To Couple or not to Couple? For Acute:Chronic Workload Ratios and Injury Risk, Does it Really Matter?

Wearable Devices and Digital Biomarkers for Optimizing Training Tolerances and Athlete Performance: A Case Study of a National Collegiate Athletic Association Division III Soccer Team over a One-Year Period

Wearable devices in sports have been used at the professional and higher collegiate levels, but not much research has been conducted at lower collegiate division levels. The objective of this retrospective study was to gather big data using the Catapult wearable technology, develop an algorithm for musculoskeletal modeling, and longitudinally determine the workloads of male college soccer (football) athletes at the Division III (DIII) level over the course of a 12-week season. The results showed that over the course of a season, (1) the average match workload (432 ± 47.7) was 1.5× greater than the average training workload (252.9 ± 23.3) for all positions, (2) the forward position showed the lowest workloads throughout the season, and (3) the highest mean workload was in week 8 (370.1 ± 177.2), while the lowest was in week 4 (219.1 ± 26.4). These results provide the impetus to enable the interoperability of data gathered from wearable devices into data management systems for optimizing performance and health.

Workload Comparison of Contemporary Interval Throwing Programs and a Novel Optimized Program for Baseball Pitchers

Background

In the rehabilitation of injured baseball pitchers, there is lack of consensus on how to guide a player back to pitching. It is unknown how different contemporary interval throwing programs (ITPs) progress in the amount of throwing workload.

Purposes

To 1) evaluate three prominent ITPs commonly employed in baseball pitcher rehabilitation and assess whether these ITPs produce training loads that increase in a controlled, graduated manner and 2) devise an ITP that produced training loads which increased steadily over time.

Study Design

Cross-sectional study.

Methods

Three publicly available ITPs from prominent sports medicine institutions were analyzed. Elbow varus torque per throw was calculated from a 2nd order polynomial regression based upon a relationship between recorded torque measurements and throwing distance measured from a database of 111,196 throws. The relative rate of workload increase was measured as an acute:chronic workload ratio (ACWR). For each ITP, throw counts, daily/acute/chronic workloads, and ACWR were calculated and plotted over time. Finally, an original ITP was devised based upon a computational model that gradually increases ACWR over time and finished with an optimal chronic workload.

Results

Each ITP exhibited a unique progression of throwing distances, quantities, and days to create different workload profiles. The three ITPs had throwing schedules ranging from 136 days to 187 days, ACWR spiked above or fell below a literature-defined "safe" range (i.e. 0.7 - 1.3) 19, 21, and 23 times. A novel ITP, predicated on a 146-day schedule and with a final chronic workload of 14.2, was designed to have no spikes outside of the safe range.

Conclusion

Existing ITPs widely utilized for rehabilitation of baseball pitchers exhibit significantly inconsistent variation in the rate of throwing load progression. Computational modeling may facilitate more incremental workload progression in ITPs, thereby reducing injury during rehabilitation and more efficiently condition a pitcher for return to competition.

Level of Evidence

3b.

Overtraining Syndrome as a Risk Factor for Bone Stress Injuries among Paralympic Athletes

Background and Objectives: In this review, we have explored the relationship between overtraining syndrome (OTS) and bone stress injuries among paralympic athletes. OTS is a complex condition that arises from an imbalance between training volume, nutrition, and recovery time, leading to significant negative effects on paralympic athlete's performance and overall well-being. On the other hand, bone stress injuries occur when abnormal and repetitive loading is applied to normal bone, resulting in microdamage accumulation and potential. The prevalence of overtraining syndrome and bone stress injuries among athletes highlights the need for a better understanding of their relationship and implications for prevention and management strategies. Methods: A literature review from the PubMed, Web of Science, and Google Scholar databases including the MeSH keywords "overtraining syndrome", "bone", and "paralympic athletes". Results: Studies have consistently shown that athletes engaged in endurance sports are particularly susceptible to overtraining syndrome. The multifactorial nature of this condition involves not only physical factors, but also psychological and environmental determinants. In addition, the diagnosis and management of OTS and bone stress injuries present challenges in clinical practice. Conclusions: Currently, there are no definitive biochemical markers for overtraining syndrome. The diagnosis is based on a combination of subjective measures such as questionnaires, symptoms checklists, and objective biomarkers, including hormone levels, inflammatory markers, and imaging studies. However, these diagnostic approaches have limitations regarding their specificity and sensitivity.

Training Load Monitoring Practices Used by Strength and Conditioning Coaches in Hurling, Gaelic Football, Camogie, and Ladies Gaelic Football

BACKGROUND

No research has investigated the training load (TL) monitoring practices currently used by strength and conditioning (S&C) coaches in Gaelic games. The purpose of this study was to investigate the TL monitoring practices used by S&C coaches across senior intercounty male and female Gaelic game sports.

STUDY DESIGN

Cross-sectional.

HYPOTHESES

It was hypothesized that (1) TL is commonly monitored, (2) various methods are used by S&C coaches to monitor TL, and (3) the level of qualifications of the S&C coach is of a professional standard.

LEVEL OF EVIDENCE

Level 4.

METHODS

A total of 33 (n = 32 male and n = 1 female) S&C coaches participated in the study by completing an online questionnaire that investigated coach biography, coach education, team biography, monitoring practices, rating of perceived exertion, acute:chronic workload ratio, and data implementation.

RESULTS

The results showed that S&C coaches had varying levels of experience and education. All 33 coaches (100%) stated they monitored the TL of the players. The most common method used to monitor TL was session rating of perceived exertion, which was used by 91% of coaches. Analysis of an open-ended question afforded each participant the opportunity to share additional information, highlighting 3 themes: (1) communication with players, (2) performance testing, and (3) clarity and support among other coaching staff.

CONCLUSION

Multiple methods are used to monitor TL in Gaelic games. Despite multiple forms of technology available, communication with players provides essential information regarding an athlete's state.

CLINICAL RELEVANCE

As this is the first study to explore TL monitoring practices used by S&C coaches in Gaelic games, the results may inform the development of educational resources for the guidance of coaches working in Gaelic games in best practice TL monitoring.

Methods of Monitoring Internal and External Loads and Their Relationships with Physical Qualities, Injury, or Illness in Adolescent Athletes: A Systematic Review and Best-Evidence Synthesis

BACKGROUND

With the increasing professionalisation of youth sports, training load monitoring is increasingly common in adolescent athletes. However, the research examining the relationship between training load and changes in physical qualities, injury, or illness in adolescent athletes is yet to be synthesised in a systematic review.

OBJECTIVE

The aim of this review was to systematically examine the research assessing internal and external methods of monitoring training load and physical qualities, injury, or illness in adolescent athletes.

METHODS

Systematic searches of SPORTDiscus, Web of Science, CINAHL and SCOPUS were undertaken from the earliest possible records to March 2022. Search terms included synonyms relevant to adolescents, athletes, physical qualities, injury, or illness. To be eligible for inclusion, articles were required to (1) be original research articles; (2) be published in a peer-reviewed journal; (3) include participants aged between 10 and 19 years and participating in competitive sport; (4) report a statistical relationship between a measure of internal and/or external load and physical qualities, injury or illness. Articles were screened and assessed for methodological quality. A best-evidence synthesis was conducted to identify trends in the relationships reported.

RESULTS

The electronic search yielded 4125 articles. Following screening and a review of references, 59 articles were included. The most commonly reported load monitoring tools were session ratings of perceived exertion (n = 29) and training duration (n = 22). Results of the best-evidence synthesis identified moderate evidence of positive relationships between resistance training volume load and improvement in strength, and between throw count and injury. However, evidence for other relationships between training load and change in physical qualities, injury, or illness were limited or inconsistent.

CONCLUSIONS

Practitioners should consider monitoring resistance training volume load for strength training. Additionally, where appropriate, monitoring throw counts may be useful in identifying injury risk. However, given the lack of clear relationships between singular measures of training load with physical qualities, injury, or illness, researchers should consider multivariate methods of analysing training load, as well as factors that may mediate the load-response relationship, such as maturation.

Training patterns associated with injury in New York City Marathon runners

OBJECTIVE

Training patterns are commonly implicated in running injuries. The purpose of this study was to measure the incidence of injury and illness among marathon runners and the association of injuries with training patterns and workload.

METHODS

Runners registered for the New York City Marathon were eligible to enrol and prospectively monitored during the 16 weeks before the marathon, divided into 4-week 'training quarters' (TQ) numbered TQ1-TQ4. Training runs were tracked using Strava, a web and mobile platform for tracking exercise. Runners were surveyed at the end of each TQ on injury and illness, and to verify all training runs were recorded. Acute:chronic workload ratio (ACWR) was calculated by dividing the running distance in the past 7 days by the running distance in the past 28 days and analysed using ratio thresholds of 1.3 and 1.5.

RESULTS

A total of 735 runners participated, mean age 41.0 (SD 10.7) and 46.0% female. Runners tracked 49 195 training runs. The incidence of injury during training was 40.0% (294/735), and the incidence of injury during or immediately after the marathon was 16.0% (112/699). The incidence of illness during training was 27.2% (200/735). Those reporting an initial injury during TQ3 averaged less distance/week during TQ2 compared with uninjured runners, 27.7 vs 31.9 miles/week (p=0.018). Runners reporting an initial injury during TQ1 had more days when the ACWR during TQ1 was ≥1.5 compared with uninjured runners (injured IQR (0-3) days vs uninjured (0-1) days, p=0.009). Multivariable logistic regression for training injuries found an association with the number of days when the ACWR was ≥1.5 (OR 1.06, 95% CI (1.02 to 1.10), p=0.002).

CONCLUSION

Increases in training volume ≥1.5 ACWR were associated with more injuries among runners training for a marathon. These findings can inform training recommendations and injury prevention programmes for distance runners.

Wearable technology in the sports medicine clinic to guide the return-to-play and performance protocols of athletes following a COVID-19 diagnosis

The coronavirus disease 2019 (COVID-19) pandemic has enabled the adoption of digital health platforms for self-monitoring and diagnosis. Notably, the pandemic has had profound effects on athletes and their ability to train and compete. Sporting organizations worldwide have reported a significant increase in injuries manifesting from changes in training regimens and match schedules resulting from extended quarantines. While current literature focuses on the use of wearable technology to monitor athlete workloads to guide training, there is a lack of literature suggesting how such technology can mediate the return to sport processes of athletes infected with COVID-19. This paper bridges this gap by providing recommendations to guide team physicians and athletic trainers on the utility of wearable technology for improving the well-being of athletes who may be asymptomatic, symptomatic, or tested negative but have had to quarantine due to a close exposure. We start by describing the physiologic changes that occur in athletes infected with COVID-19 with extended deconditioning from a musculoskeletal, psychological, cardiopulmonary, and thermoregulatory standpoint and review the evidence on how these athletes may safely return to play. We highlight opportunities for wearable technology to aid in the return-to-play process by offering a list of key parameters pertinent to the athlete affected by COVID-19. This paper provides the athletic community with a greater understanding of how wearable technology can be implemented in the rehabilitation process of these athletes and spurs opportunities for further innovations in wearables, digital health, and sports medicine to reduce injury burden in athletes of all ages.

The relationship between bowling intensity and ground reaction force in cricket pace bowlers

This study examined the relationship between perceived bowling intensity, ball release speed and ground reaction force (measured by peak force, impulse and loading rate) in male pace bowlers. Twenty participants each bowled 36 deliveries, split evenly across three perceived intensity zones: low = 70% of maximum perceived bowling effort, medium = 85%, and high = 100%. Peak force and loading rate were significantly different across the three perceived intensity zones in the horizontal and vertical directions (Cohen's d range = 0.14-0.45, p < 0.01). When ball release speed increased, peak force and loading rate also increased in the horizontal and vertical directions (η_p² = 0.04-0.18, p < 0.01). Lastly, bowling at submaximal intensities (i.e., low - medium) was associated with larger decreases in peak horizontal force (7.9-12.3% decrease), impulse (15.8-21.4%) and loading rate (7.4-12.7%) compared to decreases in ball release speed (5.4-8.3%). This may have implications for bowling strategies implemented during training and matches, particularly for preserving energy and reducing injury risk.

Effects of Chronological Age, Relative Age, and Maturation Status on Accumulated Training Load and Perceived Exertion in Young Sub-Elite Football Players

The aims of this study were 1) to analyze the influence of chronological age, relative age, and biological maturation on accumulated training load and perceived exertion in young sub-elite football players and 2) to understand the interaction effects amongst age grouping, maturation status, and birth quartiles on accumulated training load and perceived exertion in this target population. A 6-week period (18 training sessions and 324 observation cases) concerning 60 young male sub-elite football players grouped into relative age (Q1 to Q4), age group (U15, U17, and U19), and maturation status (Pre-peak height velocity (PHV), Mid-PHV, and Post-PHV) was established. External training load data were collected using 18 Hz global positioning system technology (GPS), heart-rate measures by a 1 Hz short-range telemetry system, and perceived exertion with total quality recovery (TQR) and rating of perceived exertion (RPE). U17 players and U15 players were 2.35 (95% CI: 1.25–4.51) and 1.60 (95% CI: 0.19–4.33) times more likely to pertain to Q1 and Q3, respectively. A negative magnitude for odds ratio was found in all four quartile comparisons within maturation status (95% CI: 6.72–0.64), except for Mid-PHV on Q2 (95% CI: 0.19–4.33). Between- and within-subject analysis reported significant differences in all variables on age group comparison measures (F = 0.439 to 26.636, p = 0.000 to 0.019, η2 = 0.003–0.037), except for dynamic stress load (DSL). Between-subject analysis on maturity status comparison demonstrated significant differences for all training load measures (F = 6.593 to 14.424, p = 0.000 to 0.037, η2 = 0.020–0.092). Interaction effects were found for age group x maturity band x relative age (Λ Pillai’s = 0.391, Λ Wilk’s = 0.609, F = 11.385, p = 0.000, η2 = 0.391) and maturity band x relative age (Λ Pillai’s = 0.252, Λ Wilk’s = 0.769, F = 0.955, p = 0.004, η2 = 0.112). Current research has confirmed the effects of chronological age, relative age, and biological maturation on accumulated training load. Perceived exertion does not seem to show any differences concerning age group or maturity status. Evidence should be helpful for professionals to optimize the training process and young football players’ performance.

Quantifying cricket fast bowling volume, speed and perceived intensity zone using an Apple Watch and machine learning

This study examined whether an inertial measurement unit (IMU) and machine learning models could accurately measure bowling volume (BV), ball release speed (BRS), and perceived intensity zone (PIZ). Forty-four male pace bowlers wore a high measurement range, research-grade IMU (SABELSense) and a consumer-grade IMU (Apple Watch) on both wrists. Each participant bowled 36 deliveries, split into two different PIZs (Zone 1 = 70-85% of maximum bowling effort, Zone 2 = 100% of maximum bowling effort). BRS was measured using a radar gun. Four machine learning models were compared. Gradient boosting models had the best results across all measures (BV: F-score = 1.0; BRS: Mean absolute error = 2.76 km/h; PIZ: F-score = 0.92). There was no significant difference between the SABELSense and Apple Watch on the same hand when measuring BV, BRS, and PIZ. A significant improvement in classifying PIZ was observed for IMUs located on the dominant wrist. For all measures, there was no added benefit of combining IMUs on the dominant and non-dominant wrists.

The relationship between cricket participation, health and wellbeing: A scoping review

Summarising and synthesising the evidence on cricket health and wellbeing can help inform cricket stakeholders and navigate future research directions. The purpose of this study was to investigate the relationship between cricket participation, health and wellbeing at all ages and playing standards, and identify research gaps in the existing literature. A scoping review was performed from inception to March, 2020. Studies were included if they assessed a construct related to health and/or wellbeing in cricketers, available in English. 219 articles were eligible. Injury incidence per 1,000 player exposures ranged from 1.8-5.7 injuries. 48% of former cricketers experienced persistent joint pain. However, former cricketers reported greater physical activity levels and mental-components of quality of life compared to the general population. Heat injury/illness and skin cancer are concerns and require further research. Cricket participation is associated with an inherent injury risk, which may have negative implications for musculoskeletal health in later life. However, cricket participation is associated with high quality of life which can persist after retirement. Gaps in the literature include prospective studies on health and wellbeing of cricketers, female cricketers, injury prevention strategies, and the impact of cricket participation on metabolic health and lifetime physical activity.

Quantification of the demands of cricket bowling and the relationship to injury risk: a systematic review

BACKGROUND

Bowling in cricket is a complex sporting movement which, despite being well characterised, still produces a significant number of injuries each year. Fast bowlers are more likely to be injured than any other playing role. Frequency, duration, intensity and volume of bowling, which have been generalised as measurements of workload, are thought to be risk factors for injuries. Injury rates of fast bowlers have not reduced in recent years despite the implementation of various workload monitoring practices.

OBJECTIVE

To identify the variables used to quantify frequency, intensity, time and volume of bowling; and evaluate relationships between these variables and injury risk.

METHODS

Six online databases were systematically searched for studies on fast bowling that included terms related to workload. Population characteristics, variables relating to demand and their relationship to standardised definitions of physical activity were extracted from all included studies.

RESULTS

Bowling workload is typically quantified through measures of frequency, duration, or indirect intensity, with few studies reporting on bowling volume.

CONCLUSIONS

When reported on, volume was often described using imprecise or insufficient measures of intensity. There is a need to develop more appropriate measures of intensity during bowling and improve the quality of evidence to inform on bowling programme management practices.

Internal and External Training Workload Quantification in 4 Experienced Paracanoeing Athletes

CONTEXT

Paracanoeing is one of the adapted sports eligible for different motor impairments. The acute:chronic workload ratio (ACWR) is an index between acute and chronic training workload. However, no studies have analyzed this variable in paracanoeing, relating it with training recovery markers.

OBJECTIVE

This study aimed to quantify the internal (session rating of perceived exertion) and external (distance traveled and total training time) training workloads in 4 experienced paracanoe athletes over 9 months and 5 canoeing events.

DESIGN

Cross-sectional study.

SETTING

Rehabilitation Hospital Network, Paralympic Program.

PARTICIPANTS

Four experienced paracanoe athletes participated in 36 weeks of training for 5 events.

MAIN OUTCOMES MEASURES

The daily and weekly training workload, monotony, ACWR, distance, and total training time were described for all the training phases. The perceived recovery status scale (PRS) and medicine ball throw (MBT) were used to quantify recovery.

RESULTS

The average daily and weekly training workload varied from 213.1 to 239.3 and 767.3 to 1036.8 arbitrary units, respectively. Average ACWR results ranged from 0.96 to 1.10 in the 4 athletes, findings that were outside the safety zone in 38% of the training weeks. All the correlations between MBT and PRS were classified as weak (ρ between .20 and .39, P > .05). ACWR showed a very weak correlation with MBT and moderately and highly significant correlations with PRS in 2 athletes, respectively.

CONCLUSIONS

The training workloads of 4 paracanoe athletes may serve as a comparison with other periodization models. Pretraining recovery assessments (MBT and PRS) exhibited a low, nonsignificant correlation. However, ACWR correlated significantly with PRS in 2 athletes and might be a suitable tool for daily training adjustments.

Identifying Risk Factors of Upper Extremity Injuries in Collegiate Baseball Players: A Pilot Study

BACKGROUND

Repetitive pitching places tremendous forces on the shoulder and elbow which can lead to upper extremity (UE) or lower extremity (LE) overuse injuries.

PURPOSE

The purpose of this study was to evaluate pre-season physical measurements in collegiate baseball players and track in-season baseball throwing volume to determine which factors may predict throwing overuse injuries.

STUDY DESIGN

Retrospective Cohort study.

METHODS

Baseline preseason mobility, strength, endurance, and perception of function were measured in 17 collegiate baseball pitchers. Participants were then followed during the course of the season to collect rate of individual exposure, estimated pitch volume, and rating of perceived exertion in order to determine if changes in workload contributed to risk of injury using an Acute-to-Chronic Workload ratio (ACWR).

RESULTS

Participants developing an injury had greater shoulder internal rotator strength (p=0.04) and grip strength in a neutral position (p=0.03). A significant relationship was identified between ACWR and UE injuries (p <0.001). Athletes with an ACWR above or below 33% were 8.3 (CI95 1.8-54.1) times more likely to suffer a throwing overuse injury occurring to the upper or lower extremity in the subsequent week.

CONCLUSION

ACWR change in a positive or negative direction by 33% was the primary predictor of subsequent injury. This finding may assist sports medicine clinicians by using this threshold when tracking pitch volume to ensure a safe progression in workload during a baseball season to reduce the risk of sustaining overuse upper or lower extremity injuries.

LEVEL OF EVIDENCE

3b.

A Novel Approach to Training Monotony and Acute-Chronic Workload Index: A Comparative Study in Soccer

Load is a multifactorial construct, but usually reduced to parameters of volume and intensity. In the last decades, other constructs have been proposed for assessing load, but also relying on relationships between volume and intensity. For example, Foster's Training Monotony has been used in athletes' load management simply by computing mean weekly load divided by its standard deviation, often multiplied by session rate of perceived exertion. Meanwhile, the Acute to Chronic Workload Ratio (ACWR) has been debated by the sport scientists as a useful monitoring metric and related to so-called injury prevention. None of these models includes parameters that are representative of training specificity, namely load orientation. The aim of this study is to present broader conceptual approaches translated by new indices for assessing Intraweek Training Monotony (ITM) and Acute to Chronic Workload Index (ACWI) while incorporating load orientation, session duration and weekly density (frequency normalized) in addition to parameters related to proxies of external and/or internal load. Our ITM and Foster's Training Monotony were similar in terms of average values, but very different for individualized analysis, illustrating how average values may be deceiving. While Foster's model provided clusters of values, ITM provided more scattered, individualized data. ACWI and ACWR provided very distinct qualitative information, and the two models were uncorrelated. Therefore, the models incorporating training load orientation presented in this study provide distinct and not redundant information when compared to previous models. More importantly, ITM and ACWI are metrics that are compatible to each other and might fit to coaches' monitoring targets in the short and medium terms, respectively. Because our models include several parameters, including load orientation, we contend that might provide a more complete monitoring tool. However, we suggest they are used for intraindividual comparisons and not so strongly for interindividual comparisons.

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.

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).

Accelerometry-Workload Indices Concerning Different Levels of Participation during Congested Fixture Periods in Professional Soccer: A Pilot Study Conducted over a Full Season

The aim of this study was to analyze the variations of acute load (AL), acute: chronic workload ratio (ACWR), training monotony (TM), and training strain (TS) of accelerometry-based GPS measures in players who started in three matches (S3M), two matches (S2M), and one match (S1M) during congested weeks. Nineteen elite professional male players from a Portuguese team (age: 26.5 ± 4.3 years) were monitored daily using global positioning systems (GPSs) over a full season (45 weeks). Accelerometry-derived measures of high metabolic load distance (HMLD), high accelerations (HA), and high decelerations (HD) were collected during each training session and match. Seven congested weeks were classified throughout the season, and the participation of each player in matches played during these weeks was codified. The workload indices of AL (classified as ACWR, TM, and TS) were calculated weekly for each player. The AL of HMLD was significantly greater for S2M than S1M (difference = 42%; p = 0.002; d = 0.977) and for S3M than S1M (difference = 44%; p = 0.001; d = 1.231). Similarly, the AL of HA was significantly greater for S2M than S1M (difference = 25%; p = 0.023; d = 0.735). The TM of HD was significantly greater for S2M than S3M (difference = 25%; p = 0.002; d = 0.774). Accelerometry-based measures were dependent on congested fixtures. S2M had the greatest TS values, while S3M had the greatest TM.

Can an inertial measurement unit (IMU) in combination with machine learning measure fast bowling speed and perceived intensity in cricket?

This study examined whether an inertial measurement unit (IMU), in combination with machine learning, could accurately predict two indirect measures of bowling intensity through ball release speed (BRS) and perceived intensity zone (PIZ). One IMU was attached to the thoracic back of 44 fast bowlers. Each participant bowled 36 deliveries at two different PIZ zones (Zone 1 = 24 deliveries at 70% to 85% of maximum perceived bowling effort; Zone 2 = 12 deliveries at 100% of maximum perceived bowling effort) in a random order. IMU data (sampling rate = 250 Hz) were downsampled to 125 Hz, 50 Hz, and 25 Hz to determine if model accuracy was affected by the sampling frequency. Data were analysed using four machine learning models. A two-way repeated-measures ANOVA was used to compare the mean absolute error (MAE) and accuracy scores (separately) across the four models and four sampling frequencies. Gradient boosting models were shown to be the most consistent at measuring BRS (MAE = 3.61 km/h) and PIZ (F-score = 88%) across all sampling frequencies. This method could be used to measure BRS and PIZ which may contribute to a better understanding of overall bowling load which may help to reduce injuries.

Synchronous and asynchronous tele-exercise during the coronavirus disease 2019 pandemic: Comparisons of implementation and training load in individuals with spinal cord injury

INTRODUCTION

Tele-exercise could represent an alternative for remote care in individuals with spinal cord injury at this time of the pandemic of coronavirus disease 2019. However, the differences regarding the training loads and implementation between synchronous and asynchronous types are not yet known. The purpose of this study was to compare the implementation and training load between synchronous and asynchronous tele-exercise programs in individuals with spinal cord injury.

METHODS

Forty individuals with spinal cord injury were recruited and stratified into tetraplegia and paraplegia groups. All subjects performed 3 weeks of both the synchronous and asynchronous tele-exercise programs, after two weeks of familiarization with the exercises, remote connection tools and methods to record information. The primary outcomes were training load (average daily workload and average and total weekly training load) and implementation (adherence and successful exercise recording). Demographic characteristics were obtained from participants' electronic medical records.

RESULTS

Weekly mean workload, total workload, adherence and successful exercise recording presented significantly higher values in the synchronous compared to asynchronous tele-exercises. Average daily workload did not present significant differences between the tele-exercises.

DISCUSSION

The training load for each training session presented no differences between synchronous and asynchronous tele-exercises. Both adherence and successful data recording showed more favourable implementation values for synchronous training, thus allowing greater weekly training loads (total and average).

What Role Do Chronic Workloads Play in the Acute to Chronic Workload Ratio? Time to Dismiss ACWR and Its Underlying Theory

AIM

The aim of this study was to examine the associations between the injury risk and the acute (AL) to chronic (CL) workload ratio (ACWR) by substituting the original CL with contrived values to assess the role of CL (i.e., the presence and implications of statistical artefacts).

METHODS

Using previously published data, we generated a contrived ACWR by dividing the AL by fixed and randomly generated CLs, and we compared these results to real data. We also reproduced previously reported subgroup analyses, including dichotomising players' data above and below the median CL. Our analyses follow the same, previously published modelling approach.

RESULTS

The analyses with original data showed effects compatible with higher injury risk for ACWR only (odd ratios, OR: 2.45, 95% CI 1.28-4.71). However, we observed similar effects by dividing AL by the "contrived" fixed and randomly generated CLs: OR 1.95 (1.18-3.52) dividing by 1510 (average CL); and OR ranging from 1.16 to 2.07, using random CL 1.53 (mean). Random ACWRs reduced the variance relative to the original AL and further inflated the ORs (mean OR 1.89, from 1.42 to 2.70). ACWR causes artificial reclassification of players compared to AL alone. Finally, neither ACWR nor AL alone confer a meaningful predictive advantage to an intercept-only model, even within the training sample (c-statistic 0.574/0.544 vs. 0.5 in both ACWR/AL and intercept-only models, respectively).

DISCUSSION

ACWR is a rescaling of the explanatory variable (AL, numerator), in turn magnifying its effect estimates and decreasing its variance despite conferring no predictive advantage. Other ratio-related transformations (e.g., reducing the variance of the explanatory variable and unjustified reclassifications) further inflate the OR of AL alone with injury risk. These results also disprove the etiological theory behind this ratio and its components. We suggest ACWR be dismissed as a framework and model, and in line with this, injury frameworks, recommendations, and consensus be updated to reflect the lack of predictive value of and statistical artefacts inherent in ACWR models.

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 Recovery During a Pre-Olympic Season in Professional Rhythmic Gymnasts

CONTEXT

Rhythmic gymnastics requires a high level of complexity and perfection of technical gestures, associated with well-developed physical and artistic capacities. The training-load and recovery profiles of rhythmic gymnasts across a season are unknown.

OBJECTIVE

To analyze the training load and recovery of professional rhythmic gymnasts during 1 season.

DESIGN

Cohort study.

SETTING

Brazilian National Training Center of Rhythmic Gymnastics and competition facilities.

PATIENTS OR OTHER PARTICIPANTS

Eight gymnasts from the Brazilian national senior rhythmic gymnastics group.

MAIN OUTCOME MEASURE(S)

Session rating of perceived exertion (session-RPE) and total quality recovery (TQR) scores were collected daily for 43 weeks. We obtained the session-RPE after each session and TQR score before the first session of the day. Performances during 5 competitions were also recorded. The season was divided into 8 periods. Total weekly internal training load (wITL), training intensity, frequency, duration, recovery, and acute : chronic workload ratio were calculated for analysis.

RESULTS

The season mean wITL was 10 381 ± 4894 arbitrary units, mean session-RPE score was 5.0 ± 1.6, and mean TQR score was 12.8 ± 1.3. The gymnasts trained an average of 8.7 ± 2.9 sessions per week, with a mean duration of 219 ± 36 minutes. Each competitive period showed increased wITL compared with the previous period. Training-load variables (wITL and session-RPE) and recovery were inversely correlated. Gymnasts were poorly recovered (TQR < 13) during 50.9% of the season (n = 167 times), especially during competitive weeks. Spikes in load (acute : chronic workload ratio ≥ 1.5) occurred across 18.1% of the season (n = 55 times).

CONCLUSIONS

The training-load variables and recovery changed throughout a professional rhythmic gymnastics group season, mainly during competitive periods. The correct distribution of training load is critical to ensure that gymnasts are entering competitions in a recovered state.

[Monitoring and load management in team handball]

BACKGROUND

 The monitoring of athletes has become a focus in elite-level team sports and research in recent years. The goal is to optimise load management for maximising performance. Due to the considerable amount of data gathered during monitoring in team sports, the trend is towards integrating different monitoring methods in a software-based tool. In addition, decision-support systems are used in order to enable coaches to make quick decisions to control further burdens. This article is intended to give an overview of the large number of monitoring methods used in contact team sports, to consider their test quality criteria and to check a useful application of monitoring methods for team handball, taking into account the sports-specific requirements.

METHODS

 PubMed-based review of the literature. Narrative review focusing on current data from the years 2010 to 2019.

RESULTS

 Demands on athletes in elite team handball vary depending on the playing position. Therefore, individualised load control is necessary. Monitoring methods with proven validity and reliability should ideally be used in a multivariate approach to represent the various aspects of external and internal load, recovery and fatigue, well-being and readiness. It is important to know the meaningful change for each athlete while using a monitoring method. This circumstance necessitates an individualised approach for each parameter. There are not many studies on the use of monitoring methods in team handball, neither in the amateur field nor in an elite sports environment. Nevertheless, based on evidence from other contact team sports, a recommendation for a combined use of monitoring methods can be given. Burden, time and cost/benefit should always be considered.

CONCLUSION

 There is a considerable need for research regarding the use of athlete monitoring in team handball. The combination of monitoring methods proposed in this article can be used as a framework for studies with handball players in an elite sports environment in order to implement an increasingly handball-specific monitoring concept in the future.

Understanding the association between external training load measures and injury risk in Elite Gaelic football

BACKGROUND

The current investigation examined the association between external training load variables and injury risk within elite Gaelic football.

METHODS

Workload and injury variables were collected from thirty-seven elite Gaelic footballers (mean±SD age of 24.2±2.9 years) from one elite squad across a two-season observational period. External training load variables included total distance (m), High speed running (m; ≥17.1 km·h^-1), Sprint distance (m; 22 km·h^-1), Accelerations (n), Average metabolic power (W·kg^-1), high-power distance (m; ≥25 W·kg^-1). Cumulative 1- weekly, 2-weekly, 3-weekly and 4-weekly training loads; acute: chronic workload ratio (ACWR) was analysed across specific distributions of low, moderate and high loading with respect to a reference group of the measure quantified. General estimating equations were utilized to understand the association of these variables with injury risk.

RESULTS

Strong associations (AUC>0.50) were observed amongst models developed for one weekly loading for relative distance, average metabolic power and high-power indices with similar trends observed for two, three and four weekly which showed a strong positive association within injury risk for all external loading metrics (AUC>0.50), with average metabolic power, and high-power distance showing the strongest association across the three-four week loading scales (AUC>0.60). When the ACWR was considered for external load measures these showed a positive linear association with injury risk (AUC>0.50). When intensity measures were considered relative distance showed an associated risk for injury across one and two-weekly models but not three and four weekly models. When odds risk association was considered a consistent trend towards moderate loading across external loading measures was apparent within the observed cohort.

CONCLUSIONS

The current investigation reports for the first time the injury association for external loading measures within elite Gaelic football. Data show that a range of measures are associated with increased or decreased injury risk depending on the loading scheme applied by coaches within elite Gaelic football.

Acute:Chronic Workload Ratio: Conceptual Issues and Fundamental Pitfalls

The number of studies examining associations between training load and injury has increased exponentially. As a result, many new measures of exposure and training-load-based prognostic factors have been created. The acute:chronic workload ratio (ACWR) is the most popular. However, when recommending the manipulation of a prognostic factor in order to alter the likelihood of an event, one assumes a causal effect. This introduces a series of additional conceptual and methodological considerations that are problematic and should be considered. Because no studies have even tried to estimate causal effects properly, manipulating ACWR in practical settings in order to change injury rates remains a conjecture and an overinterpretation of the available data. Furthermore, there are known issues with the use of ratio data and unrecognized assumptions that negatively affect the ACWR metric for use as a causal prognostic factor. ACWR use in practical settings can lead to inappropriate recommendations, because its causal relation to injury has not been established, it is an inaccurate metric (failing to normalize the numerator by the denominator even when uncoupled), it has a lack of background rationale to support its causal role, it is an ambiguous metric, and it is not consistently and unidirectionally related to injury risk. Conclusion: There is no evidence supporting the use of ACWR in training-load-management systems or for training recommendations aimed at reducing injury risk. The statistical properties of the ratio make the ACWR an inaccurate metric and complicate its interpretation for practical applications. In addition, it adds noise and creates statistical artifacts.

Prior workload has moderate effects on high-intensity match performance in elite-level professional football players when controlling for situational and contextual variables

This investigation examined the effect of prior workload on high-intensity football match performance. Player load variables were recorded using a global positioning system and converted into composite variables: rolling season accumulated load (AL), exponentially weighted moving average acute, chronic and acute:chronic workload ratio (A:C). Match-play high-intensity performance-per-minute: accelerations (ACC), sprints, high-speed running (HSR) and high metabolic load (HMLd) distances; and situational and contextual variables were recorded for all games. Partial least squares modelling, and backward stepwise selection determined the most parsimonious model for each performance variable. Quadratic relationships of small to moderate effect sizes were identified for sprint AL and sprint performance, HSR AL and HSR performance, acute HMLd and HMLd performance, acute sprint load and ACC performance and A:C sprint load and ACC performance. Match performance was typically greatest between the mean and +1SD. High chronic HMLd, and combined acceleration and deceleration (ACC+DEC) load exerted small beneficial effects on HMLd and HSR performance, whereas high acute load exerted trivial to moderate negative effects. High sprint A:C exerted a small beneficial effect on sprint performance and playing position exerted small effects on HSR and HMLd performance. Prior workload has trivial to moderate effects on high-intensity match performance in professional players.

A prospective cohort study on the acute:chronic workload ratio in relation to injuries in high level eventing horses: A comprehensive 3-year study

In human sport science, the acute:chronic workload (ACWR) ratio is used to monitor an athlete's preparedness for competition and to assess injury risks. The aim of this study was to investigate whether acute and chronic workload calculations for external and internal loads (e.g. high-speed work distance and associated exertional effort) were associated with injury risk in elite eventing horses and to identify workloads performed by horses competing in different competition and at different fitness levels. Training load and injury data were collected from 58 international eventing horses (CCI2*-CCI5* level) over 1-3 years. A total of 94 individual competition seasons were monitored. During this period, heart rate (HR; beat/min) and GPS data were collected of all their conditional training sessions and competitions. External load was determined as the distance (m) covered at high speed (HS¹ ; velocity between 6.6 and 9.5 m/s), and sprint speed (SS² ; velocity>9.5 m/s). Internal load was calculated for HS and SS, using individualized training impulses (TRIMP³ ;AU). For internal and external workload HS and SS the acute (1-week) and chronic (4-week) workloads were calculated and ACWR⁴ determined. The injury data in relation to ACWR was modelled with a multilevel logistic regression. Akaike's information criterion was used for model reduction. Sixty-four soft tissue injuries were registered from a total of 2300 training sessions and competitions. External and internal workload at HS and SS were significantly affected by the year and fitness level of horses. Competition level and year significantly affected the distances covered at SS. The ACWR of high-speed distance of the present week (OR; 0.133, 95 % CI; 0.032, 0.484) and the previous week (OR 3.951, 95 % CI; 1.390, 12.498) were significantly associated with injury risk. Competition level and chronic workload had no significant effect on injuries. In agreement with findings in human athletes, acute spikes of workload in eventing horses increased the risk of injury. Evaluation of horses' workload can be used to design and effectively monitor training programs and can help to improve equine welfare by reducing injury risk.

Robust Exponential Decreasing Index (REDI): adaptive and robust method for computing cumulated workload

Objective

The purpose of this study was to define a new index the Robust Exponential Decreasing Index (REDI), which is capable of an improved analysis of the cumulative workload. This allows for precise control of the decreasing influence of load over time. Additionally, REDI is robust to missing data that are frequently present in sport.

Methods

200 cumulative workloads were simulated in two ways (Gaussian and uniform distributions) to test the robustness and flexibility of the REDI, as compared with classical methods (acute:chronic workload ratio and exponentially weighted moving average). Theoretical properties have been highlighted especially around the decreasing parameter.

Results

The REDI allows practitioners to consistently monitor load with missing data as it remains consistent even when a significant portion of the dataset is absent. Adjusting the decreasing parameter allows practitioners to choose the weight given to each daily workload.

Discussion

Computation of cumulative workload is not easy due to many factors (weekends, international training sessions, national selections and injuries). Several practical and theoretical drawbacks of the existing indices are discussed in the paper, especially in the context of missing data; the REDI aims to settle some of them. The decreasing parameter may be modified according to the studied sport. Further research should focus on methodology around setting this parameter.

Conclusion

The robust and adaptable nature of the REDI is a credible alternative for computing a cumulative workload with decreasing weight over time.