ArticleLiterature Review

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

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Abstract

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

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... Load data can assist in planning the training process, informing decisions regarding any necessary adjustments in managing teams and individual players across desired cycles [5]. In this way, loads are commonly planned across microcycles during the season, varying from day-to-day within each week to best balance physical preparation and readiness for upcoming matches among players [5,6]. ...
... Load data can assist in planning the training process, informing decisions regarding any necessary adjustments in managing teams and individual players across desired cycles [5]. In this way, loads are commonly planned across microcycles during the season, varying from day-to-day within each week to best balance physical preparation and readiness for upcoming matches among players [5,6]. ...
... Furthermore, different competitions are likely to impose unique match scheduling, which may impact the weekly loading strategies adopted by teams [5]. Within an Australian context, few studies have quantified the loads experienced among professional, female soccer players competing in the Australian national A-League Women's competition. ...
... balance, agility and coordination) [9]. Furthermore, it has been acknowledged that regular testing can contribute to prevent injuries and overtraining by tracking training adaptions [6,9]. On the other hand, training methods aim to increase and optimise athletes' performance to cope with the specific demands of their sport [4,11]. ...
... In relation to an athlete's health status, an injury/health and performance relationship through a risk grading system between both constructs has been advocated [17]. Thus, assessing athletes through testing and monitoring may contribute to the identification of potential injury risks and health factors to develop further tailored performance-oriented training plans for physical and mental fitness [1,6,7,9,18]. Likewise, there is a need for snow sport-specific training approaches against one-sizefits-all practices to train and prepare athletes conveniently [1,5,7,13]. ...
... The current literature acknowledges and highlights the relationship of testing and training, through load monitoring, with injury risk prevention [6,11,19]. However, specific snow sports-specific research in these areas is limited and all the knowledge on these areas comes from personal experience and anecdotal information or remains protected and unpublished. ...
Article
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Background and Objective Competitive alpine skiing, snowboarding and freestyle skiing, all different in nature and risks, are known for their high injury and illness burden. Testing measures and training methods may be considered for athletes’ preparation to support performance enhancement while safeguarding their health. We explored the perspectives and perceptions of competitive alpine skiing, snowboarding and freestyle skiing stakeholders regarding testing and training practices in their competitive snow sports. Methods We conducted an exploratory qualitative study based on grounded theory principles through 13 semi-structured interviews about testing and training practices with athletes, on-snow and off-snow coaches, managers and healthcare providers from different national teams. The interviews were inductively analysed through a constant comparative data analysis. Results Participants described winning as the end goal of testing and training practices, which requires athletes to perform in their best condition. To do so, they mentioned two main targets: performance enhancement and health protection. Participants acknowledged health as a premise to perform optimally, considering testing and monitoring approaches, goal setting, and training to support and protect athlete performance. This continuous cyclic process is driven by communication and shared decision making among all stakeholders, using testing and monitoring outputs to inform goal setting, training (e.g. on-snow and off-snow) and injury prevention. Such an approach helps athletes achieve their goal of winning while being fit and healthy throughout their short-term and long-term athletic career development. Conclusions The ultimate goal of testing measures and training methods in such competitive snow sports is winning. Performance enhancement and health protection act as pillars in systematic, tailored and flexible processes to guarantee athletes’ best preparation to perform. Moreover, athletes’ assessments, goal setting, monitoring tools, open communication and shared decision making strongly guide this cyclic process.
... Load management has been defined by the International Olympic Committee as "the appropriate prescription, monitoring and adjustment of external and internal [training] loads," 1 which summarizes the traditional concepts of physical training, periodization, and programming, where the aim is to optimize performance (and minimize the risk of injury). 2 Individualized strategies for load management have been integrated across sports, focusing on the multiple inputs and outputs to monitor responses, including heart rate, self-reported outcome, neuromuscular, cognitive, and sport performance. 3 However, in recent years, the concept of "load management" and more specifically, the relationship between training load and injuries has become one of the most widely studied areas of sports medicine, 4 generating debate in both research and public domain. 5 From everyday members of the public to the athletes pushing the boundaries of human performance, the explosion of health technologies and data availability has catapulted this topic into the mainstream, for both the right and wrong reasons. ...
... Adding layers of complexity to these everyday decisions are the countless contextual factors that members of the multidisciplinary team must account for, including player-level factors (eg, physical, psychological, and demographic); environmental factors (eg, weather, surface type, equipment); and team-level factors (eg, match related). 3 This complexity is not unique to sport and exists in most other fields (eg, medicine, sociology, economics). Another challenge in sport relates to the validity and effectiveness of currently available load monitoring tools to support decision making for injury prevention. ...
... These issues impair the ability to evaluate both (1) causal links between load and injury 13 and (2) decision analyses that weigh the cost-benefit of different load scenarios. 3 Perhaps the most important path toward improving study design and methodological quality is to collaborate with knowledgeable, experienced statisticians and epidemiologists in the specific area of inquiry, which can aid in removing barriers to solving these important questions. These collaborations are expected to help clarify the specific injury outcome (due to the multifactorial nature of injury), provide clarity on the causal assumptions (including the clarification of the use of proxies vs direct measures), and identify sufficient sample sizes that improve the scientific investigation. ...
Article
Background : The optimization of athlete training load is not a new concept; however in recent years, the concept of “load management” is one of the most widely studied and divisive topics in sports science and medicine. Purpose : Discuss the challenges faced by sports when utilizing training load monitoring and management, with a specific focus on the use of data to inform load management guidelines and policies/mandates, their consequences, and how we move this field forward. Challenges : While guidelines can theoretically help protect athletes, overzealous and overcautious guidelines may restrict an athlete’s preparedness, negatively influence performance, and increase injury risk. Poor methods, wrong interpretation of study findings, and faulty logic do not allow for systematic scientific evaluations to inform guidelines. Practical Solutions : Guidelines and mandates should be developed through a systematic research process with stronger research designs and clear research questions. Collaborating with statistical and epidemiological experts is essential. Implementing open science principles and sharing all sports training load data increase transparency and allow for more rapid and valid advancements in knowledge. Practitioners should incorporate multiple data streams and consider individual athlete responses, rather than applying broad guidelines based on average data. Conclusion : Many current training load guidelines and mandates in sports come from good intentions; however, they are arbitrary without sound knowledge of the underlying scientific principles or methods. Common sense guidelines are helpful when there is sparse literature, but they should be careful to avoid arbitrarily choosing findings from weak research. Without precise scientific inquiries, implementing training load interventions or guidelines can have negative implications.
... 5 Therefore, successful athlete monitoring ensures that the training is effective and mitigates risks such as injury, illness, burnout, and overtraining. 3,5,6 The potential health and performance benefits of athlete monitoring, along with the increased accessibility and affordability of athlete monitoring tools and software, have led to its widespread adoption across all levels of sports. [7][8][9] The democratisation of athlete monitoring can be attributed to scientific and technological advancements leading to the growth of devices and software with enhanced quantity and quality of data and information. ...
... 3,13 However, as there is no single recipe for success in athlete monitoring, 14,15 coaches and support staff are advised to measure what is necessary and sustainable. 2,3,16 Recently, West et al. 6 suggested that the most valuable athlete monitoring tools provide accurate data to inform performance-related decisions while minimising athlete and practitioner burden. In a systematic review, McGuigan et al. 17 in 2020 summarised the training monitoring tools that coaches and support staff use in various sports and found that commonly used monitoring tools were inexpensive, non-invasive and could monitor multiple athletes simultaneously. ...
... Since then, considerable athlete monitoring research has been conducted leading to multiple reviews and consensus statements mainly on athlete monitoring tools and methods. 1,3,6,[18][19][20][21] Recognising that athlete monitoring is a human-driven process, it is imperative to learn from the coaches and support staff given their extensive knowledge and expertise accrued by working closely with athletes and athlete monitoring data. Consequently, studies on the perspectives, knowledge, beliefs, opinions, and experiences of coaches and support staff are integral to enhance our understanding and knowledge of the athlete monitoring field. ...
Article
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Objectives To map and summarise the sports coaches’ and support staff's perspectives on athlete monitoring to explore the breadth of literature, identify knowledge gaps and inform future research. Design Scoping review based on the Joanna Briggs Institute (JBI) methodology. Methods SPORTDiscus, MEDLINE, APA PsycInfo, and Embase databases were searched in English until 6 September 2022. The inclusion criteria were (1) coach(es) and/or support staff were explicitly questioned about their knowledge, perceptions, understanding, opinions, and/or applied practice of athlete monitoring; (2) results could be directly attributed to coach(es) and/or support staff; (3) primary research projects that are available as full-text. Exclusion criteria were applied for grey literature. The data were extracted into a custom-made data charting spreadsheet. Results From the 4381 identified records, 42 met the eligibility criteria. Almost all the studies were conducted within the Anglosphere and at the national or international level. The main reasons for coaches and support staff to implement athlete monitoring were to reduce injury and illness, inform the training program, and improve or maintain performance. While training load monitoring is generally seen as valuable the coaches and support staff acknowledged that there was no perfect scientific approach to monitoring athletes and believed it should be part of the bigger picture, emphasising communication. Conclusions There has been a recent surge in research demonstrating that athlete monitoring extends beyond quantitative information and encompasses non-quantified subjective information. This further substantiates that coaches and support staff will remain central to athlete monitoring, even amidst the anticipated technological progress.
... 32,33 Systematic training and regular tournaments accumulate load. 34 This load can vary with a certain frequency, intensity and duration. 2 The load entity is classified as external (training or game dose) and internal (psychobiological responses to the implemented external load). ...
... Furthermore, such metrics must have good reliability, validity and usefulness. 1,34 Individualization of loads in team sports is of great practical use, because the stimuli imposed on players during sessions tend to be uniform, almost homogeneous. On a few occasions, in training, players are separated into small groups respecting their tactical position. ...
... In other words, it is something extremely complex and imperfect, with great dependence on the interpretation carried out by the responsible practitioners. 34 Adding to this, it is known that each different biological tissue of the body has its own threshold of tolerance to loads. 6,25,27,47 With this in mind, blindly believing that an ACWR value above 1.5 implies a high susceptibility to injuries or their recurrence is disregarding the general profile of the athlete (robust or fragile, young or veteran). ...
Article
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Planning the periodization of training loads in harmony with the different periods of the season is a unique role for members of the sports team staff. Therefore, the objective of this study is to describe the distribution of training loads in microcycles and mesocycles in competitive basketball through a narrative review of the literature. In a consultation in three electronic databases (Google Scholar, PubMed and Science Direct) in Portuguese, English and/or Spanish, a total of 45 primary scientific articles were chosen that addressed the distribution of training loads in basketball and team sports in set with 21 complementary secondary references on the main thematic. It was demonstrated that compulsory load is a basic entity necessary to raise performance levels in the sporting form. Monitoring and numerically controlling the external load imposed can result in favorable responses in the internal load of athletes. In this aspect, some key metrics collaborate effectively, such as: acute-chronic workload ratio, monotony index and strain index. Short-term microcycles make it possible to see the horizontal distribution of loads, built session after session. In contrast, mesocycles group several consecutive microcycles to adjust loads vertically. Invariably, a rational and logical long-term distribution can result in improvements in athletic performance and low injury incidence. However, to achieve these objectives through the systematic periodization of loads, it is necessary to face pedagogical problems that belong to a multidimensional sphere. That is, we are manipulating an extremely complex and imperfect construct, with great dependence on the interpretation made by responsible practitioners.
... This provides the capability to report GPS-derived metrics such as total distance, maximum speed, and high-speed running distance, alongside accelerometer-derived metrics such as the number or intensity of impacts, and estimation of load from the accumulation of instantaneous accelerations experienced by the athlete (e.g., PlayerLoad, Dynamic Stress Load, or Body Load) (4,21,35). The importance of monitoring athlete performance is widely accepted and publicized (17,28,36,37). Some key areas of athlete performance in which this technology has been applied are athlete load monitoring (8,14,35), training optimization (14,27), tactical analysis (3,30), and injury risk reduction (8,35). ...
... Some key areas of athlete performance in which this technology has been applied are athlete load monitoring (8,14,35), training optimization (14,27), tactical analysis (3,30), and injury risk reduction (8,35). The technology allows practitioners to gain greater insight into athlete performance and help to make informed decisions regarding athlete load management (17,27,37). This, combined with the introduction of new and improving technologies, means the area of athlete monitoring is ever evolving to optimize practices (29,37). ...
... The technology allows practitioners to gain greater insight into athlete performance and help to make informed decisions regarding athlete load management (17,27,37). This, combined with the introduction of new and improving technologies, means the area of athlete monitoring is ever evolving to optimize practices (29,37). ...
Article
Monitoring training load is essential for optimizing the performance of athletes, allowing practitioners to assess training programs, monitor athlete progress, and minimize the risk of injury and overtraining. However, there is no universal method for training load monitoring, and the adoption of wearable global positioning system (GPS) and accelerometer technology in team sports has increased the volume of data and therefore the number of possible approaches. This survey investigated the usage, applications, and understanding of this technology by team sports practitioners. Seventy-two practitioners involved in team and athlete performance monitoring using GPS and accelerometer technology completed the survey. All respondents reported supporting the use of GPS technology in their sport, with 70.8% feeling that GPS technology is important for success. Results showed 87.5% of respondents use data from wearable technology to inform training prescription, while only 50% use the data to influence decisions in competition. Additionally, results showed GPS metrics are used more than accelerometer-derived metrics, however both are used regularly. Discrepancies in accelerometer usage highlighted concerns about practitioners’ understanding of accelerometer-derived metrics. This survey gained insight into usage, application, understanding, practitioner needs, and concerns and criticisms surrounding the use of GPS and accelerometer metrics for athlete load monitoring. Such information can be used to improve the implementation of this technology in team sport monitoring, as well as highlight gaps in the literature that will help to design future studies to support practitioner needs.
... 4 Recently, Weakley et al 5 expanded this description as "testing athletes as they train and perform without specific intervention." This has since received significant attention on social media 6 and now within peer-reviewed publications (Supplementary Material S1 [available online] [7][8][9][10][11][12][13] ). Developing invisible monitoring methods are attractive to practitioners to minimize burden on players (eg, performing a maximal effort or repeatedly completing the same questionnaire) and staff (eg, time-consuming collection and analysis of data). ...
... It is clear that invisible monitoring approaches aim to elicit less disruption to practice and daily operations therefore the extent of monitoring burden placed onto both athletes and staff by a measurement tool is clearly a fundamental subdimension. 10 The initial definition proposed by Delaney 4 suggested that invisible monitoring strategies aim to maximize the data collected routinely with the athlete suggesting an increased frequency of observations than traditional approaches. Burden is often composed of 2 subdimensions related to the probability an event can occur (ie, frequency) and the associated consequences of the measured event (eg, magnitude, severity). ...
Article
Background : Practices to routinely monitor athletes are rapidly changing. With the concurrent exponential rise in wearable technologies and advanced data analysis, tracking training exposures and responses is widespread and more frequent in the athlete–coach decision-making process. Within this scenario, the concept of invisible monitoring emerged, which was initially vaguely defined as testing athletes without testing them. Despite sound practical applications and benefits (eg, reduced burden on player staff and more frequent measurement), a clear lack of constitutive definition has led to multiple cleavages in both research and practice, including ethical concerns. Purpose : The purpose of this study is to (1) extend the current conceptualization of invisible monitoring by considering subdimensions of the concept and (2) its data-related and ethical challenges and (3) provide practical considerations to implement invisible monitoring. Monitoring burden (degree of obtrusion and frequency of measurement) and the number of constructs a single measurement tool can assess have been proposed as subdimensions of the concept of invisible monitoring. Challenges include the governance and analysis of data required to make estimates, validity and reliability of an invisible monitoring measure, and communication to athletes. Conclusions : This commentary presents a first attempt to conceptualize invisible monitoring in the context of elite sport and provide subdimensions of the concept that can be used to classify choices of measurement tools. A consensus is required from both researchers and practitioners regarding its definition and operationalization to optimize current monitoring services to elite athletes.
... 1,9 Modulating variables relating to the duration, intensity, frequency, distribution, and nature of training can directly influence the physical stimulus elicited. 10,11 This is of particular importance when considering the prescription of a soccer-specific training plan and its effects 12 on the development of youth players physical abilities. ...
... 19 Indeed, another key aspect to consider when evaluating the load prescribed within a training plan is the variability of the physical stimulus, widely considered to be one of the primary drivers of training adaptation. 2,27,28 This is of relevance for youth soccer players, who have not yet reached their full physical development 11 and there is an emphasis on developing their physical capacities as they progress through the academy. Indeed, the loading strategies applied during in-season training of elite adult soccer players 7,9,22,25 may not be appropriate for younger athletes. ...
Article
This study aimed to describe the distribution of training load (session rating of perceived exertion (sRPE), duration, and sRPE-training load) across weekly microcycles of an elite youth academy and assess the differences between four different age groups (U15-U16-U17-U19). Training load variables were recorded during in-season training weeks over 5 competitive seasons (from 2014–15 to 2018–19, evaluating new squads for each age group each season) for a total of 456 player observations. Mixed models assessed the variability of the three load variables across the different training days of a weekly microcycle and between the four different age groups. Estimated marginal means, 95% confidence intervals (CI), and effect sizes (d) were calculated for each training day of the microcycle. The main findings were significant differences in the training load variables three and four days before the next Match Day (i.e., MD-3 and MD-4, respectively), with U15 recording lower sRPE (−2.0 AU, d = 0.43–0.72) and U19 a lower duration (−35 min, d < -1.10). All age groups reduced sRPE-training load in the two days before a match, mainly due to a decrease in training duration (−160 AU & −17 min respectively). Match days provided the highest training loads within the weekly microcycle, with moderate-to-large differences between the four age groups (d = 0.77, 1.16 and 1.38 for U15 vs U16-U17-U19 respectively). The low variability in sRPE values in the three central sessions of a weekly microcycle indicates that training duration is an important factor to control when aiming to manipulate within-week training loads in elite youth soccer players.
... Information relating specifically to youth soccer players is critical because findings recorded by adult players (11,28,32,34) may not be relevant to younger, less mature players (43). Gaining a greater understanding of the differences between youth and senior players may be used to inform training programming decisions with these specific age groups. ...
... However, different methods in identifying starters and nonstarters make comparisons between studies difficult (16,19). Additional compensatory training completed by nonstarters may play an important role in player preparation by protecting from reductions in chronic load, potentially protecting against increased injury risk and loss of fitness (43). Indeed, any small deficits in training load between matches may accumulate into large differences when considered across an entire competitive season (16). ...
Article
Connolly, DR, Stolp, S, Gualtieri, A, Ferrari Bravo, D, Sassi, R, Rampinini, E, and Coutts, AJ. How do young soccer players train? A 5-year analysis of weekly training load and its variability between age groups in an elite youth academy. J Strength Cond Res 38(8): e423–e429, 2024—The aim of this study was to quantify the session rating of perceived exertion (sRPE), duration, and training load accrued across typical training weeks undertaken by youth soccer players. Differences between starters, nonstarters, and variations in training load variables were also investigated. Data were collected from 230 elite youth players in 4 age groups (U15, U16, U17, and U19) during 5 competitive seasons. Mixed models were used to describe variation between age groups and compare starters with nonstarters, with season as a fixed covariate effect. Week-to-week variation in training load was expressed as the percentage coefficient of variation. The main findings may be used to highlight a significant effect of age and playing status on training intensity, duration, and internal training load. Weekly training load increased progressively from the U15 to U17, with significant differences between each age group ( p < 0.03). Lower mean weekly perceived intensity (sRPE) was noted in U15 when compared with the older age groups (4.2 vs. 4.6–4.9 arbitrary unit for U16 to U19, p < 0.001). Low weekly training load variation was observed across the different phases of the season in each age group, with the preseason exhibiting the greatest variance (3.6–6.2%). Differences in the training load are likely more attributable to changes in training duration rather than sRPE. Control of session duration seems to play an important role when aiming to control load in the academy environment, and practitioners should closely monitor the differences in duration and load being recorded between starters and nonstarters.
... The collection, refinement, analysis, interpretation, and dissemination of loading data are usually performed with the aim of improving player performance and/or managing injury risk [64]. To achieve these results, soccer practitioners try to optimize the load at different stages of the training process, through several strategies such as the adjustment of individual sessions, the day-to-day planning, the periodization of the season, and the management of players with a long-term vision [64]. ...
... The collection, refinement, analysis, interpretation, and dissemination of loading data are usually performed with the aim of improving player performance and/or managing injury risk [64]. To achieve these results, soccer practitioners try to optimize the load at different stages of the training process, through several strategies such as the adjustment of individual sessions, the day-to-day planning, the periodization of the season, and the management of players with a long-term vision [64]. However, other authors indicate that the training or match load can show whether the planned load was realized by the player but in no case can it predict when a player will be injured [19]. ...
Article
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The aims of the study were to analyze the effects of a 12-week maximal strength- training program on injury incidence, injury burden, and physical fitness in semi-professional soccer players and to compare the perceived exertion load and well-being state between injured and non-injured soccer players. Twenty semi-professional male soccer players participated in this study. Participants were randomly allocated to an experimental group (EG, n = 10 players), who performed a maximal strength-training program, or to a control group (CG, n = 10 players), who only performed their regular soccer training. Physical fitness was measured at baseline and after the training program. In addition, the injury incidence, burden, training/match load, and the state of well-being of the players were recorded. The EG showed significant improvements in vertical jumps, change in direction ability, linear sprints, repeated sprint ability, isometric strength (p < 0.003; effect size = 1.78–11.86), and quadriceps–hamstring imbalance in both legs (p < 0.001; effect size = 2.37–3.71) in comparison to the CG. In addition, the EG players showed a significantly (p < 0.05) lower injury burden (p < 0.001, relative risk = 5.05, 95% confidence interval = 3.27–7.79). This study demonstrated the beneficial effects of a 12-week maximal strength-training program on physical fitness attributes and injury burden in semi-professional soccer players.
... The same test is used in the general population as a biomarker of athletic fitness related to health and physical performance [14]. Thus, athletes typically exhibit better cardiac autonomic function, characterised by greater heart rate variability, compared to non-athletes [15,16]. ...
Article
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Heart rate variability (HRV) is a non-invasive health and fitness indicator, and machine learning (ML) has emerged as a powerful tool for analysing large HRV datasets. This study aims to identify athletic characteristics using the HRV test and ML algorithms. Two models were developed: Model 1 (M1) classified athletes and non-athletes using 856 observations from high-performance athletes and 494 from non-athletes. Model 2 (M2) identified an individual soccer player within a team based on 105 observations from the player and 514 from other team members. Three ML algorithms were applied —Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM)— and SHAP values were used to interpret the results. In M1, the SVM algorithm achieved the highest performance (accuracy = 0.84, ROC AUC = 0.91), while in M2 Random Forest performed best (accuracy = 0.92, ROC AUC = 0.94). Based on these results, we propose an athleticism index and a soccer identification index derived from HRV data. The findings suggest that ML algorithms, such as SVM and RF, can effectively generate indices based on HRV for identifying individuals with athletic characteristics or distinguishing athletes with specific sports profiles. These insights underscore the importance of integrating HRV assessments systematically into training regimens for enhanced athletic evaluation.
... These diverse loads can cumulatively impact the perception of stress, leading to varying physiological responses. Recognizing the multifaceted nature of stress and load underscores the importance of a holistic approach in managing athlete well-being, where both physical training and external stressors are considered to optimize performance and health (West et al., 2021). ...
Article
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Introduction The aim of this study was to investigate the associations between subjective and objective measures of stress and load in elite male handball players at both the group and individual levels. Methods In this 45-week prospective cohort study, 189 elite male handball players weekly reported their perceived stress and load across training, competition, academic, and work domains. Blood samples were collected five times during the 2022/23 season to measure cortisol and the free testosterone to cortisol ratio (FTCR). We derived a “load” variable as the sum of training, competition, academic and work hours and calculated acute, chronic, and acute-to-chronic ratio variables for both load and stress. Associations between subjective and objective measures were analyzed using Spearman’s rank correlation. Results Weak to moderate positive associations were found between load and perceived stress ( r = 0.19 to 0.46, p < 0.001), and between perceived stress and cortisol ( r = 0.10, p = 0.023). Weak negative associations were found between perceived stress and FTCR ( r = −0.18 to −0.20, p < 0.001) and between load and FTCR ( r = −0.13, p = 0.003). A total of 86% of athletes had positive associations between stress and load (47% weak, 34% moderate, 5% high); 78% between stress and cortisol (27% weak, 22% moderate, 29% high); and 63% demonstrated negative associations between FTCR and load (18% weak, 32% moderate, 13% high). Conclusion This study highlights the complexity between subjective and objective measures of stress and load in athletes. Understanding the link between these measures may help coaches and sports scientists streamline athlete monitoring. In cases where moderate to strong associations exist, subjective measures might serve as a reliable substitute for objective ones, making the monitoring process more time- and cost-efficient.
... Monitoring individual athlete training loads in team sports is used to quantify physiological demands during training and competition [1,2]. Athlete training load data can inform programming decisions regarding the dosage, frequency, intensity, and volume of training loads, which take priority during the competitive season [3]. ...
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External (EL) and internal (IL) load are commonly used methods used to quantify training load in team sports. Playing time and playing position may influence the training loads for specific athletes throughout a season. The purpose of the current study was to evaluate the effect of athlete playing status and individual in-season practices on EL and IL across a collegiate women’s basketball season. Female basketball athletes were classified as high-minute (HMA; ≥15 min/game) or low-minute (LMA; <15 min/game) and wore microsensors during 53 practices for a total of 583 data points. EL was obtained via an inertial measurement unit (IMU) device that contained a triaxial accelerometer to obtain three-dimensional positioning data. IL and strength training (ST) load were determined via session rating of perceived exertion (sRPE) to create a daily summated value. Descriptive statistics indicate that athletes experienced individual differences in EL, ST, and IL throughout the season. A growth model showed that HMAs experienced higher EL than LMAs at the start of the season for practices (90.21 AU). Across all athletes, IL increased across the season (40.11 AU) and for each 1 unit of change in EL, IL increased by 1.04 AU. Repeated measures correlations identified a large relationship between IL and EL (r = 0.51, p < 0.001). A location-scale model indicated that the within-person variability of IL across all athletes was 3.29 AU but was not due to athlete playing status. It is recommended to base in-season training on individual loads and game demands to promote athlete readiness and improved sport performance.
... The primary aim of training load monitoring is to maximise competitive performance and reduce the opportunity for injuries (Booth et al., 2018;West et al., 2021). For example, excessive training loads with inadequate recovery may lead to suboptimal performance and an increased risk of injury due to heightened fatigue (Lambert et al., 2010;Vanrenterghem et al., 2017). ...
Article
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Field‐based team sports typically perform mixed‐modality training, incorporating both field‐ and resistance‐based sessions. As such, the availability of useful and reliable methods to monitor the internal and external training loads of all modalities is essential for planning effective training. Twenty‐one junior developmental female rugby league athletes (age: 17.5 ± 0.5 years, height: 167.7 ± 4.6 cm, body mass: 71.1 ± 12.9 kg, and training age: 2.3 ± 1.1 year) performed two to three resistance training sessions a week for 20 weeks (9 weeks preseason and 11 weeks in‐season). The volume load method and session rating of perceived exertion (sRPE) were used to quantify the external and internal load of the resistance training sessions, respectively. Volume load was categorised into either dynamic, plyometric, maximal or repeated efforts. Multiple linear mixed models were performed to determine whether significant relationships were present between the changes in volume load components and sRPE throughout the season. Significant relationships were identified between a decrease in sRPE, with associated increases in absolute and relative overall volume load (T1,725.5 = −2.1, p = 0.04; T1,133.5 = −2.2, p = 0.03), and relative dynamic (T1,24.1 = −8.4, p < 0.01) and lower‐body plyometric efforts (T1,16.8 = −17.2, p < 0.01). Conversely, significant relationships were observed between an increase in sRPE, with associated increases in relative lower‐body (T1,20.3 = 12.9, p < 0.01) and upper‐body repeated efforts (T1,28.5 = 9.7, p = 0.03) as well as relative upper‐body plyometric (T1,71.1 = 2.9, p = 0.01) and maximal efforts (T1,75.3 = 3.4, p < 0.01). These findings highlight the practicality of the volume load method for planning and monitoring resistance training in field‐based team sport athletes, providing useful data for the planning of specific exercises within the in‐season training week.
... Ultimately, utilising these monitoring tools to identify the competition loads and help athletes prepare for them adequately is a significant benefit. They can also be employed to compare the coaches' prescribed loads against what the athlete actually experienced and thus to create more individualised plans for athletes [43]. Finally, they can also modify any risk-adverse training load strategies that may have been implemented based on previous research conducted in other sports. ...
Article
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Training load monitoring is employed to quantify training demands, to determine individual physiological adaptions and to examine the dose-response relationship, ultimately reducing the likelihood of injury and making a meaningful impact on performance. The purpose of this study is to explore the relationship between training load and injury in competitive swimmers, using the session rate of perceived exertion (sRPE) method. Data were collected using a prospective, longitudinal study design across 104 weeks. Data were collected from 34 athletes centralised in two of Swim Ireland's National Centres. Bayesian mixed effects logistic regression models were used to analyse the relationship between sRPE-TL and medical attention injuries. The average weekly swim volume was 33.5 ± 12.9 km. The weekly total training load (AU) averaged 3838 ± 1616.1. A total of 58 medical attention injury events were recorded. The probability of an association between training load and injury ranged from 70% to 98%; however, evidence for these relationships was deemed weak or highly uncertain. The findings suggest that using a single training load metric in isolation cannot decisively inform when an injury will occur. Instead, coaches should utilise monitoring tools to ensure that the athletes are exposed to an appropriate training load to optimise physiological adaptation. Future research should strive to investigate the relationship between additional risk factors (e.g., wellbeing, lifestyle factors or previous injury history), in combination with training load and injury, in competitive swimmers.
... Одной из наиболее современных технологий видео аналитики, используемой в спорте, является технология виброизображения (Минкин, 2007;Луткова, 2022;Minkin, Nikolaenko, 2008). При этом каждая спортивная специализация отличается своими особенностями при контроле тренировочной нагрузки и психологической подготовкой спортсменов (West et al., 2021). ...
Conference Paper
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Проведено исследование изменени я эмоциональных, психофизиологических и поведенческих параметров квалифицированных спортсменов в тренировочном процессе с помощью технологии виброизображения. Измерение поведенческих характеристик гребцов проводилось до и после максимального теста на гребном эргометре «Концепт-2», моделирующем соревновательное упражнение «гребля на дистанции 1000 м», а также оценивалась достоверность изменений изучаемых характеристик. Выполнено сравнение психофизиологического профиля гребцов, полученного программой Профайлер+, с общим психофизиологическим профилем по значимой выборке. Выработаны рекомендации по регулированию тренировочной нагрузки и коррекции индивидуального психофизиологического профиля при оперативном и периодическом контроле гребцов программами ВибраМЕД и Профайлер+. The study of changes in the emotional, psychophysiological and behavioral parameters of qualified athletes in the training process using vibraimage technology was conducted. The behavioral characteristics of the rowers were measured before and after the maximum test on the rowing ergometer “Concept-2”, which simulates the competitive exercise “rowing at a distance of 1000 m”, and the reliability of the studied characteristics was also evaluated. The comparison of the psychophysiological profile of rowers calculated by Blitz Judgment program with the general psychophysiological profile for a significant sample was performed. Recommendations have been developed for regulating the training load and individual psychophysiological profile with operational and periodic monitoring of rowers by VibraMED and Blitz Judgment programs.
... Furthermore, it is challenging to identify clear evidence to favor one metric over another. Some authors [94][95][96] point out that papers claiming to have found one single metric that can help to signifcantly reduce injuries are simply not methodologically sound and lack good scientifc practice. A holistic, i.e., multivariate, monitoring system that is individualized not only to the needs of athletes but also to those of coaches seems to be a promising solution for elite basketball. ...
Article
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Athlete monitoring systems (AMSs) provide a centralized platform for integrating, processing, analyzing, and graphing various monitoring data to help coaches manage the rigorous demands of elite men’s basketball players, who frequently participate in high-stress games with minimal recovery time. This review synthesizes current challenges in deploying AMSs, underscores their role in injury prevention and performance optimization, and discusses technological advances that could enhance their utility. Key challenges include selecting appropriate monitoring methods based on human and financial resources, accuracy of data collection, real-time data processing, and personalization of training regimens. Due to the weaknesses and limitations of each monitoring method, it is recommended that both objective (e.g., external load data, heart rate measures, and biomarkers) and subjective (athlete-reported outcome measures) monitoring data be integrated into an AMS to provide a holistic insight of the athlete’s health and readiness. In addition, decision support systems integrated into an AMS can help coaches quickly gain an overview of their players’ current condition and make informed decisions about daily load and recovery management. In this context, future perspectives suggest the potential for AMSs to incorporate predictive analytics and artificial intelligence to further enhance decision-making processes in elite men’s basketball. Our findings underscore the need for continued innovation and rigorous validation of AMS technologies to ensure they meet the evolving demands of professional sports environments.
... Other studies aimed at developing monitoring guidelines lack a comprehensive survey of practices and needs across diverse sports [19]. ...
Article
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The objective of this study was to characterize surveyed coaches and elucidate the practices of physical fitness assessment and monitoring for both male and female athletes across three countries. A total of 165 coaches participated by completing a comprehensive 32-question survey. Pre-season assessments are a priority for coaches, with a significant range from 60.5% to 87.7% in Romania, while Portuguese and Spanish coaches tend to prefer testing during the competition (26.3% and 16.9%, respectively). Portuguese and Spanish coaches predominantly favor aerobic tests (50% and 46.8% respectively), whereas Romanian coaches exhibit a preference for sprint (56.9%) and skill tests (52.3%). Notably, change of direction tests are less commonly employed, ranging from 10.5% to 21% across the countries. In terms of exercise intensity determination, Portuguese coaches predominantly employ maximal heart rate (31.6%), while Spanish coaches often rely on the 220-age formula or perceived exertion (27.4%). For strength assessment, Portuguese coaches lean towards direct (34.2%) or estimated (31.6%) maximal repetition methods. When it comes to maximal speed sprint, Portuguese and Romanian coaches show preference (50% and 43.1% respectively), while Spanish coaches exhibit a relative lack of emphasis on individualized speed measures (37.1%). Perceptual scales are the preferred method for recovery monitoring, with adoption rates of 57.9% in Portugal, 53.2% in Spain, and 44.6% in Romania. In summary, this study underscores the distinct assessment and monitoring practices employed by coaches in Portugal, Spain, and Romania. These findings are in alignment with established literature standards, highlighting the diversity of approaches used in different countries.
... 8 Furthermore, the likelihood of injury is a determining factor in sports performance. A proper physical preparation and training planning can reduce its occurrence and even reduce the physical consequences of injuries, 9,10 making an adaptive, progressive and coherent training program essential. 6 The technical staff of a team (coaches and physical trainers) is in charge and responsible for the preparation of the players through the application of the training processes, 6 a determining process in the performance and improvement of the athletes, 1 which is why its evaluation and study has reached a great peak within the field of research. ...
Article
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Introduction In the quest to improve basketball players' performance during the season, the analysis of the training processes during the pre-season is crucial to successfully face the competition period. The aim of this research was to characterize the training tasks of a professional basketball team of the ACB category during the 2022/23 pre-season, as well as to analyze the relationship between the game situation with the pedagogical variables and External Load variables. Materials and Methods The sample consisted of 107 tasks during 20 sessions of a Spanish first division professional basketball team. The dependent variables were the pedagogical variables and the external load. The independent variable was the Game Situation, understood as the organization of the players during the tasks. All variables were recorded using the Integral System for the Analysis of Training Tasks (SIATE) tool. A descriptive and inferential analysis was carried out to determine the relationships between the game situation with the pedagogical and external load variables. Results All indicators of the pedagogical and external load variables show a statistically significant association with the game situation (p<.05). Conclusions Therefore, the pedagogical and external load variables are conditioned by the game situation. Positioning itself as a variable of great relevance for the planning of the sessions, as its design facilitates the achievement of the proposed objectives and more effective training sessions.
... External load measurement tools like electronic performance tracking systems (EPTS) [4] have become more prevalent in sports science [6]. Meanwhile, it is crucial to recognize that internal load determines the effectiveness of training [4,7]. Integrating training load monitoring methods is essential, as external and internal loads provide different information about the demands of training and competition [8]. ...
Article
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Background Limited research has investigated the association between training load and performance of basketball players during games. Little is known about how different indicators of player performance are affected by internal and external loads. The purpose of this study was to determine whether external and internal loads influence basketball players’ performance during games. Method This longitudinal study involved 20 professional male basketball players from a single team, classified as first-level athletes by the Chinese Basketball Association. During 34 games, external load was measured as PlayerLoad using micro-sensors, while internal load was assessed using session rating of perceived exertion (sRPE). Player performance was quantified using three metrics: Efficiency, Player Index Rating (PIR), and Plus-Minus (PM). Pearson correlation coefficients were calculated to assess the strength of the relationships between training loads and performance metrics. Linear mixed-effects models were applied to further analyze the influence of internal and external loads on basketball performance. Results Pearson correlation analysis revealed moderate positive correlations between both sRPE and PlayerLoad with Efficiency and PIR. Specifically, sRPE (r = 0.52) and PlayerLoad (r = 0.54) were both significantly correlated with Efficiency. For PIR, sRPE (r = 0.50) and PlayerLoad (r = 0.56) also demonstrated moderate correlations. These correlations were further substantiated by linear mixed-effects models, which showed that sRPE (β = 2.21, p < 0.001) and PlayerLoad (β = 1.87, p = 0.004) had significant independent effects on Efficiency. Similarly, sRPE (β = 2.15, p < 0.001) and PlayerLoad (β = 2.36, p < 0.001) significantly predicted PIR. Additionally, a significant interaction effect between PlayerLoad and sRPE was found on Plus-Minus (β = -2.49, p < 0.001), indicating that the combination of high physical and psychological loads negatively impacted overall team performance. However, the correlation strengths for Plus-Minus were relatively low (sRPE: r = 0.16; PlayerLoad: r = 0.10). Conclusion Both external and internal loads positively contribute to performance, the integration of objective (accelerometry) and subjective (sRPE) measures of load provides a comprehensive understanding of the physiological and psychological demands on athletes, contributing to more effective training regimens and performance optimization.
... Currently, managing exercise training load is central to sports science practice (West et al., 2021). This study provides new insights into optimizing training strategies for enhancing performance and recovery by comparing the effects of two training methods on blood lactate clearance. ...
Article
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This study compared the effects of High-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on blood lactate clearance. 21 adult males were equally and randomly assigned to the HIIT and MICT groups, and completed 8 weeks of training. Before the training intervention, after 4 weeks and 8 weeks of training, all subjects were tested for blood lactate levels between 0 and 55 min after the same high-intensity test. The results show that after 8 weeks, blood lactate levels were significantly lower than pre-tests in both the HIIT and MICT groups at “0–55 min” after high-intensity test (p < 0.05), and the blood lactate clearance percentage at15-min and 30-min in both groups were significantly higher than the pre-tests (P < 0.01). The blood lactate levels in the HIIT group were significantly lower than those in the MICT group at 15 min and 30 min after test (P < 0.05), and the blood lactate clearance percentage at 30 min in the HIIT group was significantly higher than those in the MICT group (P < 0.05). In conclusion, both HIIT and MICT enhance blood lactate clearance in adult males post high-intensity test, with HIIT demonstrating superior effectiveness, making it a viable alternative to MICT.
... The integration of these technologies promises to address long-term challenges in the fields of sports monitoring and healthcare. In the past, traditional sports monitoring approaches have struggled to meet their individualized demand; generalized training plans may reduce training effectiveness and increased injury risk [1]. Similarly, the healthcare sector faces significant challenges, including managing chronic diseases, the need for continuous patient monitoring, and the limitations of conventional diagnostics [2]. ...
Article
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The intersection of biomedical and bioengineering technologies with sports monitoring and healthcare has recently emerged as a key area of innovation and research [...]
... Accordingly, load monitoring plays a pivotal role in furnishing valuable information for the development of training programs and maximizing physical performance while preventing overreaching and reducing injury risk (7)(8)(9). Monitoring external and internal loads, both during training and competition, is acknowledged as being crucial for athlete management across different training and competition phases (10)(11)(12)(13)(14)(15). Moreover, it is also important to understand the extent to which players are exposed to game-like demands during practice sessions (16)(17)(18)(19)(20). ...
Article
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Introduction: Basketball, introduced by Naismith as a contactless and indoor alternative to sports such as American football, now frequently involves physical contact among players, challenging the traditional notion. Up to date, a thorough understanding of these contacts and their implications remains limited. This study aims to analyze player contacts, embedding it within overall load monitoring to optimize performance and reduce injury risk. Methods: Using a mixed-method design, video-based observations and quantitative analysis were employed to study contact characteristics during ten professional male basketball matches. Fisher exact tests and chi-squared tests (p < .05) were conducted to examine positional variations across different contact variables. Results: A total of 2,069 player contacts were examined, showing centers had the most contacts at 40.5%, followed by power forwards (19.6%), point guards (17.7%), shooting guards (12.9%), and small forwards (9.3%). Notably, half-court defense (46.1%) and set offense (48.9%) emerged as the primary game phases associated with the majority of contacts across all playing positions. Key play actions leading to physical contact included screening/picking (25.7%), box outs (22.9%), and fights for position (FFP) (18%). Post hoc analyses identified significant associations between centers (32.6%, 5.93) and point guards (21.5%, −1.98) during screening/picking maneuvers. Moreover, the torso/upper body (48.1%) and upper extremities (38.2%) were identified as the most affected contact points, while lower extremities and the head/neck exhibited minimal impact. Additionally, 81.4% (n = 1,684) of contacts resulted in kinematic displacement, whereas 18.6% (n = 385) exhibited no change. Post hoc analyses indicated significant associations of physical contacts against opposing counterparts for each playing position. Discussion: Basketball entails frequent physical contacts across all playing positions, with distinct patterns observed for each playing position. Integrating contact monitoring alongside traditional load metrics offers a more comprehensive understanding of physical demands in professional basketball. Practical implications include the developing of tailored training strategies based on playing position-specific contact profiles and recognizing the physiological and biomechanical impacts of contacts. Future research should consider whether the number of contacts between players has increased over the years, and it should acknowledge the impact of player contacts on performance in basketball in order to refine training strategies and enhance player well-being.
... Combining internal and external load measures provides valuable insights into how an athlete copes with tasks included in the training plan [12,13]. Effective management and monitoring of loads are essential to assess the athletes' adaptation to acute and chronic training outcomes and optimize performance [14,15]. Researchers have noted variations in the number of scientific studies on the monitoring of training loads across different sports disciplines [16], and the use of different tools depending on the type of sport highlights the need for further exploration to determine practical methods for evaluating training effects [17]. ...
Article
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In the long-term performance development of rhythmic gymnasts aged 16–17, athletes enter a high-performance training phase, marked by increased training loads and preparation for international competitions. This study aimed to (1) provide an overview of methods used to capture external and internal training/competition loads in elite rhythmic gymnasts, and (2) identify measurements of external and internal training/competition loads and their responses during monitored periods. Conducted according to PRISMA guidelines, the systematic review included 6 studies out of the 815 initially identified. The most common methods for calculating external training load were hours or minutes per week. Internal measures varied and included objective methods such as heart rate monitoring and biochemical, hormonal, and hematological assessments from saliva and blood samples. Among subjective methods, session-RPE was most frequently used, along with other questionnaires examining recovery, well-being, sleep, and competition anxiety. The analyzed studies integrated diverse external and internal training load variables, delving into their impact on athlete’s biochemical parameters, recovery, and well-being. Pre-competitive and competitive training periods were the focal points of measuring loads. The complex training structure of rhythmic gymnastics can complicate the calculation of training loads. Therefore, more studies are needed to explore the dose-response relationships between training load and training adaptations, fatigue, and recovery.
... Our results reveal a significant correlation between sRPE and PL across all game quarters, indicating a moderate relationship between these internal and external workload indicators in basketball. This result is linked with Espasa Labrador et al. (2021), suggesting that players' perceived exertion levels moderately align with the objective measures of physical workload (PL) throughout the game, offering a refined perspective on the workload experienced by players. Furthermore, Fox et al. (2020) provided complementary insights by examining the relationships between various workload indicators during basketball training and games in a semi-professional male context. ...
Article
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Purpose This study aims to explore the variations in external and internal loads on a quarter-by-quarter basis among professional Chinese basketball players. It emphasizes the crucial impact of these variations on optimizing athletic performance and match strategies. Method An observational longitudinal study design was employed, involving sixteen male players from the National Basketball League during the 2024 season in China. Data collection was facilitated through the use of Catapult S7 devices for measuring external loads and session ratings of perceived exertion (sRPE) for assessing internal loads. Linear mixed-effects models were utilized for the statistical analysis to identify differences in workload intensities across game quarters based on player positions. The Pearson correlation coefficient was used to examine the relationship between external and internal load throughout the game. Results The analysis uncovered significant positional differences in workload intensities across game quarters. Guards were found to have a higher PlayerLoad™ (PL) per minute in the first quarter, while centers demonstrated an increase in high-intensity accelerations and jumps in the fourth quarter. Furthermore, a significant moderate correlation between sRPE and PL was observed across all game quarters, indicating a link between physical exertion and athletes’ perceptions of effort. Conclusion The study offers new insights into the dynamic physical demands faced by basketball players and the importance of using both objective and subjective measures for a comprehensive assessment of athlete performance and wellbeing. The findings underscore the interconnectedness of physical exertion and athlete perception, providing a foundation for future research and practical applications in the field of basketball science.
... In the realm of sports, identifying risk factors for injuries through data analysis is an indispensable facet of athlete health management (Andrew et al., 2019;West et al., 2020). The application of sports analytics extends not only to assessing an athlete's prospective performance but also to their susceptibility to injuries. ...
Chapter
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This chapter focuses on the capacity of people analytics to transform talent spotting, player performance, injury prevention, and coaching methods in sports. The underpinnings of people analytics come from theory and real-world applications to point to means to improve athletic potential. The chapter emphasises how to optimise talent management and foster a culture of informed decision-making in sports organisations by analysing real-world case studies and looking at emerging trends.
... Sports tracking also facilitates evidence-based training, allowing athletes to make data-driven decisions about their training and training plans (Mencarini et al., 2019). Performance data analysis instantly facilitates observing correlations between specific training practices and their outcomes, enabling athletes to tailor their training plans more effectively (Halson, 2014;West et al., 2021;Feely et al., 2023). Besides, data-driven training personalization optimizes athletic performance and ensures that athletes remain motivated even when they face physical and mental challenges (Rapp and Tirabeni, 2020). ...
Article
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In this paper, we use self-determination theory and its related mini-theories to investigate the influence of sport data on sports experience and motivation in sports. First, we reflect on the use of technology in sports and show how sport data thwarts and promotes motivation in sports. Second, we argue that human-computer interaction (HCI) has been too narrowly focused on the 'performance' aspect of sport data. We argue for a more liberal take on sport data, showing that it also relates to motivation in sports through basic human needs. By bridging SportsHCI studies with the insights we gain from self-determination theory, we uncover the interwoven relations between the objective measures that sports technology provides and their motivational aspects for athletes. Our paper ends with five emerging points for attention for SportsHCI that we think can pave the way towards a more holistic approach to considering sport data for motivation in sports.
... Especially at the professional and academy level, players often selfreport health and wellness data daily or weekly. [62][63][64] At lower levels of play and in youth football, monitoring of hip and groin symptoms is equally important, as the groin injury rates and prevalence are expected to be high. 13 17 18 However, at lower levels of play, players and Open access coaches are often part-time employees and weekly or monthly registration of HAGOS is perceived to be too time-consuming. ...
Article
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Introduction Groin injuries represent a considerable problem in football. Although the Adductor Strengthening Programme reduced groin injury risk, players can still experience groin symptoms throughout the season. This study aimed to determine whether preseason Copenhagen Hip and Groin Outcome Score (HAGOS) and a history of previous injury can identify individuals at risk of having a longer duration of groin problems the subsequent season, using an ‘any physical complaint’ definition of injury. Methods Preseason HAGOS score and weekly groin problems were registered with the Oslo Sports Trauma Research Center Overuse questionnaire during one full season in 632 male semiprofessional adult players. Results The prognostic model showed a decreased number of weeks with groin problems for each increase in HAGOS score for ‘groin-related quality of life’ (QOL) (IRR=0.99, p=0.003). A 10-point higher ‘QOL’ score predicted 10% fewer weeks of groin problems. Additionally, previous hip/groin injury was associated with a 74% increase in the number of weeks with symptoms (p<0.001). Conclusion The HAGOS questionnaire applied preseason can detect players at risk of getting more weeks with groin problems the following season. The ‘QOL’ subscale seems to be the superior subscale for estimating subsequent groin problem duration. While HAGOS appears promising in identifying players at risk, previous groin injury is the most robust indicator, showing a substantial 74% increase in weeks with symptoms.
... Typically, practitioners (sport science and medicine personnel) use AMS with the aim of decreasing injury incidence and enhancing athletic performance and use the data gathered to support coaches' decision-making (Halson, 2014;Saw et al., 2015c). Recently, aspects of athlete monitoring, such as customised athlete self-report measures (ASRM) (Jeffries et al., 2020), its use as an injury predictor (West et al., 2021), and analysis methods, i.e., acute to chronic workload ratio have brought AMS under scrutiny. These issues have led to some researchers reporting that the evidence supporting the efficacy of monitoring systems is not high (Coyne et al., 2018;Heidari et al., 2018). ...
... The associations between internal and external measures of training load are important in understanding the training process and the validity of specific internal measures (Ferioli et al., 2021;McLaren et al., 2018). Therefore, by individually assessing the relationships between both loads (Impellizzeri et al., 2019;Soligard et al., 2016) it offers specific information on each player in relation to their performance and provides the coaches with a specific tool for load management and adaptation processes (West et al., 2021), recovery (Halson et al., 2014;Impellizzeri et al., 2019), and injury prevention in training (Gabbet, 2020). ...
Article
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The aim is to establish an specific, non-invasive, sub-maximum and applicable day-today protocol to assess the internal training load (IL) for basketball players using Heart Rate Variability (HRV) analysis before practice or competitions. Another aim is to propose a new IL index as a standardized parameter (%), to manage IL before practice sessions or competition. Twelve amateur male basketball players (age: 26.5 ± 8.8 years) completed HRV tests before a submaximal and intermittent drill (Activity Lay Up Wheel; ALUWIL 6min-test). Players performed a 5on5 scrimmage (MATCH) the following day during 10 min, completing rate of perceived exertion (RPE), total quality recovery (TQR) and wellness questionnaires, and continuous heart rate recordings. Players showed higher values of IL parameters based on heart rate (summatory heart rate zones, SHRZ; and training impulse, TRIMP), higher RPE values and lower recovery values during MATCH than ALUWIL (p<0.01). The parameter % of summatory of heart rate zones (SHRZ) showed stronger correlations than SHRZ and TRIMP during MATCH (p<0.001), and significant relations with RMSSD (square of the mean root of the adjacent R-R intervals) during the HRV test (p<0.05). During the ALUWIL test, %SHRZ shows higher and stronger correlations than SHRZ with RRmean (mean of the R-R intervals) (-.807) but similar than SHRZ with RMSSD. In this specific context, ALUWIL test could offer reliable and applied information as a standardized and integrated protocol to assess internal training load in basketball players using cardiac parameters before practice and games. The parameters RRMean, RMSSD and %SHRZ could be a specific indicator for IL management on basketball. However, more research is needed to validate these proposals in a complex context.
... This approach is widely referred to as "invisible monitoring." 10 One example was proposed by Lacome et al, 5 in which the authors adopted a linear regression (LR) approach to predict HR response during small-sided games from external load data. The difference between the actual HR and predicted HR was used as a fitness index (FI). ...
Article
Purpose: The study had 3 purposes: (1) to develop an index using machine-learning techniques to predict the fitness status of soccer players, (2) to explore the index’s validity and its relationship with a submaximal run test (SMFT), and (3) to analyze the impact of weekly training load on the index and SMFT outcomes. Methods: The study involved 50 players from an Italian professional soccer club. External and internal loads were collected during training sessions. Various machine-learning algorithms were assessed for their ability to predict heart-rate responses during the training drills based on external load data. The fitness index, calculated as the difference between actual and predicted heart rates, was correlated with SMFT outcomes. Results: Random forest regression (mean absolute error = 3.8 [0.05]) outperformed the other machine-learning algorithms (extreme gradient boosting and linear regression). Average speed, minutes from the start of the training session, and the work:rest ratio were identified as the most important features. The fitness index displayed a very large correlation ( r = .70) with SMFT outcomes, with the highest result observed during possession games and physical conditioning exercises. The study revealed that heart-rate responses from SMFT and the fitness index could diverge throughout the season, suggesting different aspects of fitness. Conclusions: This study introduces an “invisible monitoring” approach to assess soccer player fitness in the training environment. The developed fitness index, in conjunction with traditional fitness tests, provides a comprehensive understanding of player readiness. This research paves the way for practical applications in soccer, enabling personalized training adjustments and injury prevention.
... This aligned with previous evidence. 36 37 The information provided by monitoring tools supports decision-making and reinforces the value of communication and weighting all the data to provide an individualised approach. Our findings support that injury prevention requires a multidisciplinary team with multiple experts, flexible planning and tailored approaches. ...
Article
Objective To explore the beliefs and perceptions of professional female footballers and staff regarding injury prevention and performance protection in professional women’s football. Methods This qualitative study applied semistructured interviews with 18 participants from 3 top-tier teams from 2 countries (Portugal and England) and 4 nationalities, including 2 physiotherapists, 5 players, 3 team doctors, 2 head coaches, 3 strength and conditioning coaches, 2 managers, and 1 head of performance. Data analysis applied constant comparison analysis, using principles of grounded theory. There were no major differences in the perspectives of players and staff, and the findings are presented together. Results Identifying and reporting injuries and recognising potential injury risk factors were mentioned to influence the prevention of injury. Participants stated that the growth and evolution of women’s football could influence injury risk. Before reaching the professional level, exposure to potential risk factors, such as lack of recovery, limited awareness and opportunities for prevention (eg, preventive exercises and load management strategies), was believed to impact players’ injury risk. Players further described their experiences and the ‘bumpy road’ to becoming a professional player, their current context and potential future improvements for women’s football regarding injury prevention and performance protection. Conclusion Professional female football players face different injury risks during different moments of their careers. According to elite players and staff, amateur and semiprofessionals have limited resources and lack injury prevention strategies. Professional players and staff perceived the current preventive measures as good and relied on the value of individualised care and a multidisciplinary approach. In the future, more resources and structured injury prevention strategies are needed in youth and non-professional levels of women’s football to reduce injury risk and allow more players to reach their maximal performance.
... Therefore, it is important to closely monitor internal and external training loads, as well as players' neuromuscular status, to ensure the effectiveness of the applied training plan [1,[7][8][9][10]. The use of physical tests such as countermovement jump can provide a practical and easy way to monitor neuromuscular fatigue, which helps coaches to better tailor the training protocols [11,12]. ...
Article
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The study aimed to describe the neuromuscular status and training load in the U-21 soccer football from the Czech Republic during an international training camp. Sixteen players were sampled with data from the neuromuscular status by countermovement jump (CMJ), external load by global positioning system (GPS) parameters and internal load by session rate of perceived exertion (RPE). The camp consisted of 5 days of field training and 2 days of friendly matches. CMJ was performed on days 1, 4 and 7. The comparison of variables during the camp was tested by the Friedman test, one-way repeated measure ANOVA, effect size (ES) and percentage of change (p < 0.05). A significant improvement of 6% in jump performance was found from day 1 (49.7 ± 3.98 cm) to day 7 (52.8 ± 4.52 cm) (p < 0.001), with a moderate effect (ES = 0.7). Both internal and external loads presented significant variation during the camp, with higher RPE and GPS parameters on the day of the friendly matches = day 4 and day 7 and lower load on days 5 and 6 (p < 0.05). The study provides a report on a positive neuromuscular status in the Czech football players during an international camp including a congested and competitive fixture, presenting an undulation on training loads across the training sessions, with higher loads on the match days. This study demonstrated that the periodization used by the Czech national football team in this specific congested fixture seems to not impair the neuromuscular status.
... 과 스포츠영재성 발화 환경 (Yun & Jeon, 2013)의 상호작용으로 발현된다. 여기에 사회적 책임이나 도덕지능 (Yun, 2015)은 물론 ESG 반영 (Yun, 2022) (West et al., 2021). 경기력에 대한 사회적 관심의 방향은 지능관점의 전개 양상과 동일 (Yun, 2015) (Park & Yoo, 2013) (Tiedens & Linton, 2001), 예측이 어려운 정보가 누적되면 예측 가능성이 높 아지기도 한다 (Zhang et al., 2021). ...
Article
PURPOSE This study explored psychological experiences in long jump competitions and examined the continuity of psychological experiences over time.METHODS A total of 28 adult long jumpers, 18 men and 10 women, were provided data through in-depth interviews. Data on psychological experiences were extraced through inductive content analysis, while continuity by period was analyzed by calculating the response frequency ratio using Excel.RESULTS First, the psychological experience in the long jump competition was categorized as fundamental, competition intelligence, emotional control, and communication capacity experience. Second, in long jump competitions, results showed that jumpers experienced mixed feelings of anxiety and pressure, self-confidence, and concentration in the first period; peer communication and analysis thinking were necessary in the second period; practical intelligence and pressure control were important in the third period; learning ability and creativity were crucial in the fourth period; learning ability and coach communication were applied in the fifth period; and fighting spirit and creativity were present in the sixth period. Third, the psychological experience of long jumpers by period, basicphysical strength was maintained; competition intelligence increased in the second and fourth periods; communication skills increased until the fifth period, and decreased after; while emotional control decreased. This reflects the contextual changes over time andthe change in competition records owing to that.CONCLUSIONS In the long jump competition, psychological experience changes by period and affects competition records. This study will contribute to further understanding of psychological continuity.
... They have been used to evaluate the effectiveness of training programs, guide individualized training prescription, assess risk of injury, monitor recovery, and even provide real-time feedback to athletes and coaches [3]. Additionally, they are invaluable in rehabilitation settings, where they assist in assessing progress and readiness for return to play post-injury [11]. However, despite the wealth of information that these technologies provide, their integration into a holistic understanding of an athlete's performance and health is a complex task, necessitating further comprehensive exploration. ...
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Background The purpose of this scoping review was to evaluate the current use of technologies in sports settings for training adaptation and injury prevention. The review aimed to map the existing literature, identify key concepts and themes, and highlight gaps in research, thus offering guidance for future studies. Methods This study followed the guidelines of the PRISMA extension for scoping reviews and a search in four major databases was conducted. Results A total of 21 studies were included. The findings highlighted the widespread use of various technologies, including wearable devices and force plates, to monitor athletes’ performance and inform evidence-based decision-making in training and injury prevention. Variables such as Player Load, changes of direction, and acute chronic workload ratio were identified as key metrics in injury prediction. Conclusions This review uncovers a dynamic field of research in athlete injury prevention, emphasizing the extensive use of varied technologies. A key finding is the pivotal role of Player Load data, which offers nuanced insights for customizing training loads according to sport-specific demands, player positions, and the physical requirements of various activities. Additionally, the review sheds light on the utility of tools like force plates in assessing fatigue, aiding recovery, and steering injury rehabilitation, particularly in sports prone to knee and ankle injuries. These insights not only enhance our understanding of injury prevention but also provide a strategic direction for future research, aiming to boost athlete safety, performance, and career longevity.
... La monitorización es la medición sistemática y frecuente de variables consideradas clave para optimizar las adaptaciones del deportista al proceso de entrenamiento, procurando evaluar los diferentes parámetros de una forma rápida y poco invasiva aprovechando los recursos tecnológicos (Balsalobre y Rivilla, 2020). Recientemente, West et al. (2021) revisaron el concepto de monitorización en cinco niveles de uso aplicados al entrenamiento de fuerza: 1) ofrecer feedback (aumentando la motivación del deportista, mejorando la comunicación con éste y usándolo como herramienta educativa); 2) ajustar la sesión de entrenamiento (e.g., estimando la 1RM diaria); 3) planificar el entrenamiento en el día a día (optimizando la carga de entrenamiento para la próxima sesión o próximas sesiones de entrenamiento); 4) planificar la temporada (cuantificando la carga aguda y crónica de entrenamiento) y; 5) planificar el entrenamiento a largo plazo (obtener datos de referencia del deportista para el futuro). ...
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El objetivo del presente trabajo fue conocer qué prácticas emplean los entrenadores y los preparadores físicos de los deportes de equipo para el entrenamiento de fuerza. El entrenamiento de fuerza en estos deportes tiene como objetivos principales mejorar el rendimiento y prevenir lesiones. En el siguiente trabajo se llevó a cabo una revisión narrativa de los diferentes trabajos que han explorado las prácticas de fuerza en los deportes de equipo. Los datos muestran que, los preparadores físicos, emplean evaluaciones para medir la condición física, incluyendo la composición corporal, fuerza muscular y potencia. Asimismo, los métodos de evaluación incluyen pruebas de fuerza dinámica máxima, potencia máxima propulsiva, fuerza reactiva y valoraciones funcionales de movimiento. Además, los métodos de entrenamiento de fuerza incluyen resistencia variable, entrenamiento balístico, pliometría, entrenamiento complejo, levantamientos olímpicos, resistencia neumática y sobrecarga excéntrica. En relación con estos, las variables de la sesión de entrenamiento, como frecuencia, volumen, series y repeticiones, varían según la etapa de la temporada. De igual forma, se mencionan varios ejercicios fundamentales para miembros inferiores y superiores, así como métodos de monitorización y evaluación de fuerza excéntrica y perfiles de fuerza-velocidad-potencia. En resumen, la elaboración minuciosa de un plan de entrenamiento de fuerza que considere diversos aspectos, como métodos, ejercicios, frecuencia, series y variables monitorizadas, resulta fundamental para optimizar el rendimiento físico de los atletas. Sin embargo, se observan disparidades entre naciones y disciplinas deportivas en lo que respecta a las prácticas recomendadas, subrayando la importancia de una mayor difusión de conocimientos y evidencia científica. Palabras clave: revisión narrativa; preparación física; planificación del entrenamiento; deporte profesional. Abstract. The aim of this study was to determine the practices used by coaches and strength and conditioning professionals in team sports for strength training. The primary goals of strength training in these sports are to improve performance and prevent injuries. In the following work, a narrative review of the different works that have explored strength training practices in team sports was carried out. The findings reveal that strength and conditioning professionals employ assessments to measure physical fitness, including body composition, muscular strength, and power. Evaluation methods include maximal dynamic strength tests, maximal propulsive power, reactive strength, and functional movement assessments. Additionally, strength training methods encompass variable resistance, ballistic training, plyometrics, complex training, Olympic lifts, pneumatic resistance, and eccentric overload. Regarding training sessions, variables such as frequency, volume, sets, and repetitions vary according to the stage of the season. Furthermore, fundamental exercises for lower and upper limbs are mentioned, along with monitoring methods and assessment of eccentric strength and strength-velocity-power profiles. In conclusion, the careful development of a strength training plan, taking into account various aspects such as methods, exercises, frequency, sets and monitored variables, is crucial for optimising the physical performance of athletes. However, there are differences between countries and sports in terms of recommended practices. This highlights the need for greater dissemination of knowledge and scientific evidence. Keywords: narrative review; physical preparation; training planning; professional sport
... By using effective management principles, leaders or managers can optimize the performance and productivity of their organizations (Gammelsaeter, 2021 (Singer et al., 2019).By carrying out these functions effectively, management can help the organization achieve its stated goals and produce tangible effects, such as increased performance, personal satisfaction, and improved products and services. Management functions are divided into four stages, namely planning, organizing, implementing and controlling (West, 2021). ...
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Sports management in Indonesia is faced with a lack of adequate attention and investment in sports development. The budget allocated for sports development is still limited, including in terms of coaching athletes and improving sports facilities. This can make it difficult to achieve excellence in national competitions and develop the potential of high-achieving athletes. The Rock-Climbing Federation (FPTI) PENGCAB Jember district is experiencing quite serious problems in organizational management. This is evidenced by several elements of management that are not fulfilled, such as limited funds, multiple jobs in management, senior athletes changing residence, inadequate facilities and infrastructure. The aim of this research is to examine the management functions within FPTI PENGCAB Jember district as follows: Planning, Organizing, Mobilizing and Controlling. This research uses a qualitative approach with data collection methods in the form of observation, interviews and documentation. The research objects in this study are organizational administrators, coaches and athletes. The data analysis process uses data triangulation 1) data reduction, 2) data presentation, and 3) drawing conclusions. Research findings include: 1) Management planning (FPTI) meets the categorization criteria, namely clear who, what, when, where and how to do it; 2) Organization and management (FPTI) meets the categorization criteria, namely comprehensive management, work mechanisms, no written job descriptions, and routine activities discussed at the beginning of the year; 3) Driving, management (FPTI) meets the categorization criteria, namely complete management, work mechanisms, and there are routine activities. The research conclusions show that: (1) Planning: management of the Indonesian rock-climbing federation is very good; (2) Organization: the management of the Indonesian rock-climbing sports federation is quite good; and (3) Actuating: the management of the Indonesian rock-climbing sports federation is quite good. (4) Control: The Indonesian Rock-Climbing Sports Association is running quite well. Keywords: Sport Climbing, Sports management, Indonesian rock-climbing
... Therefore, evaluating TL from an individual perspective can identify periods when players potentially have an increased risk of injury, representing one piece of the injury prevention puzzle. 39 Practitioners may use these indicators in TL combined with their clinical experience and knowledge of physiology and basic training principles to decrease injury risk. ...
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Objectives Elite youth football players miss out on a large part of seasonal training due to injury. Limited research suggests an association between external and internal training load (TL) and injury incidence in elite youth football. This study analysed external and internal TL variables and their association with injury incidence in a group of male elite youth football players over four seasons. Methods Measures of external and internal TL and injury incidence of 56 male elite youth football players (age 17–19 years) were collected throughout four seasons. Heart rate, session rating of perceived exertion andGlobal Positioning System (GPS) variables were analysed. Individual players’ TL during the 30 days leading up to injury was compared with 30-day injury-free control periods. Change in TL through the periods was also analysed. Results Eighty-five injuries were included for analysis, showing that for most TL variables, the average levels were significantly lower during the period leading up to injury. Significant increases for the majority of TL variables were also found during the periods leading up to injury, while the control periods did not show any significant change. Conclusion A lower and/or increasing average TL volume over 30 days might increase the risk of injury in male elite youth football players. Avoiding long-term drops in TL and balance increases in TL might be beneficial to reduce injury risk.
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Context Athletes often face the dual challenge of high training loads with insufficient time to recover. Equally, in any team, sports medicine and performance staff are required to progress training loads in healthy athletes and avoid prolonged reductions in training load in injured athletes. In both cases, the implementation of a well-established psychological technique known as motor imagery (MI) can be used to counteract adverse training adaptations such as excessive fatigue, reduced capacity, diminished performance, and heightened injury susceptibility. Study Design Narrative overview. Level of Evidence Level 5. Results MI has been shown to enhance performance outcomes in a range of contexts including rehabilitation, skill acquisition, return-to-sport protocols, and strength and conditioning. Specific performance outcomes include reduction of strength loss and muscular atrophy, improved training engagement of injured and/or rehabilitating athletes, promotion of recovery, and development of sport-specific skills/game tactics. To achieve improvements in such outcomes, it is recommended that practitioners consider the following factors when implementing MI: individual skill level (ie, more time may be required for novices to obtain benefits), MI ability (ie, athletes with greater capacity to create vivid and controllable mental images of their performance will likely benefit more from MI training), and the perspective employed (ie, an internal perspective may be more beneficial for increasing neurophysiological activity whereas an external perspective may be better for practicing technique-focused movements). Conclusion We provide practical recommendations grounded in established frameworks on how MI can be used to reduce strength loss and fear of reinjury in athletes with acute injury, improve physical qualities in rehabilitating athletes, reduce physical loads in overtrained athletes, and to develop tactical and technical skills in healthy athletes.
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Spor Bilimleri Alanında Farklı Paradigmalar- I başlıklı bu kitap, spor bilimleri alanındaki akademik çalışmaların kapsamlı ve disiplinler arası bir koleksiyonunu temsil etmektedir. Bu kitap, spor bilimlerinin çeşitli konularını ele almaktadır. Kitap bölümlerimiz multidisipliner alanda çeşitli konulara ilişkin iç görüler sunan, alandaki uzmanlar tarafından titizlikle hazırlanmıştır. Dahil edilen çalışmalar literatüre değerli katkılar sunmayı ve spor bilimleri anlayışımızı ilerletmeyi amaçlamaktadır. Bu kitap aracılığıyla, alana özgü konulara değinmekle kalmayıp aynı zamanda spor bilimleri alanındaki ortaya çıkan zorlukları da ele alan zengin bir bilgi dokusu sunmayı amaçlıyoruz. Bu koleksiyon, spor bilimlerinin dinamik ve sürekli kendini yenileyen iklimini geliştirmeye hevesli akademisyenler, araştırmacılar, uygulayıcılar ve öğrenciler için tasarlanmıştır.
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Background Load management is a sports science concept describing the execution of well-established training principles to measure athletic workloads and enhance performance. The term ‘load management’ has become common in sports media to refer to a much wider range of scenarios, including the idea that by limiting regular season workload for athletes, their health and playoff performance will improve. Varying links between load and performance have been demonstrated in baseball and soccer. The purpose of this study was to objectively assess the impact of regular season workload on postseason performance among National Hockey League (NHL) goalies. Hypothesis NHL goalies with lighter regular season workloads will perform better in postseason appearances. Study Design Retrospective cohort. Level of Evidence Level 3. Methods NHL goalies with a minimum of 20 regular season games played and 3 playoff game appearances in the same season since 2013-2014 were eligible for inclusion. All regular season and postseason workload and performance metrics were collected from publicly available statistical databases. Workload outcomes included games started, minutes played, and shots faced. Performance outcomes included goals against average, save percentage, goals saved above average, and quality start percentage. Multivariable linear regression was used to determine whether regular season workload predicted postseason performance, when controlling for age and injury status. Results A total of 51 goalies contributed 111 goalie-seasons to the analysis. The results of the primary model indicated that regular season workload explained only 6.8% of the variance in postseason performance, and that this relationship was not significant ( R ² = 0.068; F(5,92) = 1.335; P = 0.26). Conclusion Based on data from 6 full seasons, there is no evidence to support a specific regular season game limit among NHL goalies with the aim of improved performance. Clinical Relevance Individualized workload plans may be more appropriate than a single league-wide standard.
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The increasing development of mankind can be seen in the progress in the design of sports facilities which must satisfy certain high standards of construction and equipment and which need to offer a maximum number of services in their environment in order to meet the needs of customers. One of the major positive influences on users includes opening diagnostic centers within sports objects which must be furnished properly and functionally. When furnishing and designing the interior, it is necessary to pay attention to the choice of colours, floor materials, lighting, and most importantly – the equipment that will be used in the premises of the center. They can be separated into zones: medical rooms, laboratory, and diagnostics and training area. Each of these zones has different requirements for equipment with special attention to the privacy of the patients being tested, their safety and keeping the space clean.
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In order to study the mechanisms of adaptation to loads requiring high endurance, the 27-year-old master of Sports of Russia in cross-country skiing repeatedly recorded a cardiointervalogram (CIG) under clinostasis conditions, estimating TP, absolute power (mc2) of LF-, HF- and VLF-waves and the relative (as a percentage of TP) power of these waves, i.e. LF%, HF% and VLF%. They were compared with the volume (Vkm, Vmin) and intensity (Nhr) of training loads. The volume of loads was maximum in the preparatory period (21 km/day) and it is minimal in the transition period (18 km/day), and their intensity throughout the annual cycle was stable (working pulse – 120–121 beats/min). With the change in the volume of loads, the values of the KIG indicators also changed. So, in the preparatory period, the medians of TP, the power of HF-, LF- and VLF-waves, as well as VLF% increase; in this period, with an increase in the volume of loads (Vkm), the values of VLF% increase. In the competitive period, the medians of TP, the power of HF-, LF- and VLF-waves and VLF% remain at a high level. In the transition period, the median of TP, the power HF-, LF- and VLF-waves, as well as LF% and VLF%, but the median of HF% increases. For the annual cycle, a direct dependence of the median of TP on the volume of loads (Vkm) and the median power of VLF waves on the volume (Vkm) and intensity (Nhr) of the load was revealed. It is postulated that the values of TP, HF-, LF-, and VLF-waves, as well as VLF% (in clinostasis) reflect the influence of the Cholinergic system on the heart, while VLF% probably reflects the intensity of synthesis of non-neuronal heart’s acetylcholine, and the values of LF% and HF% reflect the formation of anxiety in connection with upcoming starts.
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Introduction: Monitoring training loads is a powerful tool to achieve victory in team sports, represented by Thor's hammer metaphor. Objective: This scientific article discusses the importance of monitoring training loads in team sports for optimizing athletic performance and preventing injuries. Methods: The article presents a review of the literature on monitoring training loads in team sports, focusing on advancements in the field, including internal and external load monitoring, monitoring tools, and monitoring devices. Results: The review emphasizes the importance of implementing multifaceted athlete monitoring systems to ensure that the correct training dose is given at the right time, increase physical conditioning, and decrease fatigue. Conclusion: The article concludes that a scientific approach to load monitoring is essential for optimizing athletic performance and preventing injuries. Comprehensive monitoring should address mechanical, physiological, psychological, social, behavioral, and cognitive factors. Therefore, it is essential that coaches understand the importance of monitoring training loads and include it in their training programs, as a powerful weapon to increase performance in competitions.
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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 sourcesPubMed, EMBASE and grey literature databases; inception to May 2019.Eligibility criteriaLongitudinal 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.ResultsTwenty 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 numberCRD42017067585.
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This systematic review aimed to identify and summarise associations between currently identified contextual factors and match running in senior male professional rugby league. Eligible articles included at least one contextual factor and used GPS to measure at least one displacement variable within competitive senior, male, professional rugby league matches. Of the 15 included studies, the identified contextual factors were grouped into factors related to individual characteristics (n = 3), match result (n = 4), team strength (n = 2), opposition strength (n = 3), match conditions (n = 6), technical and tactical demands (n = 6), spatial and temporal characteristics (n = 7), and nutrition (n = 1). Speed was the most commonly reported measure of match running (100%), followed by distance (47%), and acceleration (20%). Inconsistencies were found between studies for most contextual factors on match running. Higher speeds were generally associated with higher fitness, encountered earlier in the match and whilst defending. All 15 studies utilised a univariate approach to quantify associations of a contextual factor. The inconsistencies found in the associations of given contextual factors highlight the complex and multi-faceted nature of match running. Therefore, practitioners should consider contextual factors when analysing and interpreting GPS data.
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Aim: The aim of this study is to assess the presence and implications of statistical artefacts created by a commonly used indicator of injury risk in both research and practice: the ratio between acute workload (AL) and chronic workload (CL), named ACWR. 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. Results: After reproducing the original analyses with only the ACWR showing effects compatible with higher injury risk (odd ratios, OR: 2.45, 95%CI 1.28 to 4.71), we demonstrated similar findings by dividing AL by the “contrived” fixed and randomly generated CLs: OR=1.95 (1.18 to 3.52) dividing by 1510 (average CL); and OR using random CL= 1.53 (mean), ranging from 1.16 to 2.07. Random ACWR calculated reducing the variance of the original AL 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 predictive advantage to an intercept-only model, even within the training sample (c-statistic = 0.426 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.
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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.
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Background There has been a recent increase in research examining training load as a method of mitigating injury risk due to its known detrimental effects on player welfare and team performance. The acute:chronic workload ratio (ACWR) takes into account the current training load (acute) and the training load that an athlete has been prepared for (chronic). The ACWR can be calculated using; (1) the rolling average model (RA) and (2) the exponentially weighted moving average model (EWMA). Objective The primary aim of this systematic review was to investigate the literature examining the association between the occurrence of injury and the ACWR and to investigate if sufficient evidence exists to determine the best method of application of the ACWR in team sports. Methods Studies were identified through a comprehensive search of the following databases: EMBASE, Medline, SPORTDiscus, SCOPUS, AMED and CINAHL. Extensive data extraction was performed. The methodological quality of the included studies was assessed according to the Newcastle–Ottawa Scale (NOS) for Cohort Studies. Results A total of 22 articles met the inclusion criteria. The assessment of article quality had an overall median NOS score of 8 (range 5–9). The findings of this review support the association between the ACWR and non-contact injuries and its use as a valuable tool for monitoring training load as part of a larger scale multifaceted monitoring system that includes other proven methods. There is support for both models, but the EWMA is the more suitable measure, in part due to its greater sensitivity. The most appropriate acute and chronic time periods, and training load variables, may be dependent on the specific sport and its structure. Conclusions For practitioners, it is the important to understand the intricacies of the ACWR before deciding the best method of calculation. Future research needs to focus on the more sensitive EWMA model, for both sexes, across a larger range of sports and time frames and also combinations with other injury risk factors.
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Background ‘How much change in training load is too much before injury is sustained, among different athletes?’ is a key question in sports medicine and sports science. To address this question the investigator/practitioner must analyse exposure variables that change over time, such as change in training load. Very few studies have included time-varying exposures (eg, training load) and time-varying effect-measure modifiers (eg, previous injury, biomechanics, sleep/stress) when studying sports injury aetiology. Aim To discuss advanced statistical methods suitable for the complex analysis of time-varying exposures such as changes in training load and injury-related outcomes. Content Time-varying exposures and time-varying effect-measure modifiers can be used in time-to-event models to investigate sport injury aetiology. We address four key-questions (i) Does time-to-event modelling allow change in training load to be included as a time-varying exposure for sport injury development? (ii) Why is time-to-event analysis superior to other analytical concepts when analysing training-load related data that changes status over time? (iii) How can researchers include change in training load in a time-to-event analysis? and, (iv) Are researchers able to include other time-varying variables into time-to-event analyses? We emphasise that cleaning datasets, setting up the data, performing analyses with time-varying variables and interpreting the results is time-consuming, and requires dedication. It may need you to ask for assistance from methodological peers as the analytical approaches presented this paper require specialist knowledge and well-honed statistical skills. Conclusion To increase knowledge about the association between changes in training load and injury, we encourage sports injury researchers to collaborate with statisticians and/or methodological epidemiologists to carefully consider applying time-to-event models to prospective sports injury data. This will ensure appropriate interpretation of time-to-event data.
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Background Since 2000, there has been a rapid growth in training load and injury research. In the past 5 years alone, a total of 38 studies (from as many as 24 different research groups, and 11 different sports) have investigated the relationship between loading profiles and injury. Despite the growing body of literature examining training load and injury, there is often a disconnect between this evidence and the actual training programmes prescribed in practice. In this paper, some common myths and misconceptions about training load and its role in injury and performance are reviewed. Myths and misconceptions Common myths relating to training load (the role of training load in injuries, the ‘10% rule’, the influence of spikes and troughs on injury risk and the acute:chronic workload ratio (ACWR)) are explored and discussed. Although the likelihood of injury is increased at an ACWR of ≥1.5 ( on average ), the difference between robust and fragile athletes can largely be explained by three key categories of moderators of the workload—injury relationship; ‘ideal’ age (ie, not too young or too old), physical qualities (eg, well-developed aerobic fitness, speed, repeated-sprint ability and lower body strength) and high chronic training load all decrease the risk associated with a given spike in workload. Rather than focusing solely on the ACWR as has been done in some studies, practitioners are advised to stratify players according to these three moderators of the workload—injury relationship (eg, age, training and injury history, physical qualities), and interpret internal and external load variables in combination with well-being and physical readiness data. When prescribing training load, the practitioner also needs to factor in injury risk factors such as poor biomechanics, academic and emotional stress, anxiety, inadequate sleep and stress-related personality traits. Summary Rapid increases in training and competition workloads and low chronic workloads are associated with greater injury risk. These findings suggest that appropriately staged training programmes may reduce injury risk in athletes. There is an urgent need for randomised controlled trials to test this working hypothesis.
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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.
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Time–motion analysis is a valuable data-collection technique used to quantify the physical match performance of elite soccer players. For over 40 years researchers have adopted a ‘traditional’ approach when evaluating match demands by simply reporting the distance covered or time spent along a motion continuum of walking through to sprinting. This methodology quantifies physical metrics in isolation without integrating other factors and this ultimately leads to a one-dimensional insight into match performance. Thus, this commentary proposes a novel ‘integrated’ approach that focuses on a sensitive physical metric such as high-intensity running but contextualizes this in relation to key tactical activities for each position and collectively for the team. In the example presented, the ‘integrated’ model clearly unveils the unique high-intensity profile that exists due to distinct tactical roles, rather than one-dimensional ‘blind’ distances produced by ‘traditional’ models. Intuitively this innovative concept may aid the coaches understanding of the physical performance in relation to the tactical roles and instructions given to the players. Additionally, it will enable practitioners to more effectively translate match metrics into training and testing protocols. This innovative model may well aid advances in other team sports that incorporate similar intermittent movements with tactical purpose. Evidence of the merits and application of this new concept are needed before the scientific community accepts this model as it may well add complexity to an area that conceivably needs simplicity.
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