratic model, fractional polynomials and restricted cubic splines.

CONCLUSION

The relationship between training load and injury risk should be assumed to be non-linear. Future research should apply appropriate methods to account for non-linearity, such as fractional polynomials or restricted cubic splines. We propose a guide for which method(s) to use in a range of different situations.

Facilitators and barriers for implementation of a load management intervention in football

BACKGROUND

In a recent randomised controlled trial, we found that a commonly used training load management approach was not effective in preventing injuries and illnesses in Norwegian elite youth footballers.

AIM

To investigate players' and coaches' barriers and facilitators to a load management approach to prevent injuries and illnesses and their attitudes and beliefs of load management and injuries and illnesses in general.

METHODS

We asked players and coaches about their views on injury risk in football, the benefits and limitations of load management in general and implementation of load management in football. The questionnaires used were based on similar studies using the Reach, Effectiveness, Adoption, Implementation and Maintenance framework.

RESULTS

We recorded answers from 250 players and 17 coaches. Most players (88%) reported that scientific evidence showing improved performance from the intervention measures is a key facilitator to completing the intervention. Similarly, coaches reported that the most important facilitator was scientific evidence that the preventive measures were effective (100%). Players reported that the coach's attitude to preventive measures was important (86%), and similarly, 88% of coaches reported that the player's attitude was important.

CONCLUSIONS

By having a mutual positive attitude towards the intervention, players and coaches can positively contribute to each other's motivation and compliance. Both players and coaches reported scientific evidence for load management having injury-preventive and performance-enhancing effect and being time efficient as important facilitators.

TRIAL REGISTRATION NUMBER

Trial registration number.

Training Load Monitoring Considerations for Female Gaelic Team Sports: From Theory to Practice

Athlete monitoring enables sports science practitioners to collect information to determine how athletes respond to training loads (TL) and the demands of competition. To date, recommendations for females are often adapted from their male counterparts. There is currently limited information available on TL monitoring in female Gaelic team sports in Ireland. The collection and analysis of female athlete monitoring data can provide valuable information to support the development of female team sports. Athletic monitoring can also support practitioners to help minimize risk of excessive TL and optimize potential athletic performance. The aims of this narrative review are to provide: (i) an overview of TL athlete monitoring in female team sports, (ii) a discussion of the potential metrics and tools used to monitor external TL and internal TL, (iii) the advantages and disadvantages of TL modalities for use in Gaelic team sports, and (iv) practical considerations on how to monitor TL to aid in the determination of meaningful change with female Gaelic team sports athletes.

Training Load Monitoring in Amateur Rugby Union: A Survey of Current Practices

ABSTRACT

Griffin, A, Kenny, IC, Comyns, TM, and Lyons, M. Training load monitoring in amateur Rugby Union: A survey of current practices. J Strength Cond Res 35(6): 1568-1575, 2021-Amateur Rugby Union has an inherent risk of injury that is associated with detrimental effects on player welfare and team performance. Training load (TL) is a modifiable risk factor that, when monitored, may provide strength and conditioning (S&C) coaches with opportunities to reduce the risk of injury. The purpose of this study was to explore TL monitoring practices used by S&C coaches working with male and female amateur adult Rugby Union teams and their rationale for using such. Thirty-three (n = 31 male and n = 2 female) S&C coaches representing 62% of the total number of male clubs and 71% of female clubs, playing at the highest national amateur level, participated in the study by completing an online survey. Seventy-three percent of respondents stated that they monitor TL. The most common method of recording TL was the session rating of perceived exertion (sRPE), used in 83% of monitoring systems. Thirty-three percent of the S&C coaches surveyed use the sRPE data to calculate the acute:chronic workload ratio (ACWR) for highlighting when players are at risk of injury. This study is the first of its kind to exclusively examine the TL monitoring practices of S&C coaches working with amateur adult Rugby Union teams. Thirteen S&C coaches responded to the open-ended question and 3 higher order themes were highlighted: (a) communication with players (b) support from other staff and (c) limiting factors.

The Association Between the Acute:Chronic Workload Ratio and Running-Related Injuries in Dutch Runners: A Prospective Cohort Study

OBJECTIVE

To investigate the association between the acute:chronic workload ratio (ACWR) and running-related injuries (RRI).

METHODS

This is a secondary analysis using a database composed of data from three studies conducted with the same RRI surveillance system. Longitudinal data comprising running exposure (workload) and RRI were collected biweekly during the respective cohorts' follow-up (18-65 weeks). ACWR was calculated as the most recent (i.e., acute) external workload (last 2 weeks) divided by the average external (i.e., chronic) workload of the last 4, 6, 8, 10 and 12 weeks. Three methods were used to calculate the ACWR: uncoupled, coupled and exponentially weighted moving averages (EWMA). Bayesian logistic mixed models were used to analyse the data.

RESULTS

The sample was composed of 435 runners. Runners whose ACWR was under 0.70 had about 10% predicted probability of sustaining RRI (9.6%; 95% credible interval [CrI] 7.5-12.4), while those whose ACWR was higher than 1.38 had about 1% predicted probability of sustaining RRI (1.3%; 95% CrI 0.7-1.7). The association between the ACWR and RRI was significant, varying from a small to a moderate association (1-10%). The higher the ACWR, the lower the RRI risk.

CONCLUSIONS

The ACWR showed an inversely proportional association with RRI risk that can be represented by a smooth L-shaped, second-order, polynomial decay curve. The ACWR using hours or kilometres yielded similar results. The coupled and uncoupled methods revealed similar associations with RRIs. The uncoupled method presented the best discrimination for ACWR strata. The EWMA method yielded sparse and non-significant results.

A systematic review of small sided games within rugby: Acute and chronic effects of constraints manipulation

Small-sided games is a commonly used training method to develop technical, tactical and physical qualities concurrently. However, a review of small-sided games in rugby football codes (e.g. rugby union, rugby league) is not available. This systematic review aims to investigate the acute responses and chronic adaptations of small-sided games within rugby football codes considering the constraints applied. Four electronical databases were systematically searched until August 2020. Acute and chronic studies investigating rugby football codes small-sided games, with healthy amateur and professional athletes were included. Twenty studies were eventually included: 4 acute and 1 chronic in rugby union, 13 acute and 2 chronic in rugby league. Acute studies investigated task and individual constraints. Chronic studies showed that small-sided games would be an effective training method to improve physical performance. Current research in rugby football codes is heavily biased towards investigating how manipulating constraints can affect the physical characteristics of small-sided games, with limited literature investigating the effect on technical skills, and no studies investigating tactical behaviour. Future research is needed to evidence the effects of constraint manipulation on technical and tactical behaviour of rugby football players in small-sided games, in addition to physical characteristics.

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.

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.

Relationships Between Different Internal and External Training Load Variables and Elite International Women's Basketball Performance

PURPOSE

To investigate the relationships between internal and external training load (TL) metrics with elite international women's basketball performance.

METHODS

Sessional ratings of perceived exertion, PlayerLoad™/minute, and training duration were collected from 13 elite international-level female basketball athletes (age 29.0 [3.7] y, stature 186.0 [9.8] cm, body mass 77.9 [11.6] kg) during the 18 weeks prior to the International Basketball Federation Olympic qualifying event for the 2016 Rio Olympic Games. Training stress balance, differential load, and the training efficiency index were calculated with 3 different smoothing methods. These TL metrics and their change in the last 21 days prior to competition were examined for their relationship to competition performance as coach ratings of performance.

RESULTS

For a number of TL variables, there were consistent significant small to moderate correlations with performance and significant small to large differences between successful and unsuccessful performances. However, these differences were only evident for external TL when using exponentially weighted moving averages to calculate TL. The variable that seemed most sensitive to performance was the change in training efficiency index in the last 21 days prior to competition (performance r = .47-.56, P < .001 and difference between successful and unsuccessful performance P < .001, f2 = 0.305-0.431).

CONCLUSIONS

Internal and external TL variables were correlated with performance and distinguished between successful and unsuccessful performances among the same players during international women's basketball games. Manipulating TL in the last 3 weeks prior to competition may be worthwhile for basketball players' performance, especially in internal TL.

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.

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.

More than a Metric: How Training Load is Used in Elite Sport for Athlete Management

Training load monitoring is a core aspect of modern-day sport science practice. Collecting, cleaning, analysing, interpreting, and disseminating load data is usually undertaken with a view to improve player performance and/or manage injury risk. To target these outcomes, practitioners attempt to optimise load at different stages throughout the training process, like adjusting individual sessions, planning day-to-day, periodising the season, and managing athletes with a long-term view. With greater investment in training load monitoring comes greater expectations, as stakeholders count on practitioners to transform data into informed, meaningful decisions. In this editorial we highlight how training load monitoring has many potential applications and cannot be simply reduced to one metric and/or calculation. With experience across a variety of sporting backgrounds, this editorial details the challenges and contextual factors that must be considered when interpreting such data. It further demonstrates the need for those working with athletes to develop strong communication channels with all stakeholders in the decision-making process. Importantly, this editorial highlights the complexity associated with using training load for managing injury risk and explores the potential for framing training load with a performance and training progression mindset.

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.

Consensus statements that fail to recognise dissent are flawed by design: a narrative review with 10 suggested improvements

Consensus statements have the potential to be very influential. Recently, such statements in sport and exercise medicine appear more prescriptive, strongly recommending particular approaches to research or treatment. In 2020, a statement on methods for reporting sport injury surveillance studies included an extension to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines; STROBE guidelines are now official requirements for many journals. This suggests that investigators who use methods outside of these guidelines may have difficulty publishing their results. By definition, consensus is not unanimity, and consensus recommendations are sometimes considered flawed at a later date. This is expected as a discipline benefits from new knowledge. However, the consensus methods themselves may also inadvertently suppress contrary-but valid-opinions. I point to a different model for consensus meetings and statements that embraces dissenting opinions and is more transparent than common current methods in sport and exercise medicine. The method, based on how Supreme Courts function in many countries, allows for both majority and one or more minority opinions. I illustrate how a consensus statement might be written using examples from four previous sport and exercise medicine consensus statements. By adopting the 'Supreme Court' approach, important disagreements about the strength and interpretation of evidence will be far more visible than is currently the case in most consensus meetings. The benefit of the Supreme Court model is that it will ensure that clinicians, researchers and journals are not inappropriately influenced by recommendations from consensus statements where uncertainty remains.

Association of acute and chronic workloads with injury risk in high-performance junior tennis players

This study examined the association and predictive ability of several markers of internal workload on risk of injury in high-performance junior tennis players. Fifteen young, high-level tennis players (9 males, 6 females; age: 17.2 ± 1.1 years; height: 178.5 ± 8.7 cm; mass: 68.1 ± 4.8 kg) participated in this investigation. Data on injury epidemiology and internal workload during training were obtained for one competitive season. The session-rating of perceived exertion (s-RPE) was used to calculate internal workload markers in absolute (acute workload and chronic workload for 2-weeks, 3-weeks and 4-weeks) and relative terms (acute:chronic workload ratios [ACWR] for 2-weeks, 3-weeks and 4-weeks). Associations and diagnostic power for predicting tennis injuries were examined through generalised estimating equations and receiver operating characteristics analyses. During the season, a total of 40 injuries were recorded, corresponding to 3.5 injuries per 1000 h of tennis practice. The acute workload was highly associated with injury incidence (P=0.04), as injury risk increased by 1.62 times (95% CI: 1.01-2.62) for every increase of 1858.7 arbitrary units (AU) of the workload during the most recent training week. However, acute workload was a poor predictor of injury, and associations between injury and internal workload markers were weak (all P>0.05). These findings demonstrate an association between high values of acute workload and the risk of injury in high-level tennis players. However, a high acute workload is only one of the many factors associated with injury, and by itself, has low predictive ability for injury.

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.

The Training-Performance Puzzle: How Can the Past Inform Future Training Directions?

Over the past 20 years, research on the training-load-injury relationship has grown exponentially. With the benefit of more data, our understanding of the training-performance puzzle has improved. What were we thinking 20 years ago, and how has our thinking changed over time? Although early investigators attributed overuse injuries to excessive training loads, it has become clear that rapid spikes in training load, above what an athlete is accustomed, explain (at least in part) a large proportion of injuries. In this respect, it appears that overuse injuries may arise from athletes being underprepared for the load they are about to perform. However, a question of interest to both athletic trainers (ATs) and researchers is why some athletes sustain injury at low training loads, while others can tolerate much greater training loads? A higher chronic training load and well-developed aerobic fitness and lower body strength appear to moderate the training-injury relationship and provide a protective effect against spikes in load. The training-performance puzzle is complex and dynamic-at any given time, multiple inputs to injury and performance exist. The challenge facing researchers is obtaining large enough longitudinal data sets to capture the time-varying nature of physiological and musculoskeletal capacities and training-load data to adequately inform injury-prevention efforts. The training-performance puzzle can be solved, but it will take collaboration between researchers and clinicians as well as an understanding that efficacy (ie, how training load affects performance and injury in an idealized or controlled setting) does not equate to effectiveness (ie, how training load affects performance and injury in the real-world setting, where many variables cannot be controlled).

Does an Optimal Relationship Between Injury Risk and Workload Represented by the "Sweet Spot" Really Exist? An Example From Elite French Soccer Players and Pentathletes

Objective

To examine the relationships between the occurrence and severity of injuries using three workload ratios (ACWR, EWMA, REDI) in elite female soccer players and international male and female pentathletes.

Materials and Methods

Female soccer players in the U16 to U18 national French teams (n = 24) and international athletes (n = 12, 4 women and 8 men) in the French modern pentathlon team were monitored throughout an entire season. The Acute Chronic Workload Ratio (ACWR), the Exponentially Weighted Moving Averages (EWMA), and the Robust Exponential Decreasing Index (REDI) were calculated for internal load by the ROE method in soccer and external load in pentathlon. The occurrence and severity of injuries (determined according to time-loss) were quantified in the sweet spot zone [0.8; 1.3] and compared to the other zones of load variation: [0; 0.8], [1.3; 1.5], [1.5; +8], using the three ratios.

Results

Over the study period, a total of sixty-six injuries (2.75 per athlete) were reported in the soccer players and twelve in pentathletes (1 per athlete). The cumulative severity of all injuries was 788 days lost in soccer and 36 in pentathlon: respectively, 11.9 days lost per injury in soccer player and 3.0 per pentathlete. The mean values across the three methods in soccer showed a higher number of injuries detected in the [0; 0.8] workload ratio zone: 22.3 ± 6.4. They were 17.3 ± 3.5 in the sweet spot ([0.8-1.3] zone) and 17.6 ± 5.5 in the [1.5; +8] zone. In comparison to the [1.5; +8] zone, soccer players reported a higher number of days lost to injuries in the presumed sweet spot and in the [0-0.8] zone: 204.7 ± 28.7 and 275.0 ± 120.7 days, respectively. In pentathletes, ten of the twelve injuries (83.3%) occurred in the presumed sweet spot. REDI was the only method capable of tracking workloads over all-time series.

Conclusion

In the present cohort of elite soccer players and pentathletes, acute chronic workload calculations showed an association with injury occurrence and severity but did not provide evidence supporting existence of a sweet spot diminishing injury risk.

Player Monitoring in Professional Soccer: Spikes in Acute:Chronic Workload Are Dissociated From Injury Occurrence

This study aimed to determine whether spikes in acute:chronic workload ratio (ACWR) are associated with injury incidence, and to examine the differences in external load due to greater or lesser exposure to matches and the long-term effects of the load during a chronic seasonal period. Fifteen professional soccer players belonging to the squad of a European Champions League club were enrolled in this study. External training and match load were assessed from all athletes using a global positioning system (GPS). We calculated the uncoupled ACWR for 10 consecutive competitive microcycles. Injuries were identified and determined by the days of absence. The differences in external load were determined using a linear mixed-model approach. In addition to the null hypothesis testing, the effect size was calculated. Thirteen athletes who did not suffer an injury exceeded several times the critical threshold of an ACWR > 1.5. This is equivalent to 1 player exceeding the critical threshold for ACWR in total distance (TD), 2 players for ACWR at distance covered above moderate speed (MSD), 2 players for ACWR at distance covered above high speed (HSD), 2 players for ACWR at distance covered above very high speed (VHSD), and 2 players for ACWR in DC at sprint per week. One athlete experienced a non-contact muscle strain injury and another a contact -injury manifested as a concussion; both athletes document an ACWR <1.5 within the 4 weeks prior to the injury event. Players with lesser participation in official games covered lower TD (-19.6%, very-large ES), MSD (-24.8%, very-large ES), HSD (-25.1%, moderate ES), VHSD (-25.5%, moderate ES), and DC at sprint (-30.6%, moderate ES) over the course of the 10-weeks period in comparison with the players with greater participation in official games. The present study demonstrated that spikes in the ACWR were not related to a subsequent injury occurrence in professional soccer players. Differences in participation in official games caused significant imbalances in the chronic external loads between players in a squad, which should be minimized in training sessions in order to prevent substantial changes in workload for those who usually do not play.

Epidemiology of injury and illness in 153 Australian international-level rowers over eight international seasons

Aim

To report the epidemiology of injury and illness in elite rowers over eight seasons (two Olympiads).

Methods

All athletes selected to the Australian Rowing Team between 2009 and 2016 were monitored prospectively under surveillance for injury and illness. The incidence and burden of injury and illness were calculated per 1000 athlete days (ADs). The body area, mechanism and type of all injuries were recorded and followed until the resumption of full training. We used interrupted time series analyses to examine the association between fixed and dynamic ergometer testing on rowers’ injury rates. Time lost from illness was also recorded.

Results

All 153 rowers selected over eight seasons were observed for 48 611 AD. 270 injuries occurred with an incidence of 4.1–6.4 injuries per 1000 AD. Training days lost totalled 4522 (9.2% AD). The most frequent area injured was the lumbar region (84 cases, 1.7% AD) but the greatest burden was from chest wall injuries (64 cases, 2.6% AD.) Overuse injuries (n=224, 83%) were more frequent than acute injuries (n=42, 15%). The most common activity at the time of injury was on-water rowing training (n=191, 68). Female rowers were at 1.4 times the relative risk of chest wall injuries than male rowers; they had half the relative risk of lumbar injuries of male rowers. The implementation of a dynamic ergometers testing policy (Concept II on sliders) was positively associated with a lower incidence and burden of low back injury compared with fixed ergometers (Concept II). Illness accounted for the greatest number of case presentations (128, 32.2% cases, 1.2% AD).

Conclusions

Chest wall and lumbar injuries caused training time loss. Policy decisions regarding ergometer testing modality were associated with lumbar injury rates. As in many sports, illness burden has been under-recognised in elite Australian rowers.

Variations of Workload Indices Prior to Injuries: A Study in Trail Runners

The purpose of this study was to compare the variations of weekly workload indices of internal and external load measures across the three weeks prior to injury occurrences in trail runners. Twenty-five trail runners (age: 36.23 ± 8.30 years old; body mass: 67.24 ± 5.97 kg; height: 172.12 ± 5.12 cm) were monitored daily for 52 weeks using global positioning systems (GPSs) to determine the total distance covered. Additionally, a rate of perceived exertion (RPE) scale was applied to determine session-RPE (sRPE: RPE multiplied by training time). The accumulated load (AL), acute: chronic workload ratio (ACWR), training monotony (TM), and training strain (TS) indices were calculated weekly for each runner. During the period of analysis, the injury occurrences were recorded. The differences were observed in AL and ACWR for sRPE and training time were significantly greater during the injury week when compared to the previous weeks. Similar evidence was found in TM and TS indices for sRPE, training time, and total distance. Furthermore, no meaningful differences were observed in AL and ACWR for total distance in the weeks prior to injury occurrence. Nevertheless, significant between-subjects variability was found, and this should be carefully considered. For that reason, an individualized analysis of the workload dynamics is recommended, avoiding greater spikes in load by aiming to keep a progressive increment of load without consequences for injury risk.