External Training Load Monitoring and the Impact on Training Load Management in Collegiate Male Soccer Players

ABSTRACT

Gdovin, JR, Galloway, R, Tomasiello, LS, Seabolt, M, and Booker, R. External training load monitoring and the impact on training load management in collegiate male soccer players. J Strength Cond Res 37(7): 1434-1439, 2023-Soccer is a physically demanding sport within the National Collegiate Athletic Association and continuously increases in popularity. To ensure athletes are adequately prepared for weekly physical stressors, coaches can use global positioning system technology to monitor external workloads and exercise intensity. These data can subsequently help coaches and practitioners better implement individualized training programs to ensure athletes are properly balancing the overreaching and overtraining paradigm. Therefore, the purpose of this observational study was to retrospectively analyze 3 consecutive seasons of external workload (total and high intensity distance) and injury data, which were derived from all training sessions and matches in 46 Division-I collegiate male soccer players. A coach's interpretation sought to provide practical insight into the functionality behind load management and how it prepares athletes for the physical stressors placed on them throughout a season. Two separate 3 × 3 repeated measures ANOVAs were conducted to determine differences between total distance and distance at high-intensity with an alpha level set at 0.05. Total distance between preseason and in-season ( p = 0.003), acute high-intensity distance ( p < 0.001), and chronic high-intensity distance ( p < 0.001) yielded significant differences. These results conclude the demands of each athlete change weekly and between seasons. It is recommended that sport coaches and practitioners develop individualized training programs by workload monitoring while considering variables such as a team's style of play, experience, position, role within a program, training intensity, and the length of time between conditioning sessions, practices, and matches.

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

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

Injury rates remained elevated in the second National Football League season after the onset of the COVID-19 pandemic

Purpose

The purpose of this study is to compare the injury incidence of the 2018-2019 and 2020 National Football League (NFL) seasons with the 2021 season.

Methods

Publicly released NFL weekly injury reports were queried to identify players listed as "out" or placed on injured reserve (IR) for at least one game in the 2018-2021 seasons. Injuries were then categorized into upper extremity, lower extremity, spine/core, and head. Incidence per 1,000 athlete exposures were calculated for each season and proportions of injuries by position were calculated separately for the 2018-2019, 2020, and 2021 cohorts. Incidence rate ratios (IRR) were used to compare injury rates.

Results

Overall injury incidence in the 2021 NFL season increased compared to the pre-COVID-19 seasons (2018-2019) in all anatomical zones except for the upper extremity. [28.70 vs. 23.09 per 1,000 exposures, IRR 1.24 (95% CI: 1.14-1.36); p< 0.001]. The injury rate remained elevated and further increased in 2021 compared to the 2020 season for all anatomical zones other than the spine/core [28.70 vs. 21.64 per 1,000 exposures, IRR 1.33 (1.19-1.47); p< 0.001]. No significant difference existed during the early season (weeks 1-4); however, injury rates after week 4 increased in 2021 compared to both the 2018-2019 and 2020 seasons.

Conclusion

The injury incidence in the 2021 season remained elevated and increased further compared to both the 2018-2019 and 2020 seasons. Traumatic injuries resulting in missed games increased despite return to a more traditional season since the beginning of the COVID-19 pandemic. The injury rates significantly increased in mid- to late season.

Level of Evidence

III, cross-sectional study.

Training, Wellbeing and Recovery Load Monitoring in Female Youth Athletes

Participation in youth sports is ever-increasing, along with training and competition demands placed upon youth athletes. Young athletes may experience high training loads due to playing several sports, as well as participating in school physical education. Therefore, monitoring youth athlete load is an emerging area of research that may help limit non-functional overreaching, injury, or illness and assist with long-term athlete development. This narrative review highlights that multiple measures have been explored to monitor both internal and external load. However, the validity, reliability and practicality of these measures are often not fully understood in female youth populations. The most commonly used external monitoring methods are GPS tracking and TRIMP whereas common internal monitoring tools are questionnaires, perceived exertion rating and heart rate measures. The reporting of injuries and menstrual cycles is also crucial for providing completeness when monitoring an athlete. It has been suggested that the combination of training load, recovery and wellbeing monitoring variables is the optimal way to monitor an athlete's fatigue levels. Whichever monitoring method is applied, in a youth population it is important that the protocol can be individualised, is inexpensive and can be easily implemented and reported so that the monitoring is sustainable.

Workload is associated with the occurrence of non-contact injuries in professional male soccer players: A pilot study

Injuries in professional soccer are a significant concern for teams, and they are caused amongst others by high training load. This cohort study describes the relationship between workload parameters and the occurrence of non-contact injuries, during weeks with high and low workload in professional soccer players throughout the season. Twenty-one professional soccer players aged 28.3 ± 3.9 yrs. who competed in the Iranian Persian Gulf Pro League participated in this 48-week study. The external load was monitored using global positioning system (GPS, GPSPORTS Systems Pty Ltd) and the type of injury was documented daily by the team's medical staff. Odds ratio (OR) and relative risk (RR) were calculated for non-contact injuries for high- and low-load weeks according to acute (AW), chronic (CW), acute to chronic workload ratio (ACWR), and AW variation (Δ-Acute) values. By using Poisson distribution, the interval between previous and new injuries were estimated. Overall, 12 non-contact injuries occurred during high load and 9 during low load weeks. Based on the variables ACWR and Δ-AW, there was a significantly increased risk of sustaining non-contact injuries (p &lt; 0.05) during high-load weeks for ACWR (OR: 4.67), and Δ-AW (OR: 4.07). Finally, the expected time between injuries was significantly shorter in high load weeks for ACWR [1.25 vs. 3.33, rate ratio time (RRT)] and Δ-AW (1.33 vs. 3.45, RRT) respectively, compared to low load weeks. The risk of sustaining injuries was significantly larger during high workload weeks for ACWR, and Δ-AW compared with low workload weeks. The observed high OR in high load weeks indicate that there is a significant relationship between workload and occurrence of non-contact injuries. The predicted time to new injuries is shorter in high load weeks compared to low load weeks. Therefore, the frequency of injuries is higher during high load weeks for ACWR and Δ-AW. ACWR and Δ-AW appear to be good indicators for estimating the injury risk, and the time interval between injuries.

Increased Regular Season Soft Tissue Injury Rates in National Football League (NFL) Players May Be Associated With the Canceled 2020 NFL Preseason Due to COVID-19

Introduction The purpose of this study is to evaluate the rates of regular season soft tissue injuries in National Football League (NFL) players during the 2020 season, which had a canceled preseason due to the COVID-19 pandemic. Methods This study retrospectively reviewed the injury rates of the 2020-2021 NFL regular season in comparison to the 2018-2019 NFL regular season using publicly available injury data. The focus of our analysis was comparing the following soft tissue injuries: hamstring, groin, calf, quadriceps, thigh, knee - anterior cruciate ligament (ACL), pectoral, and Achilles. The week of injury occurrence, duration of injury in weeks, position of the injured player, and age of the NFL player at injury were obtained. Injury rates were calculated per 1000 athletic exposures with 95% confidence intervals (CIs). A chi-square test and Student's t-test were utilized as appropriate. Results There were 1370 total injuries in the 2018-2019 regular NFL season and 2086 total injuries reported in the 2020-2021 regular NFL season. The total number of injuries per 1000 athletic exposures was significantly higher in the 2020-2021 NFL season compared to the 2018-2019 NFL season (88.57 versus 58.17, p < 0.001). The rates of injuries per 1000 athletic exposures for hamstring (9.98 versus 5.31, p = 0.043), groin (5.56 versus 2.46, p = 0.007), calf (4.08 versus 1.61, p = 0.006), quadriceps (2.00 versus 0.72, p = 0.030), and thigh (1.23 versus 0.30, p = 0.012) injuries were significantly higher in the 2020-2021 regular NFL season compared to the 2018-2019 NFL regular season. Conclusions The 2020-2021 NFL season had a significantly higher incidence of soft tissue injuries compared to the 2018-2019 regular NFL season, which may have been associated with the absent preseason due to the COVID-19 pandemic and an abrupt increase in the athletic workload of players.

Fluctuations of Training Load Variables in Elite Soccer Players U-14 throughout the Competition Season

Excessive daily training load (TL) can affect the musculoskeletal system health of youth elite soccer players. The purposes of this study were (i) to describe the TL and session rating of perceived exertion (s-RPE) throughout the competition season; (ii) to analyze the weekly (w) differences of acute (daily) workload (wAWL), chronic workload (wCWL), acute–chronic workload ratio, training monotony (wTM), and training strain (wTS) among three periods over the season (early-, mid-, and end-season) by playing position; and (iii) to compare the TL variables during competition periods for the whole team. Twenty young elite soccer players in the under-14 category participated in this study. The game positions were considered as six wide defenders and wide midfielders (WM), five central defenders and central midfielders, and four strikers (ST). Daily monitoring was continued for 26 weeks during a full competition season. According to the league schedule, the season was divided into three periods: early-season from w1 to w8, mid-season from w9 to w17, and end-season from w18 to w26. The main results were that the higher TLs were detected in the early- and mid-season. There was a wAWL and wCWL decrease for all playing positions from early- to mid- and end-season, but the wCWL change was significant only from early- to mid-season (p ≤ 0.05). For all playing positions but ST, there was a considerable wTM increase from early- to mid-season. When compared with all other playing positions in terms of wAWL and wCWL, WM showed significantly greater values (p ≤ 0.05). Throughout the season periods, all workload indicators showed a considerable reduction, although there was a significant increase in the three other workload-derived variables (all with p ≤ 0.05) and namely: (i) wACWLR from mid- to end-season; (ii) wTM from early- to mid- and end-season; and (iii) wTS from early- to mid-season. Daily training load and s-RPE had significant fluctuations during all macrocycles of the competition season (p ≤ 0.05). In addition, in the mid-season, wTM and wTS were higher. Training load monitoring (in terms of, e.g., wAWL, wCWL, and s-RPE) could be the key for coaches of soccer teams to prevent overtraining and injury, especially in U-14 players, who are more susceptible to being affected by high workload.

Increased Lower Extremity Injury Risk Associated With Player Load and Distance in Collegiate Women's Soccer

BACKGROUND

There is limited research regarding the impact of workload on injury risk specific to women's soccer. Wearable global positioning system (GPS) units can track workload metrics such as total distance traveled and player load during games and training sessions. These metrics can be useful in predicting injury risk.

PURPOSE

To examine the relationship between injury risk and player workload as collected from wearable GPS units in National Collegiate Athletic Association (NCAA) Division I women's soccer players.

STUDY DESIGN

Case-control study; Level of evidence, 3.

METHODS

Lower extremity injury incidence and GPS workload data (player load, total distance, and high-speed distance) for 65 NCAA Division I women's soccer players were collected over 3 seasons. Accumulated 1-, 2-, 3-, and 4-week loads and acute-to-chronic workload ratios (ACWR) were classified into discrete ranges by z-scores. ACWR was calculated using rolling averages and exponentially weighted moving averages (EWMA) models. Binary logistic regression models were used to compare the 7:28 rolling average and EWMA ACWRs between injured and noninjured players for all GPS/accelerometer variables. The prior 1-, 2-, 3-, and 4-week accumulated loads for all GPS/accelerometer variables were compared between the injured and uninjured cohorts using 2-sample t tests.

RESULTS

There were a total of 53 lower extremity injuries that resulted in lost time recorded (5.76/1000 hours "on-legs" exposure time; 34 noncontact and 19 contact injuries). The prior 2-week (7242 vs 6613 m/s2; P = .02), 3-week (10,533 vs 9718 m/s2; P = .02), and 4-week (13,819 vs 12,892 m/s2; P = .04) accumulated player loads and 2-week (62.40 vs 57.25 km; P = .04), 3-week (90.97 vs 84.10 km; P = .03), and 4-week (119.31 vs 111.38 km; P = .05) accumulated total distances were significantly higher for injured players compared with noninjured players during the same time frames. There were no significant differences in player load, total distance, or high-speed distance ACWR between injured and noninjured players for both the rolling averages and EWMA calculations.

CONCLUSION

Higher accumulated player load and total distance, but not ACWR, were associated with injury in women's soccer players.

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.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Exercise-Based Strategies to Prevent Muscle Injury in Male Elite Footballers: An Expert-Led Delphi Survey of 21 Practitioners Belonging to 18 Teams from the Big-5 European Leagues

Purpose

To define based on expert opinion and practical experience using a systematic and scientific approach, (1) the perceived most effective exercise-based strategies to prevent muscle injury in elite footballers; and, (2) when and how these exercise programs are prescribed based on the number of days between games i.e. implementation strategy.

Methods

A Delphi survey obtained opinions and assessed for agreement. Delphi respondents consisted of 21 experienced sports practitioners (12 ± 5.3 years in elite football and with an academic background) belonging to 18 teams from the Big-5 European football leagues; England, France, Germany, Italy, Spain. Three teams were represented collaboratively by two experts. The Delphi process involves sequential rounds each evolving based on the responses from the previous. The number of rounds is not pre-defined and continues until an agreement is either achieved or it is clear that no agreement will be reached. Frequency of responses was recorded where the agreement was sought (i.e. in closed questions) and an agreement was achieved if ≥ 13/18 (70%) respondents agreed. For open-ended questions, a qualitative content analysis was performed to identify recurring themes and when themes were specified by ≥ 13 (70%), these were also considered as reaching an agreement. Practitioners had the opportunity to raise concerns if they disagreed with the ‘agreement from recurrent themes’.

Results

There were four Delphi rounds (100% response for each round). Sprinting and High-Speed Running (HSR) focused exercises were agreed as most effective (perceived) to prevent muscle injuries. Eccentric exercise was perceived as the next most effective. It was agreed that sprinting and HSR be integrated into coaches training, and target 100% of players worst-case match scenario (e.g. volume, intensity) based on individual maximum speeds. Eccentric exercise was recommended to be implemented according to the context of the main football session and planned/actual sprinting and HSR content. It was agreed that eccentrics can be performed before or after training, context dependent. The day to perform specific sprinting and HSR or eccentric exercises depended on the proximity of previous and upcoming matches. Other exercises reaching agreement as ‘somewhat effective’ included concentric and isometric, horizontal and vertical plyometrics, coordination, core and dynamic flexibility in addition to core stability. No agreement was reached for multi-joint, resisted sprinting, kicking or agility exercises nor simultaneous single-leg strength and stability. Finally, no agreement was reached regarding programming variables e.g. sets, repetitions as deemed too contextual.

Conclusion

Regarding exercise-based strategies, particular importance agreed by the Delphi expert group was to focus on sprinting, HSR and eccentric exercises, integrated with a variety of other exercise modes which also carry some level of effectiveness in a multidimensional programme. Context was agreed to be key and decision-making about when to undertake/ how to prescribe exercise strategies to be made according to the content of normal football training and the proximity of matches.

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

BACKGROUND

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

OBJECTIVES

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

DATA SOURCES

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

ELIGIBILITY CRITERIA

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

METHODS

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

RESULTS

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

CONCLUSION

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

PROSPERO REGISTRATION NUMBER

CRD42017067585.

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

OBJECTIVE

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

DESIGN

Prospective cohort study.

METHODS

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

RESULTS

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

CONCLUSION

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

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

Injuries occur when an athlete performs a greater amount of activity than what their body can withstand. To maximize the positive effects of training while avoiding injuries, athletes and coaches need to determine safe activity levels. The International Olympic Committee has recommended using the acute:chronic workload ratio (ACWR) to monitor injury risk and has provided thresholds to minimize risk when designing training programs. However, there are several limitations to the ACWR and how it has been analyzed which impact the validity of current recommendations and should discourage its use. This review aims to discuss previously published and novel challenges with the ACWR, and strategies to improve current analytical methods. In the first part of this review, we discuss challenges inherent to the ACWR. We explain why using a ratio to represent changes in activity may not always be appropriate. We also show that using exponentially weighted moving averages to calculate the ACWR results in an initial load problem, and discuss their inapplicability to sports where athletes taper their activity. In the second part, we discuss challenges with how the ACWR has been implemented. We cover problems with discretization, sparse data, bias in injured athletes, unmeasured and time-varying confounding, and application to subsequent injuries. In the third part, conditional on well-conceived study design, we discuss alternative causal-inference based analytical strategies that may avoid major flaws in studies on changes in activity and injury occurrence.

Validity of Real-Time Ultra-wideband Global Navigation Satellite System Data Generated by a Wearable Microtechnology Unit

Johnston, RD, Hewitt, A, and Duthie, G. Validity of real-time ultra-wideband global navigation satellite system data generated by a wearable microtechnology unit. J Strength Cond Res 34(7): 2071-2075, 2020-This study aimed to determine the validity of real-time ultra-wideband data generated by a wearable microtechnology unit during rugby league training sessions using a repeated-measures crossover study. Twenty-four semiprofessional rugby league players wore a commercially available microtechnology device (StatSports Apex, Newry, Northern Ireland) during 10 training sessions. Total distance; moderate-speed running (3.6-4.9 m·s); high-speed running (5.0-6.9 m·s); very high-speed running (≥7 m·s); maximum velocity (m·s); the number of high-intensity accelerations (≥2.78 m·s) and decelerations (≥-2.78 m·s); dynamic stress load (AU); and high metabolic load distance (m) were recorded in real time through an Apex beacon over a secured wireless network before being exported to a csv file at the end of the session. The data were then downloaded to a computer after event. To determine the validity of the real-time data, they were compared with the postevent downloaded data using coefficient of variation and Pearson's correlation coefficient. There was almost perfect agreement between real-time and postevent downloaded data for all variables reported. The overall bias effect size scores were all trivial, ranging from 0.00 for total distance and high-speed running up to -0.12 for maximal velocity; Pearson's correlations were either perfect or nearly perfect (r = 0.98-1.00). Irrespective of the movement speed, the data collected by these devices in real time show excellent levels of agreement with postevent downloaded data.

UEFA expert group statement on nutrition in elite football. Current evidence to inform practical recommendations and guide future research

Football is a global game which is constantly evolving, showing substantial increases in physical and technical demands. Nutrition plays a valuable integrated role in optimising performance of elite players during training and match-play, and maintaining their overall health throughout the season. An evidence-based approach to nutrition emphasising, a 'food first' philosophy (ie, food over supplements), is fundamental to ensure effective player support. This requires relevant scientific evidence to be applied according to the constraints of what is practical and feasible in the football setting. The science underpinning sports nutrition is evolving fast, and practitioners must be alert to new developments. In response to these developments, the Union of European Football Associations (UEFA) has gathered experts in applied sports nutrition research as well as practitioners working with elite football clubs and national associations/federations to issue an expert statement on a range of topics relevant to elite football nutrition: (1) match day nutrition, (2) training day nutrition, (3) body composition, (4) stressful environments and travel, (5) cultural diversity and dietary considerations, (6) dietary supplements, (7) rehabilitation, (8) referees and (9) junior high-level players. The expert group provide a narrative synthesis of the scientific background relating to these topics based on their knowledge and experience of the scientific research literature, as well as practical experience of applying knowledge within an elite sports setting. Our intention is to provide readers with content to help drive their own practical recommendations. In addition, to provide guidance to applied researchers where to focus future efforts.

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

OBJECTIVES

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

DESIGN

Scoping review.

LITERATURE SEARCH

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

STUDY SELECTION CRITERIA

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

DATA SYNTHESIS

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

RESULTS

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

CONCLUSION

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

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

OBJECTIVE

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

DESIGN

Scoping review.

LITERATURE SEARCH

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

STUDY SELECTION CRITERIA

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

DATA SYNTHESIS

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

RESULTS

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

CONCLUSION

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

Clinical utility of measuring the size of the lumbar multifidus and quadratus lumborum muscles in the Australian football league setting: A prospective cohort study

OBJECTIVES

Test the odds of factors previously associated with lower limb injury (decreased size of the multifidus (MF) and increased size of the quadratus lumborum (QL) muscle) in an independent sample of Australian Rules Football (ARF) players.

DESIGN

Prospective cohort study.

SETTING

Professional ARF.

PARTICIPANTS

Forty-three male ARF players.

MAIN OUTCOME MEASURES

Cross-sectional areas (CSAs) of MF and QL muscles measured from pre-season ultrasound images. Playing season injuries were recorded by club personnel. A multivariable logistic regression model was used to evaluate the usefulness of MF and QL muscle size for predicting playing season lower limb injuries.

RESULTS

Fifteen players (35%) sustained a playing season lower limb injury. The multivariable model indicated that the odds of sustaining a lower limb injury during the season was 2.38 (95% CI: 1.18, 5.00; P = 0.017) times less likely for a one cm² increase from the mean value in MF muscle CSA at the L5 vertebral level after adjusting for CSA of the QL, age and BMI. The main effect and interaction models positively predicted 75% of players that sustained a lower limb injury during the season (sensitivity 80%, specificity 85%).

CONCLUSION

Future studies could examine the efficacy, feasibility and adherence of 'at risk' players to a pre-season training program aimed at increasing MF muscle size and monitor playing season injuries.

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).

Global Positioning System-Derived Workload Metrics and Injury Risk in Team-Based Field Sports: A Systematic Review

OBJECTIVE

To evaluate the current literature regarding the utility of global positioning system (GPS)-derived workload metrics in determining musculoskeletal injury risk in team-based field-sport athletes.

DATA SOURCES

PubMed entries from January 2009 through May 2019 were searched using terms related to GPS, player workload, injury risk, and team-based field sports.

STUDY SELECTION

Only studies that used GPS metrics and had injury as the main outcome variable were included.

DATA EXTRACTION

Total distance, high-speed running, and acute : chronic workload ratios were the most common GPS metrics analyzed, with the most frequent sports being soccer, rugby, and Australian rules football.

DATA SYNTHESIS

Many distinct workload metrics were associated with increased injury risk in individual studies performed in particular sport circumstances; however, the body of evidence was inconclusive as to whether any specific metrics could consistently predict injury risk across multiple team-based field sports.

CONCLUSIONS

Our results were inconclusive in determining if any GPS-derived workload metrics were associated with an increased injury risk. This conclusion is due to a myriad of factors, including differences in injury definitions, workload metrics, and statistical analyses across individual studies.

Is There a Relationship Between Workload and Occurrence of Back Pain and Back Injuries in Athletes?

The back is subjected to a great deal of strain in many sports. Up to 20% of all sports injuries involve an injury to the lower back or neck. Repetitive or high impact loads (e.g., running, gymnastics, skiing) and weight loading (e.g., weightlifting) affect the lower back. Rotation of the torso (e.g., golf, tennis) causes damage to both, the lumbar and thoracic spine. The cervical spine is most commonly injured in contact sports (e.g., boxing, football). One of the factors that increases the odds of injuries in athletes is excessive and rapid increases in training loads. In spite of currently emerging evidence on this issue, little is known about the balance between physiological loading on the spine and athletic performance, versus overloading and back pain and/or injury in athletes. This scoping review aims (i) to map the literature that addresses the association between the training load and the occurrence of back pain and/or injury, especially between the Acute:Chronic Workload Ratio (ACWR) and back problems in athletes of individual and team sports, and (ii) to identify gaps in existing literature and propose future research on this topic. A literature search of six electronic databases (i.e., MEDLINE, PubMed, Web of Science, SCOPUS, SportDiscus, and CINAHL) was conducted. A total of 48 research articles met the inclusion criteria. Findings identified that fatigue of the trunk muscles induced by excessive loading of the spine is one of the sources of back problems in athletes. In particular, high training volume and repetitive motions are responsible for the high prevalence rates. The most influential are biomechanical and physiological variations underlying the spine, though stress-related psychological factors should also be considered. However, limited evidence exists on the relationship between the ACWR and back pain or non-contact back injuries in athletes from individual and team sports. This may be due to insufficiently specified the acute and chronic time window that varies according to sport-specific schedule of competition and training. More research is therefore warranted to elucidate whether ACWR, among other factors, is able to identify workloads that could increase the risk of back problems in athletes.

The use of GPS and inertial devices for player monitoring in team sports: A review of current and future applications

Player-worn devices, combining global positioning system and inertial monitors, are being used increasingly by professional sports teams. Recent interest focusses on using the data generated to track trainingload and whether this may lead to more effective training prescription with better management of injury risk. The aim of this review is to summarize the development and current use of this technology alongside proposed future applications. PubMed and Medline searches (2000-2017) identified all relevant studies involving use in team sports or comparative studies with other accepted methods. Our review determined that the latest devices are valid and reliably track activity levels. This technology is both accurate and more efficient than previous methods. Furthermore, recent research has shown that measurable changes in trainingload (the acute-to-chronic load ratio) are related to injury risk. However, results remain very sport specific and generalization must be done with caution. Future uses may include injury-prevention strategies and return-to-play judgement.

Relationship Between Mechanical Effectiveness in Sprint Running and Force-Velocity Characteristics of a Countermovement Jump in Australian Rules Football Athletes

Morris, CG, Weber, JA, and Netto, KJ. Relationship between mechanical effectiveness in sprint running and force-velocity characteristics of a countermovement jump in Australian rules football athletes. J Strength Cond Res XX(X): 000-000, 2020-This study evaluated the mechanical determinants of 40-m sprint performance in elite Australian Rules Football (ARF) athletes and identified variables of countermovement jumps (CMJs) that related to the sprint. Fourteen elite male ARF athletes (age = 22.7 ± 3.6 years; height = 1.88 ± 0.08 m; mass = 88.2 ± 9.38 kg) completed two 40-m sprints and 3 CMJs. Sprint mechanics were calculated using inverse dynamic methods from sprint times, anthropometric and spatiotemporal data, whereas CMJ variables were obtained from in-ground force plates. Associations between sprint mechanics, sprint performance, and CMJ variables were identified using Pearson's correlation coefficient. A p-value of <0.036 was considered statistically significant for all analyses after performing Bonferroni correction adjustment. Relative peak running power was significantly correlated (p < 0.036, r = -0.781 to -0.983) with sprint split times across all distances (5-40 m). Relative maximum horizontal force significantly correlated with acceleration performance (0-20 m, p < 0.036, r = -0.887 to -0.989). Maximum running velocity was significantly correlated (p < 0.036, r = -0.714 to -0.970) with sprint times across 20-40 m. Relative peak force in the CMJ was significantly associated (p < 0.036, r = -0.589 to -0.630) with sprint kinetics (power and horizontal force) and 5-20-m sprint times. Jump height and concentric time in the CMJ were significantly (p < 0.036) correlated with sprint time at 20 m (r = -0.550 and r = 0.546), respectively. These results indicate emphasis should be placed on training protocols that improve relative peak power, particularly in time-constrained environments such as team sports, focusing on maximal force production or maximal running velocity ability. Furthermore, associations between CMJ variables and sprint performance provide practitioners with an approach to assess sprint performance in-season, monitor training adaptations and further individualize training interventions, without requiring maximal sprint testing.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Does Overexertion Correlate With Increased Injury? The Relationship Between Player Workload and Soft Tissue Injury in Professional American Football Players Using Wearable Technology

BACKGROUND

The relationship of training load to injury using wearable technology has not been investigated in professional American football players. The primary objective of this study was to determine the correlation between player workload and soft tissue injury over the course of a football season utilizing wearable global positioning system (GPS) technology.

HYPOTHESIS

Increased training load is associated with a higher incidence of soft tissue injuries.

STUDY DESIGN

Case-control study.

LEVEL OF EVIDENCE

Level 3.

METHODS

Player workloads were assessed during preseason and regular-season practice sessions using GPS tracking and triaxial accelerometry from 2014 to 2016. Soft tissue injuries were recorded during each season. Player workload during the week of injury (acute) and average weekly workload during the 4 weeks (chronic) prior to injury were determined for each injury and in uninjured position-matched controls during the same week. A matched-pairs t test was used to determine differences in player workload. Subgroup analysis was also conducted to determine whether observed effects were confounded by training period and type of injury.

RESULTS

In total, 136 lower extremity injuries were recorded. Of the recorded injuries, 101 injuries with complete GPS and clinical data were included in the analysis. Injuries were associated with greater increases in workload during the week of injury over the prior month when compared with uninjured controls. Injured players saw a 111% (95% CI, 66%-156%) increase in workload whereas uninjured players saw a 73% (95% CI, 34%-112%) increase in workload during the week of injury (P = 0.032). Individuals who had an acute to chronic workload ratio higher than 1.6 were 1.5 times more likely to sustain an injury relative to time- and position-matched controls (64.6% vs 43.1%; P = 0.004).

CONCLUSION

Soft tissue injuries in professional football players were associated with sudden increases in training load over the course of a month. This effect seems to be especially pronounced during the preseason when player workloads are generally higher. These results suggest that a gradual increase of training intensity is a potential method to reduce the risk of soft tissue injury.

CLINICAL RELEVANCE

Preseason versus regular-season specific training programs monitored with wearable technology may assist team athletic training and medical staff in developing programs to optimize player performance.

Hamstring rehabilitation in elite track and field athletes: applying the British Athletics Muscle Injury Classification in clinical practice

Rationale

Hamstring injuries are common in elite sports. Muscle injury classification systems aim to provide a framework for diagnosis. The British Athletics Muscle Injury Classification (BAMIC) describes an MRI classification system with clearly defined, anatomically focused classes based on the site of injury: (a) myofascial, (b) muscle–tendon junction or (c) intratendinous; and the extent of the injury, graded from 0 to 4. However, there are no clinical guidelines that link the specific diagnosis (as above) with a focused rehabilitation plan.

Objective

We present an overview of the general principles of, and rationale for, exercise-based hamstring injury rehabilitation in British Athletics. We describe how British Athletics clinicians use the BAMIC to help manage elite track and field athletes with hamstring injury. Within each class of injury, we discuss four topics: clinical presentation, healing physiology, how we prescribe and progress rehabilitation and how we make the shared decision to return to full training. We recommend a structured and targeted diagnostic and rehabilitation approach to improve outcomes after hamstring injury.

Developing Athlete Monitoring Systems in Team Sports: Data Analysis and Visualization

In professional team sports, the collection and analysis of athlete-monitoring data are common practice, with the aim of assessing fatigue and subsequent adaptation responses, examining performance potential, and minimizing the risk of injury and/or illness. Athlete-monitoring systems should be underpinned by appropriate data analysis and interpretation, to enable the rapid reporting of simple and scientifically valid feedback. Using the correct scientific and statistical approaches can improve the confidence of decisions made from athlete-monitoring data. However, little research has discussed and proposed an outline of the process involved in the planning, development, analysis, and interpretation of athlete-monitoring systems. This review discusses a range of methods often employed to analyze athlete-monitoring data to facilitate and inform decision-making processes. There is a wide range of analytical methods and tools that practitioners may employ in athlete-monitoring systems, as well as several factors that should be considered when collecting these data, methods of determining meaningful changes, and various data-visualization approaches. Underpinning a successful athlete-monitoring system is the ability of practitioners to communicate and present important information to coaches, ultimately resulting in enhanced athletic performance.

Getting the most out of intensive longitudinal data: a methodological review of workload-injury studies

OBJECTIVES

To systematically identify and qualitatively review the statistical approaches used in prospective cohort studies of team sports that reported intensive longitudinal data (ILD) (>20 observations per athlete) and examined the relationship between athletic workloads and injuries. Since longitudinal research can be improved by aligning the (1) theoretical model, (2) temporal design and (3) statistical approach, we reviewed the statistical approaches used in these studies to evaluate how closely they aligned these three components.

DESIGN

Methodological review.

METHODS

After finding 6 systematic reviews and 1 consensus statement in our systematic search, we extracted 34 original prospective cohort studies of team sports that reported ILD (>20 observations per athlete) and examined the relationship between athletic workloads and injuries. Using Professor Linda Collins' three-part framework of aligning the theoretical model, temporal design and statistical approach, we qualitatively assessed how well the statistical approaches aligned with the intensive longitudinal nature of the data, and with the underlying theoretical model. Finally, we discussed the implications of each statistical approach and provide recommendations for future research.

RESULTS

Statistical methods such as correlations, t-tests and simple linear/logistic regression were commonly used. However, these methods did not adequately address the (1) themes of theoretical models underlying workloads and injury, nor the (2) temporal design challenges (ILD). Although time-to-event analyses (eg, Cox proportional hazards and frailty models) and multilevel modelling are better-suited for ILD, these were used in fewer than a 10% of the studies (n=3).

CONCLUSIONS

Rapidly accelerating availability of ILD is the norm in many fields of healthcare delivery and thus health research. These data present an opportunity to better address research questions, especially when appropriate statistical analyses are chosen.

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

Aim: Relationships between athlete monitoring-derived variables and injury risk have been investigated predominantly in isolation. The aim of this study was to evaluate the individual and combined effects of multiple factors on the risk of soft-tissue non-contact injuries in elite team sport athletes. Methods: Fifty-five elite Australian footballers were prospectively monitored over two consecutive seasons. Internal and external training load was quantified using the session rating of perceived exertion and GPS/accelerometry, respectively. Cumulative load and acute-to-chronic workload ratios were derived using rolling averages and exponentially weighted moving averages. History of injuries in the current and previous seasons was recorded along with professional experience, weekly musculoskeletal screening, and subjective wellness scores for individual athletes. Individual and combined effects of these variables on injury risk were evaluated with generalized linear mixed models. Results: High cumulative loads and acute-to-chronic workload ratios were associated with increased risk of injuries. The effects for measures derived using exponentially weighted moving averages were greater than those for rolling averages. History of a recent injury, long-term experience at professional level, and substantial reductions in a selection of musculoskeletal screening and subjective wellness scores were associated with increased risk. The effects of high cumulative loads were underestimated by ~20% before adjusting for previous injuries, whereas the effects of high acute-to-chronic workload ratios were overestimated by 10-15%. Injury-prone players, identified via player identity in the mixed model, were at > 5 times higher risk of injuries compared to robust players (hazard ratio 5.4, 90% confidence limits 3.6-12) despite adjusting for training load and previous injuries. Combinations of multiple risk factors were associated with extremely large increases in risk; for example, a hazard ratio of 22 (9.7-52) was observed for the combination of high acute load, recent history of a leg injury, and a substantial reduction in the adductor squeeze test score. Conclusion: On the basis of our findings with an elite team of Australian footballers, the information from athlete monitoring practices in team sports should be interpreted collectively and used as a part of the injury prevention decision-making process along with consideration of individual differences in risk.

Methods of Monitoring Training Load and Their Association With Changes Across Fitness Measures in Hurling Players

Malone, S, Hughes, B, Collins, K, and Akubat, I. Methods of monitoring training load and their association with changes across fitness measures in hurling players. J Strength Cond Res 34(1): 225-234, 2020-The aim of the current investigation was to assess the dose-response relationship for various methods of monitoring training load (TL) and changes in aerobic and anaerobic fitness in hurling players. Training and match load measures were collected from 30 hurling players (speed at different blood lactate [vLT, vOBLA], maximal oxygen uptake [VO2max], speed at VO2max [vVO2max], peak treadmill velocity [PTV] running economy [RE] Yo-Yo intermittent recovery test (Yo-YoIR1, Yo-YoIR2), speed at 5, 10 , 20 m, and repeated sprint ability [6 × 35 m]) before and after during a 12-week in-season period. Mean weekly training and match loads as determined by s-RPE, bTRIMP, luTRIMP, eTRIMP, iTRIMP, and gTRIMP were correlated with each other, percentage change in VO2max, vVO2max, RE, PTV, the speed at blood lactate concentrations of 2 mmol·L (vLT) and 4 mmol·L (vOBLA), and YoYoIR1, Yo-YoIR2 performance. iTRIMP showed a trivial association with s-RPE and a small to moderate association with other heart rate-based methods. Small to large changes (effect size: 0.38-1.12) were observed in aerobic and anaerobic fitness measures were observed across the 12-week period. Trivial to very large associations (r = 0.11-0.78) were observed between TL variables and changes in fitness depending on the variable analyzed. iTRIMP was shown to have large to very large associations with changes in vOBLA {r = 0.78 (95% confidence interval [CI]: 0.71-0.88)}, VO2max (r = 0.77 [95% CI: 0.68-0.82]), RE (r = 0.77 [95% CI: 0.67-0.82]), Yo-YoIR1 (r = 0.69 [95% CI: 0.51-0.72]), and RSAb (r = 0.66 [95% CI: 0.60-0.72]) with moderate associations reported between iTRIMP and other variables. All other measures of TL showed trivial to moderate associations (r = 0.11-0.66). The current investigation shows that fully individualized training load (iTRIMP) measures may potentially offer a better understanding of dose-response relationships when compared with subjective and nonindividualized measures of TL to changes in aerobic and anaerobic fitness in team sports athletes; as such, it may be suggested that practitioners should use individualized measures of TL assessment within their day-to-day practices.

Relation Between Training Load and Recovery-Stress State in High-Performance Swimming

Background: The relation between training load, especially internal load, and the recovery-stress state is of central importance for avoiding negative adaptations in high-performance sports like swimming. The aim of this study was to analyze the individual time-delayed linear effect relationship between training load and recovery-stress state with single case time series methods and to monitor the acute recovery-stress state of high-performance swimmers in an economical and multidimensional manner over a macro cycle. The Acute Recovery and Stress Scale (ARSS) was used for daily monitoring of the recovery-stress state. The methods session-RPE (sRPE) and acute:chronic workload-ratio (ACWR) were used to compare different methods for quantifying the internal training load with regard to their interrelationship with the recovery-stress state. Methods: Internal load and recovery-stress state of five highly trained female swimmers [with a training frequency of 13.6 ± 0.8 sessions per week and specializing in sprint (50 and 100 m), middle-distance (200 and 400 m), or long distance (800 and 1,500 m) events] were daily documented over 17 weeks. Two different types of sRPE were applied: RPE^∗duration (sRPE^h) and RPE^∗volume (sRPE^km). Subsequently, we calculated the ratios ACWR^h and ACWR^km (sRPE last week: 4-week exponentially weighted moving average). The recovery-stress state was measured by using the ARSS, consisting of eight scales, four of which are related to recovery [Physical Performance Capability (PPC), Mental Performance Capability (MPC), Emotional Balance (EB), Overall Recovery (OR)], and four to stress [Muscular Stress (MS), Lack of Activation (LA), Negative Emotional State (NES), Overall Stress (OS)]. To examine the relation between training load and recovery-stress state a cross correlation (CCC) was conducted with sRPE^h, sRPE^km, ACWR^h, and ACWR^km as lead and the eight ARSS-scales as lag variables. Results: A large variation of training load can be observed in the individual week-to-week fluctuations whereby the single fluctuations can significantly differ from the overall mean of the group. The range also shows that the CCC individually reaches values above 0.3, especially with sRPE^km as lead variable. Overall, there is a large range with significant differences between the recovery and stress dimensions of the ARSS and between the training load methods, with sRPE^km having the largest span (Range = 1.16). High inter-individual differences between the athletes lie in strength and direction of the correlation | 0.66|≤ CCC ≥|-0.50|. The time delayed effects (lags 0-7) are highly individual, however, clear patterns can be observed. Conclusion: The ARSS, especially the physical and overall-related scales (PPC, OR, MS, OS), is a suitable tool for monitoring the acute recovery-stress state in swimmers. MPC, EB, LA, and NES are less affected by training induced changes. Comparably high CCC and Ranges result from the four internal load methods, whereby sRPE, especially sRPE^km, shows a stronger relation to recovery-stress state than ACWR. Based on these results and the individual differences in terms of time delay in training response, we recommend for swimming to use sRPE to monitor the internal training load and to use the ARSS, with a focus at the physical and overall-scales, to monitor the recovery-stress state.

Internal workload and non-contact injury: a one-season study of five teams from the UEFA Elite Club Injury Study

Background

Internal workload (ie, from training and matches) is considered one of the most important injury risk factors for elite European football teams, however there is little published evidence to support this belief.

Objective

We examined the association and predictive power of internal workload and non-contact injuries.

Methods

Five elite European teams, 171 players (age: 25.1±4.9 years; height: 181.6±6.7 cm; body mass: 77.5±7.2 kg) participated over one full competitive season. Using the session-rating of perceived exertion (s-RPE) method player’s internal workloads were calculated for acute week, week-to-week changes, cumulated weeks, chronic weeks and acute:chronic ratios and analysed for association with non-contact injury (using generalised estimating equations (GEE)). Associated variables from GEE analysis were categorised into very low to very high workload zones and checked for increased relative risks (RRs). Associated workload variables were also analysed for predictive power (receiver operating characteristics).

Results

Acute:chronic workload ratios at 1:3 and 1:4 weeks were associated with non-contact injury (P<0.05). Specifically, a greater risk of injury was found for players with an acute:chronic workload at 1:4 weeks of 0.97 to 1.38 (RR 1.68; 95% CI 1.02 to 2.78, likely harmful) and >1.38 (RR 2.13; 95% CI 1.21 to 3.77, very likely harmful) compared with players whose acute:chronic workload was 0.60 to 0.97. An acute:chronic workload 1:3 of >1.42 compared with 0.59 to 0.97 displayed a 1.94 times higher risk of injury (RR 1.90; 95% CI 1.08 to 3.36, very likely harmful). Importantly, acute:chronic workload at both 1:4 and 1:3 showed poor predictive power (area under the curve 0.53 to 0.58) despite previous reports and beliefs that it can predict injury.

Conclusions

This study provides evidence for the acute:chronic internal workload (measured using s-RPE) as a risk factor for non-contact injury in elite European footballers. However the acute:chronic workload, in isolation, should not be used to predict non-contact injury.

Innovations and pitfalls in the use of wearable devices in the prevention and rehabilitation of running related injuries

Running-related injuries are common and are associated with a high rate of reoccurrence. Biomechanics and errors in applied training loads are often cited as causes of running-related injuries. Clinicians and runners are beginning to utilize wearable technologies to quantify biomechanics and training loads with the hope of reducing the incidence of running-related injuries. Wearable devices can objectively assess biomechanics and training loads in runners, yet guidelines for their use by clinicians and runners are not currently available. This article outlines several applications for the use of wearable devices in the prevention and rehabilitation of running-related injuries. Applications for monitoring of training loads, running biomechanics, running epidemiology, return to running programs and gait retraining are discussed. Best-practices for choosing and use of wearables are described to provide guidelines for clinicians and runners. Finally, future applications are outlined for this rapidly developing field.

How much is too much? (Part 1) International Olympic Committee consensus statement on load in sport and risk of injury

Athletes participating in elite sports are exposed to high training loads and increasingly saturated competition calendars. Emerging evidence indicates that poor load management is a major risk factor for injury. The International Olympic Committee convened an expert group to review the scientific evidence for the relationship of load (defined broadly to include rapid changes in training and competition load, competition calendar congestion, psychological load and travel) and health outcomes in sport. We summarise the results linking load to risk of injury in athletes, and provide athletes, coaches and support staff with practical guidelines to manage load in sport. This consensus statement includes guidelines for (1) prescription of training and competition load, as well as for (2) monitoring of training, competition and psychological load, athlete well-being and injury. In the process, we identified research priorities.