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

2020 ◽  
Author(s):  
Stephen W. West ◽  
Jo Clubb ◽  
Lorena Torres-Ronda ◽  
Daniel Howells ◽  
Edward Leng ◽  
...  
Keyword(s):  
Injury Risk ◽  
Training Load ◽  
Decision Making Process ◽  
Sport Science ◽  
Load Monitoring ◽  
Potential Applications ◽  
Player Performance ◽  
And Training ◽  
Athlete Management

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

scholarly journals Monitoring Practices of Training Load and Biological Maturity in UK Soccer Academies

2020 ◽  
pp. 1-12
Author(s):  
Jamie Salter ◽  
Mark B.A. De Ste Croix ◽  
Jonathan D. Hughes ◽  
Matthew Weston ◽  
Christopher Towlson
Keyword(s):  
Injury Risk ◽  
Online Survey ◽  
Support Staff ◽  
Training Load ◽  
Premier League ◽  
Load Monitoring ◽  
Accelerated Growth ◽  
Biological Maturity ◽  
Dose Responses ◽  
And Training

Purpose: Overuse injury risk increases during periods of accelerated growth, which can subsequently impact development in academy soccer, suggesting a need to quantify training exposure. Nonprescriptive development scheme legislation could lead to inconsistent approaches to monitoring maturity and training load. Therefore, this study aimed to communicate current practices of UK soccer academies toward biological maturity and training load. Methods: Forty-nine respondents completed an online survey representing support staff from male Premier League academies (n = 38) and female Regional Talent Clubs (n = 11). The survey included 16 questions covering maturity and training-load monitoring. Questions were multiple-choice or unipolar scaled (agreement 0–100) with a magnitude-based decision approach used for interpretation. Results: Injury prevention was deemed highest importance for maturity (83.0 [5.3], mean [SD]) and training-load monitoring (80.0 [2.8]). There were large differences in methods adopted for maturity estimation and moderate differences for training-load monitoring between academies. Predictions of maturity were deemed comparatively low in importance for bio-banded (biological classification) training (61.0 [3.3]) and low for bio-banded competition (56.0 [1.8]) across academies. Few respondents reported maturity (42%) and training load (16%) to parent/guardians, and only 9% of medical staff were routinely provided this data. Conclusions: Although consistencies between academies exist, disparities in monitoring approaches are likely reflective of environment-specific resource and logistical constraints. Designating consistent and qualified responsibility to staff will help promote fidelity, feedback, and transparency to advise stakeholders of maturity–load relationships. Practitioners should consider biological categorization to manage load prescription to promote maturity-appropriate dose–responses and to help reduce the risk of noncontact injury.

scholarly journals Two Training-Load Paradoxes: Can We Work Harder and Smarter, Can Physical Preparation and Medical Be Teammates?

2017 ◽  
Vol 12 (s2) ◽  
pp. S2-50-S2-54 ◽  
Author(s):  
Tim J. Gabbett ◽  
Rod Whiteley
Keyword(s):  
Decision Making ◽  
Injury Risk ◽  
Early Stage ◽  
Support Staff ◽  
Training Load ◽  
Shared Decision ◽  
The Relationship ◽  
And Training ◽  
Physical Preparation

The authors have observed that in professional sporting organizations the staff responsible for physical preparation and medical care typically practice in relative isolation and display tension as regards their attitudes toward training-load prescription (much more and much less training, respectively). Recent evidence shows that relatively high chronic training loads, when they are appropriately reached, are associated with reduced injury risk and better performance. Understanding this link between performance and training loads removes this tension but requires a better understanding of the relationship between the acute:chronic workload ratio (ACWR) and its association with performance and injury. However, there remain many questions in the area of ACWR, and we are likely at an early stage of our understanding of these parameters and their interrelationships. This opinion paper explores these themes and makes recommendations for improving performance through better synergies in support-staff approaches. Furthermore, aspects of the ACWR that remain to be clarified—the role of shared decision making, risk:benefit estimation, and clearer accountability—are discussed.

scholarly journals Heart Rate Variability Responses to a Training Cycle in Female Youth Rowers

2020 ◽  
Vol 17 (22) ◽  
pp. 8391
Author(s):  
Rohan Edmonds ◽  
Julian Egan-Shuttler ◽  
Stephen J. Ives
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Cardiac Autonomic Function ◽  
Female Youth ◽  
Training Cycle ◽  
And Training

Heart rate variability (HRV) is a reputable estimate of cardiac autonomic function used across multiple athletic populations to document the cardiac autonomic responses to sport demands. However, there is a knowledge gap of HRV responses in female youth rowers. Thus, the purpose of this study was to measure HRV weekly, over a 15-week training period, covering pre-season and up to competition in youth female rowers, in order to understand the physiological response to long-term training and discern how fluctuations in HRV may relate to performance in this population. Measures of heart rate and heart rate variability were recorded before training each Friday over the monitoring period in seven athletes. Analysis of heart rate variability focused on time domain indices, the standard deviation of all normal to normal R–R wave intervals, and the root mean square of successive differences as markers of cardiac parasympathetic modulation. Training load was quantified by multiplying the rating of perceived exertion of the weeks training and training duration. A decrease was identified in cardiac parasympathetic modulation as the season progressed (Effect Size (Cohen’s d) = −0.34 to −0.8, weeks 6 and 11–15), despite no significant relationship between training load and heart rate variability. Factors outside of training may further compound the reduction in heart rate variability, with further monitoring of external stressors (e.g., school) in adolescent athletes.

Managing the Training Load in Adolescent Athletes

2017 ◽  
Vol 12 (s2) ◽  
pp. S2-42-S2-49 ◽  
Author(s):  
Andrew Murray
Keyword(s):  
Athletic Performance ◽  
Injury Risk ◽  
Systematic Approach ◽  
Training Load ◽  
Evidence Based ◽  
Adolescent Athletes ◽  
Training Dose ◽  
Modern Times ◽  
Load Monitoring ◽  
Athletic Development

While historically adolescents were removed from their parents to prepare to become warriors, this process repeats itself in modern times but with the outcome being athletic performance. This review considers the process of developing athletes and managing load against the backdrop of differing approaches of conserving and maximizing the talent available. It acknowledges the typical training “dose” that adolescent athletes receive across a number of sports and the typical “response” when it is excessive or not managed appropriately. It also examines the best approaches to quantifying load and injury risk, acknowledging the relative strengths and weaknesses of subjective and objective approaches. Making evidence-based decisions is emphasized, while the appropriate monitoring techniques are determined by both the sporting context and individual situation. Ultimately a systematic approach to training-load monitoring is recommended for adolescent athletes to both maximize their athletic development and allow an opportunity for learning, reflection, and enhancement of performance knowledge of coaches and practitioners.

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

2020 ◽  
Author(s):  
Stephen W. West ◽  
Sean Williams ◽  
Dario Cazzola ◽  
Simon Kemp ◽  
Matthew J. Cross ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Injury Risk ◽  
Tissue Injury ◽  
Soft Tissue Injury ◽  
Soft Tissue Injuries ◽  
Rugby Union ◽  
Training Load ◽  
Alternative Methods ◽  
Load Monitoring ◽  
The Relationship

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

scholarly journals Blood Biomarkers Variations across the Pre-Season and Interactions with Training Load: A Study in Professional Soccer Players

2021 ◽  
Vol 10 (23) ◽  
pp. 5576
Author(s):  
Filipe Manuel Clemente ◽  
Francisco Tomás González-Fernández ◽  
Halil Ibrahim Ceylan ◽  
Rui Silva ◽  
Saeid Younesi ◽  
...  
Keyword(s):  
Injury Risk ◽  
Perceived Exertion ◽  
Hematological Parameters ◽  
Blood Parameters ◽  
Training Load ◽  
Soccer Players ◽  
Immune Functions ◽  
Professional Soccer ◽  
Biochemical Analyses ◽  
And Training

Background: Pre-season training in soccer can induce changes in biological markers in the circulation. However, relationships between chosen hematological and biochemical blood parameters and training load have not been measured. Objective: Analyze the blood measures changes and their relationships with training loads changes after pre-season training. Methodology: Twenty-five professional soccer players were assessed by training load measures (derived from rate of perceived exertion- known as RPE) during the pre-season period. Additionally, blood samples were collected for hematological and biochemical analyses. Results: For hematological parameters, significant increases were found for platelets (PLT) (dif: 6.42; p = 0.006; d = −0.36), while significant decreases were found for absolute neutrophils count (ANC) (dif: −3.98; p = 0.006; d = 0.11), and absolute monocytes count (AMC) (dif: −16.98; p = 0.001; d = 0.78) after the pre-season period. For biochemical parameters, there were significant increases in creatinine (dif: 5.15; p = 0.001; d = −0.46), alkaline phosphatase (ALP) (dif: 12.55; p = 0.001; d = −0.84), C-reactive protein (CRP) (dif: 15.15; p = 0.001; d = −0.67), cortisol (dif: 2.85; p = 0.001; d = −0.28), and testosterone (dif: 5.38; p = 0.001; d = −0.52), whereas there were significant decreases in calcium (dif: −1.31; p = 0.007; d =0.49) and calcium corrected (dif: −2.18; p = 0.015; d = 0.82) after the pre-season period. Moreover, the Hooper Index (dif: 13.22; p = 0.01; d = 0.78), and all derived RPE measures increased after pre-season period. Moderate-to-very large positive and negative correlations (r range: 0.50–0.73) were found between the training load and hematological measures percentage of changes. Moderate-to-large positive and negative correlations (r range: 0.50–0.60) were found between training load and biochemical measures percentage of changes. Conclusions: The results indicated heavy physical loads during the pre-season, leading to a decrease in immune functions. Given the significant relationships between blood and training load measures, monitoring hematological and biochemical measures allow coaches to minimize injury risk, overreaching, and overtraining.

scholarly journals Quantifying Training and Game Demands of a National Basketball Association Season

2021 ◽  
Vol 12 ◽  
Author(s):  
Jennifer L. Russell ◽  
Blake D. McLean ◽  
Sean Stolp ◽  
Donnie Strack ◽  
Aaron J. Coutts
Keyword(s):  
Body Mass ◽  
External Load ◽  
Primary Objective ◽  
Training Load ◽  
National Basketball Association ◽  
Training Data ◽  
Basketball Players ◽  
Load Monitoring ◽  
Individualized Training ◽  
And Training

Purpose: There are currently no data describing combined practice and game load demands throughout a National Basketball Association (NBA) season. The primary objective of this study was to integrate external load data garnered from all on-court activity throughout an NBA season, according to different activity and player characteristics.Methods: Data from 14 professional male basketball players (mean ± SD; age, 27.3 ± 4.8 years; height, 201.0 ± 7.2 cm; body mass, 104.9 ± 10.6 kg) playing for the same club during the 2017–2018 NBA season were retrospectively analyzed. Game and training data were integrated to create a consolidated external load measure, which was termed integrated load. Players were categorized by years of NBA experience (1-2y, 3-5y, 6-9y, and 10 + y), position (frontcourt and backcourt), and playing rotation status (starter, rotation, and bench).Results: Total weekly duration was significantly different (p < 0.001) between years of NBA playing experience, with duration highest in 3–5 year players, compared with 6–9 (d = 0.46) and 10+ (d = 0.78) year players. Starters experienced the highest integrated load, compared with bench (d = 0.77) players. There were no significant differences in integrated load or duration between positions.Conclusion: This is the first study to describe the seasonal training loads of NBA players for an entire season and shows that a most training load is accumulated in non-game activities. This study highlights the need for integrated and unobtrusive training load monitoring, with engagement of all stakeholders to develop well-informed individualized training prescription to optimize preparation of NBA players.

scholarly journals Training Load and Its Role in Injury Prevention, Part I: Back to the Future

2020 ◽  
Vol 55 (9) ◽  
pp. 885-892
Author(s):  
Franco M. Impellizzeri ◽  
Paolo Menaspà ◽  
Aaron J. Coutts ◽  
Judd Kalkhoven ◽  
Miranda J Menaspà
Keyword(s):  
Injury Prevention ◽  
Injury Risk ◽  
Training Load ◽  
Training Process ◽  
Current State ◽  
Training Principles ◽  
Load Monitoring ◽  
Quantitative Indication ◽  
Practical Recommendations

The purpose of this 2-part commentary series is† to explain why we believe our ability to control injury risk by manipulating training load (TL) in its current state is an illusion and why the foundations of this illusion are weak and unreliable. In part 1, we introduce the training process framework and contextualize the role of TL monitoring in the injury-prevention paradigm. In part 2, we describe the conceptual and methodologic pitfalls of previous authors who associated TL and injury in ways that limited their suitability for the derivation of practical recommendations. The first important step in the training process is developing the training program: the practitioner develops a strategy based on available evidence, professional knowledge, and experience. For decades, exercise strategies have been based on the fundamental training principles of overload and progression. Training-load monitoring allows the practitioner to determine whether athletes have completed training as planned and how they have coped with the physical stress. Training load and its associated metrics cannot provide a quantitative indication of whether particular load progressions will increase or decrease the injury risk, given the nature of previous studies (descriptive and at best predictive) and their methodologic weaknesses. The overreliance on TL has moved the attention away from the multifactorial nature of injury and the roles of other important contextual factors. We argue that no evidence supports the quantitative use of TL data to manipulate future training with the purpose of preventing injury. Therefore, determining “how much is too much” and how to properly manipulate and progress TL are currently subjective decisions based on generic training principles and our experience of adjusting training according to an individual athlete's response. Our message to practitioners is to stop seeking overly simplistic solutions to complex problems and instead embrace the risks and uncertainty inherent in the training process and injury prevention.

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