The Validity and Reliability of Wearable Microtechnology for Intermittent Team Sports: A Systematic Review

Accuracy Standards of Wearable Technologies for Assessment of Soccer Kicking: Protocol for a Systematic Literature Review

BACKGROUND

Wearable technology is widely applied in performance monitoring, an integral part of sports and exercise sciences. The kick movement in soccer exemplifies a sports technique that could benefit from appropriate biomechanics assessment methodologies. However, the accuracy of wearables in quantifying soccer kick mechanics, particularly under field conditions, remains unclear.

OBJECTIVE

This study aims to present a protocol for a systematic review to discuss the measurement properties (validity, reliability, and/or accuracy aspects) of wearable technology systems explicitly used to measure ball-kicking features in soccer.

METHODS

This review protocol was preregistered in the Open Science Framework. A total of 2 authors will perform searches in major electronic databases using specific keyword combinations in PubMed, Physical Therapy and Sports Medicine, Web of Science, ProQuest, IEEE Xplore, EBSCOHost, and Scopus. Following a specific population, intervention, comparison, outcome framework (population: soccer players and/or collected human data in a football-related environment; intervention: at least 1 wearable used; comparator: criterion measures, repeated testing sessions and/or actual values; outcome: ball kicking data), studies will be screened based on predetermined inclusion and exclusion criteria. The methodological quality of the included studies will be assessed using the "consensus-based standards for the selection of health measurement instruments" checklist (in studies concerning validity or reliability) or the "quality assessment of diagnostic accuracy studies" tool (in studies concerning accuracy). Data extraction will be conducted to determine the level of evidence according to the "best evidence synthesis method," and an evidence gap map will be constructed. The Cohen κ coefficient will be used to estimate the interevaluator agreement.

RESULTS

This ongoing systematic review has completed database searches and is currently in the screening phase. Depending on the number and consistency of studies, results may be presented by meta-analysis or qualitative synthesis, with subgroup analyses considering factors such as gender, age, and playing level. The final results are expected by July 2024, with manuscript submission anticipated by November 2024.

CONCLUSIONS

Our study will provide a comprehensive summary of the highest level of evidence available on the use of wearables for the assessment of soccer kick mechanics, providing practical guidance for athletes and sports sciences professionals regarding the validity and reliability aspects of using wearable technology to measure ball-kicking features in soccer.

TRIAL REGISTRATION

OSF registries https://osf.io/zm3j6.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/57433.

Intensity Zones and Intensity Thresholds Used to Quantify External Load in Competitive Basketball: A Systematic Review

BACKGROUND

Despite widespread use of intensity zones to quantify external load variables in basketball research, the consistency in identifying zones and accompanying intensity thresholds using predominant monitoring approaches in training and games remains unclear.

OBJECTIVES

The purpose of this work was to examine the external load intensity zones and thresholds adopted across basketball studies using video-based time-motion analysis (TMA), microsensors, and local positioning systems (LPS).

METHODS

PubMed, MEDLINE, and SPORTDiscus databases were searched from inception until 31 January 2023 for studies using intensity zones to quantify external load during basketball training sessions or games. Studies were excluded if they examined players participating in recreational or wheelchair basketball, were reviews or meta-analyses, or utilized monitoring approaches other than video-based TMA, microsensors, or LPS.

RESULTS

Following screening, 86 studies were included. Video-based TMA studies consistently classified jogging, running, sprinting, and jumping as intensity zones, but demonstrated considerable variation in classifying low-intensity (standing and walking) and basketball-specific activities. Microsensor studies mostly utilized a single, and rather consistent, threshold to identify only high-intensity activities (> 3.5 m·s-2 for accelerations, decelerations, and changes-in-direction or > 40 cm for jumps), not separately quantifying lower intensity zones. Similarly, LPS studies predominantly quantified only high-intensity activities in a relatively consistent manner for speed (> 18.0 m·s-1) and acceleration/deceleration zones (> 2.0 m·s-2); however, the thresholds adopted for various intensity zones differed greatly to those used in TMA and microsensor research.

CONCLUSIONS

Notable inconsistencies were mostly evident for low-intensity activities, basketball-specific activities, and between the different monitoring approaches. Accordingly, we recommend further research to inform the development of consensus guidelines outlining suitable approaches when setting external load intensity zones and accompanying thresholds in research and practice.

From lab to field: validity and reliability of inertial measurement unit-derived gait parameters during a standardised run

The aim was to assess concurrent validity and test-retest reliability of spatiotemporal gait parameters from a thoracic-placed inertial measurement unit (IMU) in lab- (Phase One) and field-based (Phase Two) conditions. Spatiotemporal gait parameters were compared (target speeds 3, 5 and 7.5 m·s-1) between a 100 Hz IMU and an optical measurement system (OptoJump Next, 1000 hz) in 14 trained individuals (Phase One). Additionally, 29 English Premier League football players performed weekly 3 × 60 m runs (5 m·s-1; observations = 1227; Phase Two). Mixed effects modelling assessed the effect of speed on agreement between systems (Phase One) and test-retest reliability (Phase Two). IMU step time showed strong agreement (<0.3%) regardless of individual or running speed. Direction of mean biases up to 40 ms for contact and flight time depended on the running speed and individual. Step time, length and frequency were most reliable (coefficient of variation = 1.3-1.4%) but confounded by running speed. Step time, length and frequency derived from a thoracic-placed IMU can be used confidently. Contact time could be used if bias is corrected for each individual. To optimise test-retest reliability, a minimum running distance of 40 m is needed to ensure 10 constant-speed steps is gathered.

A Review of the Validity and Reliability of Accelerometer-Based Metrics From Upper Back-Mounted GNSS Player Tracking Systems for Athlete Training Load Monitoring

ABSTRACT

Dawson, L, Beato, M, Devereux, G, and McErlain-Naylor, SA. A review of the validity and reliability of accelerometer-based metrics from upper back-mounted GNSS player tracking systems for athlete training load monitoring. J Strength Cond Res 38(8): e459-e474, 2024-Athlete load monitoring using upper back-mounted global navigation satellite system (GNSS) player tracking is common within many team sports. However, accelerometer-based load monitoring may provide information that cannot be achieved with GNSS alone. This review focuses on the accelerometer-based metrics quantifying the accumulation of accelerations as an estimation of athlete training load, appraising the validity and reliability of accelerometer use in upper back-mounted GNSS player tracking systems, the accelerometer-based metrics, and their potential for application within athlete monitoring. Reliability of GNSS-housed accelerometers and accelerometer-based metrics are dependent on the equipment model, signal processing methods, and the activity being monitored. Furthermore, GNSS unit placement on the upper back may be suboptimal for accelerometer-based estimation of mechanical load. Because there are currently no feasible gold standard comparisons for field-based whole-body biomechanical load, the validity of accelerometer-based load metrics has largely been considered in relation to other measures of training load and exercise intensity. In terms of convergent validity, accelerometer-based metrics (e.g., PlayerLoad, Dynamic Stress Load, Body Load) have correlated, albeit with varying magnitudes and certainty, with measures of internal physiological load, exercise intensity, total distance, collisions and impacts, fatigue, and injury risk and incidence. Currently, comparisons of these metrics should not be made between athletes because of mass or technique differences or between manufacturers because of processing variations. Notable areas for further study include the associations between accelerometer-based metrics and other parts of biomechanical load-adaptation pathways of interest, such as internal biomechanical loads or methods of manipulating these metrics through effective training design.

The effects of rule changes in football-code team sports: a systematic review

Rule changes within football-code team sports aim to improve performance, enhance player welfare, increase competitiveness, and provide player development opportunities. This manuscript aimed to review research investigating the effects of rule changes in football-code team sports. A systematic search of electronic databases (PubMed, ScienceDirect, CINAHL, MEDLINE, and SPORTDiscus) was performed to August 2023; keywords related to rule changes, football-code team sports, and activity type. Studies were excluded if they failed to investigate a football-code team sport, did not quantify the change of rule, or were review articles. Forty-six studies met the eligibility criteria. Four different football codes were reported: Australian rules football (n = 4), rugby league (n = 6), rugby union (n = 16), soccer (n = 20). The most common category was physical performance and match-play characteristics (n = 22). Evidence appears at a high risk of bias partly due to the quasi-experimental nature of included studies, which are inherently non-randomised, but also due to the lack of control for confounding factors within most studies included. Rule changes can result in unintended consequences to performance (e.g., longer breaks in play) and effect player behaviour (i.e., reduce tackler height in rugby) but might not achieve desired outcome (i.e., unchanged concussion incidence). Coaches and governing bodies should regularly and systematically investigate the effects of rule changes to understand their influence on performance and injury risk. It is imperative that future studies analysing rule changes within football codes account for confounding factors by implementing suitable study designs and statistical analysis techniques.

Data Mining Paths for Standard Weekly Training Load in Sub-Elite Young Football Players: A Machine Learning Approach

The aim of this study was to test a machine learning (ML) model to predict high-intensity actions and body impacts during youth football training. Sixty under-15, -17, and -19 sub-elite Portuguese football players were monitored over a 6-week period. External training load data were collected from the target variables of accelerations (ACCs), decelerations (DECs), and dynamic stress load (DSL) using an 18 Hz global positioning system (GPS). Additionally, we monitored the perceived exertion and biological characteristics using total quality recovery (TQR), rating of perceived exertion (RPE), session RPE (sRPE), chronological age, maturation offset (MO), and age at peak height velocity (APHV). The ML model was computed by a feature selection process with a linear regression forecast and bootstrap method. The predictive analysis revealed that the players' MO demonstrated varying degrees of effectiveness in predicting their DEC and ACC across different ranges of IQR. After predictive analysis, the following performance values were observed: DEC (x¯predicted = 41, β = 3.24, intercept = 37.0), lower IQR (IQRpredicted = 36.6, β = 3.24, intercept = 37.0), and upper IQR (IQRpredicted = 46 decelerations, β = 3.24, intercept = 37.0). The player's MO also demonstrated the ability to predict their upper IQR (IQRpredicted = 51, β = 3.8, intercept = 40.62), lower IQR (IQRpredicted = 40, β = 3.8, intercept = 40.62), and ACC (x¯predicted = 46 accelerations, β = 3.8, intercept = 40.62). The ML model showed poor performance in predicting the players' ACC and DEC using MO (MSE = 2.47-4.76; RMSE = 1.57-2.18: R2 = -0.78-0.02). Maturational concerns are prevalent in football performance and should be regularly checked, as the current ML model treated MO as the sole variable for ACC, DEC, and DSL. Applying ML models to assess automated tracking data can be an effective strategy, particularly in the context of forecasting peak ACC, DEC, and bodily effects in sub-elite youth football training.

Wearable Sensors and the Evaluation of Physiological Performance in Elite Field Hockey Players

Sports performance tracking has gained a lot of interest and widespread use in recent years, especially in elite and sub-elite sports. This makes it possible to improve the effectiveness of training, to calibrate and balance workloads according to real energy expenditure, and to reduce the likelihood of injuries due to excessive physical stress. In this context, the aim of this review was to map the scientific literature on wearable devices used in field hockey, evaluating their characteristics and the available evidence on their validity in measuring physiological and movement parameters. A systematic investigation was carried out by employing five electronic databases and search terms that incorporated field hockey, wearables, and performance analysis. Two independent reviewers conducted assessments of the 3401 titles and abstracts for inclusion, and at the end of the screening process, 102 full texts were analyzed. Lastly, a total of 23 research articles that specifically concentrated on field hockey were incorporated. The selected papers dealt with performance monitoring (6 papers), technical analysis and strategy game (6), injury prevention (1), and physiological measurements (10). To appraise the quality of the evaluations, the Oxford quality scoring system scale was employed. The extraction of information was carried out through the utilization of the participants, intervention, comparison, and outcomes (PICOS) format. The analysis encompassed research studies that implemented wearable devices during training and competitive events. Among elite field hockey competitions, GPS units were identified as the predominant wearable, followed by heart rate monitors. The intraclass correlation coefficient (ICC) related to wearable devices showed reasonably high between-trial ICCs ranging from 0.77 to 0.99. The utilization of wearable devices in field hockey primarily centers around the measurement of player activity profiles and physiological demands. The presence of discrepancies in sampling rates and performance bands makes it arduous to draw comparisons between studies. Nevertheless, this analysis attested to the fact that wearable devices are being employed for diverse applications in the realm of field hockey.

Understanding the relationship between surfing performance and fin design

This research aimed to determine whether accomplished surfers could accurately perceive how changes to surfboard fin design affected their surfing performance. Four different surfboard fins, including conventional, single-grooved, and double-grooved fins, were developed using computer-aided design combined with additive manufacturing (3D printing). We systematically installed these 3D-printed fins into instrumented surfboards, which six accomplished surfers rode on waves in the ocean in a random order while blinded to the fin condition. We quantified the surfers' wave-riding performance during each surfing bout using a sport-specific tracking device embedded in each instrumented surfboard. After each fin condition, the surfers rated their perceptions of the Drive, Feel, Hold, Speed, Stiffness, and Turnability they experienced while performing turns using a visual analogue scale. Relationships between the surfer's perceptions of the fins and their surfing performance data collected from the tracking devices were then examined. The results revealed that participants preferred the single-grooved fins for Speed and Feel, followed by double-grooved fins, commercially available fins, and conventional fins without grooves. Crucially, the surfers' perceptions of their performance matched the objective data from the embedded sensors. Our findings demonstrate that accomplished surfers can perceive how changes to surfboard fins influence their surfing performance.

The validity of raw custom-processed global navigation satellite systems data during straight-line sprinting across multiple days

OBJECTIVES

(1) Determine the validity of instantaneous speed and acceleration and (2) the variation in validity over time (multiple sessions) for global navigation satellite systems (GNSS) devices.

DESIGN

Repeated measures.

METHODS

10-Hz GNSS devices from Statsports (n = 2, Apex Pro) and Catapult (n = 2, Vector S7) were examined, whilst a speed laser manufactured by MuscleLab (n = 1, LaserSpeed) was the criterion measure, sampling at 2.56 kHz, with data exported at 1000 Hz. Ten participants completed 40 m sprinting and changes of pace on three separate days. Root mean square error (RMSE) was used to assess the magnitude and direction of the difference between GNSS and criterion measures (instantaneous speed, instantaneous acceleration). Linear mixed models were built to assess the difference in validity across days.

RESULTS

RMSE ranged from 0.14 to 0.21 m·s-1 and 0.22 to 0.47 m·s-2 for speed and acceleration, respectively showing strong agreement. There were small variations in the agreement to criterion between days for both devices for speed (Catapult RMSE = 0.12 to 21 m·s-1; Statsports RMSE = 0.14 to 0.17 m·s-1) and for acceleration (Catapult RMSE = 0.26 to 0.47 m·s-2; Statsports RMSE = 0.22 to 0.43 m·s-2) across all movements. There was a negative linear relationship between speed and acceleration error as speed increased.

CONCLUSIONS

Wearable microtechnology devices from Catapult (Vector S7) and Statsports (Apex Pro) have suitable validity when measuring instantaneous speed and acceleration across multiple days. There may be small variations during different sessions and over the speed spectrum.

Validity and Reliability of Thoracic-Mounted Inertial Measurement Units to Derive Gait Characteristics During Running

ABSTRACT

Horsley, BJ, Tofari, PJ, Halson, SL, Kemp, JG, Chalkley, D, Cole, MH, Johnston, RD, and Cormack, SJ. Validity and reliability of thoracic-mounted inertial measurement units to derive gait characteristics during running. J Strength Cond Res 38(2): 274-282, 2024-Inertial measurement units (IMUs) attached to the tibia or lumbar spine can be used to analyze running gait but, with team-sports, are often contained in global navigation satellite system (GNSS) units worn on the thoracic spine. We assessed the validity and reliability of thoracic-mounted IMUs to derive gait characteristics, including peak vertical ground reaction force (vGRF peak ) and vertical stiffness (K vert ). Sixteen recreationally active subjects performed 40 m run throughs at 3-4, 5-6, and 7-8 m·s -1 . Inertial measurement units were attached to the tibia, lumbar, and thoracic spine, whereas 2 GNSS units were also worn on the thoracic spine. Initial contact (IC) from a validated algorithm was evaluated with F1 score and agreement (mean difference ± SD ) of gait data with the tibia and lumbar spine using nonparametric limits of agreement (LoA). Test-retest error {coefficient of variation, CV (95% confidence interval [CI])} established reliability. Thoracic IMUs detected a nearly perfect proportion (F1 ≥ 0.95) of IC events compared with tibia and lumbar sites. Step length had the strongest agreement (0 ± 0.04 m) at 3-4 m·s -1 , whereas contact time improved from 3 to 4 (-0.028 ± 0.018 second) to 7-8 m·s -1 (-0.004 ± 0.013 second). All values for K vert fell within the LoA at 7-8 m·s -1 . Test-retest error was ≤12.8% for all gait characteristics obtained from GNSS units, where K vert was most reliable at 3-4 m·s -1 (6.8% [5.2, 9.6]) and vGRF peak at 7-8 m·s -1 (3.7% [2.5, 5.2]). The thoracic-spine site is suitable to derive gait characteristics, including K vert , from IMUs within GNSS units, eliminating the need for additional sensors to analyze running gait.

A Systematic Review and Meta-Analysis of Wearable Satellite System Technology for Linear Sprint Profiling: Technological Innovations and Practical Applications

ABSTRACT

Cormier, P, Meylan, C, Agar-Newman, D, Geneau, D, Epp-Stobbe, A, Lenetsky, S, and Klimstra, M. A systematic review and meta-analysis of wearable satellite system technology for linear sprint profiling: technological innovations and practical applications. J Strength Cond Res 38(2): 405-418, 2024-An emerging and promising practice is the use of global navigation satellite system (GNSS) technology to profile team-sports athletes in training and competition. Therefore, the purpose of this narrative systematic review with meta-analysis was to evaluate the literature regarding satellite system sensor usage for sprint modeling and to consolidate the findings to evaluate its validity and reliability. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, an electronic search of the databases, PubMed and SPORTDiscus (EBSCO), was conducted. Concurrent validity and reliability studies were considered, and 16 studies were retained for the review from the initial 1,485 studies identified. The effects on outcomes were expressed as standardized mean differences (SMDs, Cohen's d ) for each outcome (i.e., maximal sprint speed [MSS], the acceleration constant [τ], maximal theoretical velocity [ V0 ], relative force [ F0 ], and relative power [P max ]). Effect magnitudes represented the SMD between GNSS-derived and criterion-derived (i.e., radar and laser) and resulted in the following estimates: small for MSS ( d = 0.22, 95% CI 0.01 to 0.42), τ ( d = -0.18, 95% CI -0.60 to 0.23), V0 ( d = 0.14, 95% CI -0.08 to 0.36), relative F0 ( d = 0.15, 95% CI -0.25 to 0.55), and relative P max ( d = 0.21, 95% CI -0.16 to 0.58). No publication bias was identified in meta-analyzed studies and moderator analysis revealed that several factors (sampling rate and sensor manufacturer) influenced the results. Heterogeneity between studies was considered moderate to high. This highlighted the differences between studies in sensor technology differences (i.e., sampling rate, sensor fusion, and satellite network acquisition), processing techniques, criterion technology used, sprint protocols, outcome reporting, and athlete characteristics. These findings may be useful in guiding improvements in sprint modeling using GNSS technology and enable more direct comparisons in future research. Implementation of all-out linear sprint efforts with GNSS technology can be integrated into sport-specific sessions for sprint modeling when robust and consistent data processing protocols are performed, which has important implications for fatigue monitoring, program design, systematic testing, and rehabilitation in individual and team sports.

Match-play movement demands of international and domestic women's rugby sevens players in an elite dual-level tournament

OBJECTIVES

To characterize and compare match-play movement demands via Global Positioning Systems (GPS) between international and domestic women's rugby sevens players performing in a novel elite dual-level tournament, with consideration to position and tournament characteristics.

DESIGN

Fifty-four rugby sevens players; twenty-one international(5 speed edges, 8 backs, 8 forwards), and thirty-three domestic(10 speed edges, 11 backs, 12 forwards) wore GPS devices during an elite dual-level tournament covering 2 seasons, with 367 full match-play data files analysed. Internationaland domestic players were distributed evenly between competing teams.

METHODS

Match-play movement demands were characterized by distance, speed, and acceleration-based indices from 5 to 10 Hz GPS devices.

RESULTS

International players recorded significantly higher high-intensity match-play movement demands compared to domestic players in distance in high and very high-speed zones (P = 0.01, P = 0.03, P = 0.01, P = 0.03), maximal acceleration (P = 0.001), maximal velocity (P < .001), speed exertion (P = 0.01),       , and acceleration load density (P = 0.03)   . Positional analysis demonstrated forwards displayed the largest significant differences between international and domestic players. . Total and relative match-play movement demands of the dual-leveltournament also showed comparable demands to previous international tournament research .

CONCLUSIONS

Results identify key points of difference in match-play movement demands between player levels in women's rugby sevens, and provides important information on the characteristics of playing positions, and of a dual-level tournament of this nature. This will improve the design and implementation of structures from domestic to international level.

Technology Innovation and Guardrails in Elite Sport: The Future is Now

A growing number of companies are developing or using wearable sensor technologies that can monitor, analyse and transmit data from humans in real time that can be used by the sporting, biomedical and media industries. To explore this phenomenon, we describe and review two high-profile sporting events where innovations in wearable technologies were trialled: the Tokyo 2020 Summer Olympic Games (Tokyo 2020, Japan) and the 2022 adidas Road to Records (Germany). These two major sporting events were the first time academic and industry partners came together to implement real-time wearable solutions during major competition, to protect the health of athletes competing in hot and humid environments, as well as to better understand how these metrics can be used moving forwards. Despite the undoubted benefits of such wearables, there are well-founded concerns regarding their use including: (1) limited evidence quantifying the potential beneficial effects of analysing specific parameters, (2) the quality of hardware and provided data, (3) information overload, (4) data security and (5) exaggerated marketing claims. Employment and sporting rules and regulations also need to evolve to facilitate the use of wearable devices. There is also the potential to obtain real-time data that will oblige medical personnel to make crucial decisions around whether their athletes should continue competing or withdraw for health reasons. To protect athletes, the urgent need is to overcome these ethical/data protection concerns and develop wearable technologies that are backed by quality science. The fields of sport and exercise science and medicine provide an excellent platform to understand the impact of wearable sensors on performance, wellness, health, and disease.

Effects of Bed Rest on Physical Performance in Athletes: A Systematic and Narrative Review

BACKGROUND

Athletes can face scenarios in which they are confined to bed rest (e.g., due to injury or illness). Existing research in otherwise healthy individuals indicates that those entering bed rest with the greatest physical performance level might experience the greatest performance decrements, which indirectly suggests that athletes might be more susceptible to the detrimental consequences of bed rest than general populations. Therefore, a comprehensive understanding of the effects of bed rest might help guide the medical care of athletes during and following bed rest.

OBJECTIVE

This systematic and narrative review aimed to (1) establish the evidence for the effects of bed rest on physical performance in athletes; (2) discuss potential countermeasures to offset these negative consequences; and (3) identify the time-course of recovery following bed rest to guide return-to-sport rehabilitation.

METHODS

This review was performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Four databases were searched (SPORTDiscus, Web of Science, Scopus, and MEDLINE/PubMed) in October of 2022, and studies were included if they were peer-reviewed investigations, written in English, and investigated the effects of horizontal bed rest on changes in physical capacities and qualities in athletes (defined as Tier 3-5 participants). The reporting quality of the research was assessed using a modified version of the Downs & Black checklist. Furthermore, findings from studies that involved participants in Tiers 1-2 were presented and synthesized using a narrative approach.

RESULTS

Our systematic review of the literature using a rigorous criterion of 'athletes' revealed zero scientific publications. Nevertheless, as a by-product of our search, seven studies were identified that involved apparently healthy individuals who performed specific exercise training prior to bed rest.

CONCLUSIONS

Based on the limited evidence from studies involving non-athletes who were otherwise healthy prior to bed rest, we generally conclude that (1) bed rest rapidly (within 3 days) decreases upright endurance exercise performance, likely due to a rapid loss in plasma volume; whereas strength is reduced within 5 days, likely due to neural factors as well as muscle atrophy; (2) fluid/salt supplementation may be an effective countermeasure to protect against decrements in endurance performance during bed rest; while a broader array of potentially effective countermeasures exists, the efficacy of these countermeasures for previously exercise-trained individuals requires further study; and (3) athletes likely require at least 2-4 weeks of progressive rehabilitation following bed rest of ≤ 28 days, although the timeline of recovery might need to be extended depending on the underlying reason for bed rest (e.g., injury or illness). Despite these general conclusions from studies involving non-athletes, our primary conclusion is that substantial effort and research is still required to quantify the effects of bed rest on physical performance, identify effective countermeasures, and provide return-to-sport timelines in bona fide athletes.

TRIAL REGISTRATION NUMBER AND DATE OF REGISTRATION

Registration ID: osf.io/d3aew; Date: October 24, 2022.

The Effect of Feedback on Resistance Training Performance and Adaptations: A Systematic Review and Meta-analysis

BACKGROUND

Augmented feedback is often used during resistance training to enhance acute physical performance and has shown promise as a method of improving chronic physical adaptation. However, there are inconsistencies in the scientific literature regarding the magnitude of the acute and chronic responses to feedback and the optimal method with which it is provided.

OBJECTIVE

This systematic review and meta-analysis aimed to (1) establish the evidence for the effects of feedback on acute resistance training performance and chronic training adaptations; (2) quantify the effects of feedback on acute kinematic outcomes and changes in physical adaptations; and (3) assess the effects of moderating factors on the influence of feedback during resistance training.

METHODS

Twenty studies were included in this systematic review and meta-analysis. This review was performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Four databases were searched, and studies were included if they were peer-reviewed investigations, written in English, and involved the provision of feedback during or following dynamic resistance exercise. Furthermore, studies must have evaluated either acute training performance or chronic physical adaptations. Risk of bias was assessed using a modified Downs and Black assessment tool. Multilevel meta-analyses were performed to quantify the effects of feedback on acute and chronic training outcomes.

RESULTS

Feedback enhanced acute kinetic and kinematic outputs, muscular endurance, motivation, competitiveness, and perceived effort, while greater improvements in speed, strength, jump performance, and technical competency were reported when feedback was provided chronically. Furthermore, greater frequencies of feedback (e.g., following every repetition) were found to be most beneficial for enhancing acute performance. Results demonstrated that feedback improves acute barbell velocities by approximately 8.4% (g = 0.63, 95% confidence interval [CI] 0.36-0.90). Moderator analysis revealed that both verbal (g = 0.47, 95% CI 0.22-0.71) and visual feedback (g = 1.11, 95% CI 0.61-1.61) were superior to no feedback, but visual feedback was superior to verbal feedback. For chronic outcomes, jump performance might have been positively influenced (g = 0.39, 95% CI - 0.20 to 0.99) and short sprint performance was likely enhanced (g = 0.47, 95% CI 0.10-0.84) to a greater extent when feedback is provided throughout a training cycle.

CONCLUSIONS

Feedback during resistance training can lead to enhanced acute performance within a training session and greater chronic adaptations. Studies included in our analysis demonstrated a positive influence of feedback, with all outcomes showing superior results than when no feedback is provided. For practitioners, it is recommended that high-frequency, visual feedback is consistently provided to individuals when they complete resistance training, and this may be particularly useful during periods of low motivation or when greater competitiveness is beneficial. Alternatively, researchers must be aware of the ergogenic effects of feedback on acute and chronic responses and ensure that feedback is standardised when investigating resistance training.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Concurrent validity and between-unit reliability of a foot-mounted inertial measurement unit to measure velocity during team sport activity

The concurrent validity and between-unit reliability of a foot-mounted inertial measurement unit (F-IMU) was investigated during linear and change of direction running drills. Sixteen individuals performed four repetitions of two drills (maximal acceleration and flying 10 m sprint) and five repetitions of a multi-directional movement protocol. Participants wore two F-IMUs (Playermaker) and 10 retro-reflective markers to allow for comparisons to the criterion system (Qualisys). Validity of the F-IMU derived velocity was assessed via root-mean-square error (RMSE), 95% limits of agreement (LoA) and mean difference with 95% confidence interval (CI). Between-unit reliability was assessed via intraclass correlation (ICC) with 90% CI and 95% LoA. The mean difference for instantaneous velocity for all participants and drills combined was -0.048 ± 0.581 m ∙ s^-1, the LoA were from -1.09 to -1.186 m ∙ s^-1 and RMSE was 0.583 m ∙ s^-1. The ICC ranged from 0.84 to 1, with LoA from -7.412 to 2.924 m ∙ s^-1. Differences were dependent on the reference speed, with the greatest absolute difference (-0.66 m ∙ s^-1) found at velocities above 7 m ∙ s^-1. Between-unit reliability of the F-IMU ranges from good to excellent for all locomotor characteristics. Playermaker has good agreement with 3D motion capture for velocity and good to excellent between-unit reliability.

External Load Monitoring in Female Basketball: A Systematic Review

The primary aim of this systematic review was to summarize the current state of research in relation to external load monitoring in female basketball. The review was conducted according to the PRISMA-P® statement. Publications included in the review: 1) were original research, 2) evaluated healthy female basketball players, and 3) monitored basketball practice and competition. The STROBE scale was used to assess quality. A total of 40 publications were included. The external load was assessed during practice (n = 9), competition (n = 11) or both events (n = 8). Also, time-motion analysis was implemented in practice (n = 2), competition (n = 9), or both events (n = 1). Accelerometry (n = 28) and time-motion (n = 12) analysis were the most frequently used methods. However, a wide range in methods and variables were used to quantify the external load. Placement of devices on the upper back and measuring with a sampling frequency of 100 Hz were most common. Player Load (PL) values increased with the competitive level of players and were higher in competition compared to training. Small-sided games can be used to gradually increase loads in female basketball (PL 5v5: 34.8 ± 8, PL 3v3: 47.6 ± 7.4, TD 5v5: 209.2 ± 35.8 m, and TD 3v3: 249.3 ± 2.8 m). Tasks without defense seemed to be less demanding. More research is needed to reach a consensus on load control in women's basketball, on what data are important to collect, and how to use and transfer knowledge to stakeholders.

The Criterion Validity and Between-Day Reliability of the Perch for Measuring Barbell Velocity During Commonly Used Resistance Training Exercises

ABSTRACT

Weakley, J, Munteanu, G, Cowley, N, Johnston, R, Morrison, M, Gardiner, C, Pérez-Castilla, A, and García-Ramos, A. The criterion validity and between-day reliability of the Perch for measuring barbell velocity during commonly used resistance training exercises. J Strength Cond Res 37(4): 787-792, 2023-This study aimed to assess the criterion validity and between-day reliability (accounting for technological and biological variability) of mean and peak concentric velocity from the Perch measurement system. On 2 testing occasions, 16 subjects completed repetitions at 20, 40, 60, 80, 90, and 100% of 1-repetition maximum in the free-weight barbell back squat and bench press. To assess criterion validity, values from the Perch and a 3-dimensional motion capture system (criterion) were compared. Technological variability was assessed by determining whether the differences between the Perch and criterion for each load were comparable for both testing sessions, whereas between-day reliability with both technological and biological variability was calculated from Perch values across days. Generalized estimating equations were used to calculate R2 and root mean square error, whereas Bland-Altman plots assessed magnitude of difference between measures. To support monitoring of athletes over time, standard error of measurement and minimum detectable changes (MDC) were calculated. There was excellent agreement between the Perch and criterion device, with mean velocity in both exercises demonstrating a mean bias ranging from -0.01 to 0.01 m·s -1 . For peak velocity, Perch underestimated velocity compared with the criterion ranging from -0.08 to -0.12 m·s -1 for the back squat and -0.01 to -0.02 m·s -1 for the bench press. Technological variability between-days were all less than the MDC. These findings demonstrate that the Perch provides valid and reliable mean and peak concentric velocity outputs across a range of velocities. Therefore, practitioners can confidently implement this device for the monitoring and prescription of resistance training.

Reliability and validity of an indoor local positioning system for measuring external load in ice hockey players

This study determined the reliability and validity of a Kinexon local positioning system (LPS) for measuring external load in ice hockey players during an on-ice session. Fourteen ice hockey players (25.1 y, 78.6 kg, 176.9 cm) wore two LPS sensors to examine the inter-sensor reliability of the LPS during an on-ice session, and LPS speed and acceleration were measured during 40 m linear on-ice sprints and compared to a previously validated robotic sprint device to examine LPS accuracy. The coefficient of variation (CV), standard error of measurement (SEM), and intra-class correlation coefficient (ICC) were calculated for each LPS measure. Pearson's correlations, simple linear regressions, and Bland-Altman plots were used to test the agreement and relationship between the two systems. Statistical significance was determined at p < 0.05. The majority of LPS measures were reliable (CV < 10% and ICC > 0.9) when comparing the two sensors worn by each player. Peak speed, speed at 5 m, and 0-5 m acceleration were all comparable to those reported by the robotic sprint device, with nearly perfect (peak speed and 0-5 m acceleration) and very large (speed at 5 m) magnitudes of correlation and mean biases <0.5 km/hr for speed measures and <0.01 m/s² for acceleration. The present results demonstrate that the Kinexon LPS is reliable and accurate for investigating on-ice external load in ice hockey players when sensors are consistently secured on the back of the players' shoulder pads.

Differentiating Stroke and Movement Accelerometer Profiles to Improve Prescription of Tennis Training Drills

ABSTRACT

Perri, T, Reid, M, Murphy, A, Howle, K, and Duffield, R. Differentiating stroke and movement accelerometer profiles to improve prescription of tennis training drills. J Strength Cond Res 37(3): 646-651, 2023-This study compared the movement- and stroke-related accelerometer profiles and stroke counts between common on-court tennis training drills. Ten, junior-elite, male tennis players wore a cervical-mounted global positioning systems, with in-built accelerometer, gyroscope, and magnetometer during hard court training sessions ( n = 189). Individual training drills were classified into 8 categories based on previous research descriptions. Manufacturer software calculated total player load (tPL), while a prototype algorithm detected forehand (FH), backhands (BH), and serves and then calculated a stroke player load (sPL) from individual strokes. Movement player load (mPL) was calculated as the difference between tPL and sPL. Drill categories were compared for relative ( . min -1 ) tPL, sPL, mPL, and stroke counts via a 1-way analysis of variance with effect sizes (Cohen's d ) and 95% confidence intervals. Highest tPL . min -1 existed in accuracy and recovery or defensive drills ( p < 0.05), with lowest tPL·min -1 values observed in match-play simulation ( p < 0.05). For sPL·min -1 , accuracy drills elicited greater values compared with all other drill types ( p < 0.05), partly via greater FH-sPL·min -1 ( p < 0.05), with lowest sPL·min -1 existing for match-play ( p < 0.05). Accuracy, open, and recovery or defensive drills result in greater BH-sPL·min -1 and BH . min -1 ( p < 0.05). Serve-sPL·min -1 is highest in technical and match-play drills ( p < 0.05). Higher mPL·min -1 existed in accuracy, recovery or defensive, 2v1 net, open, and 2v1 baseline ( p < 0.05). Furthermore, mPL·min -1 in points drills was greater than technical and match-play simulation drills ( p < 0.05). Higher hitting-based accelerometer loads (sPL·min -1 ) exist in accuracy drills, whereas technical and match-play drills show the lowest movement demands (mPL·min -1 ). These findings can aid individual drill prescription for targeting movement or hitting load.

Effect of Traditional, Rest Redistribution, and Velocity-Based Prescription on Repeated Sprint Training Performance and Responses in Semiprofessional Athletes

ABSTRACT

Weakley, J, Castilla, AP, Ramos, AG, Banyard, H, Thurlow, F, Edwards, T, Morrison, M, McMahon, E, and Owen, C. The effect of traditional, rest redistribution, and velocity-based prescription on repeated sprint training performance and responses in semi-professional athletes. J Strength Cond Res XX(X): 000-000, 2022-The aim of this study was to investigate the effects of traditional, rest redistribution, and velocity-based repeated sprint training methods on repeated sprint performance, perceived effort, heart rate, and changes in force-velocity-power (FVP) profiles in male semiprofessional athletes. In a randomized crossover design, a traditional (2 sets of 6 repetitions [TRAD]), 2 different rest redistribution (4 sets of 3 repetitions [RR4] and 12 sets of 1 repetition [RR12]), and a 5% velocity loss (VL5%) (12 repetitions, with sets terminated when a 5% reduction in mean velocity had occurred) condition were completed. Mean and peak velocity, mean heart rate, and differential ratings of perceived exertion (dRPE) were measured throughout each session, while horizontal FVP profiles were assessed presession and postsession. The RR4 and RR12 conditions allowed the greatest maintenance of velocity, while the RR4, RR12, and VL5% had a moderate, significantly greater mean heart rate than the traditional condition. Trivial, nonsignificant differences between all conditions were observed in dRPE of the legs and breathlessness and FVP profiles. These findings indicate that rest redistribution can allow for greater maintenance of sprint velocity and heart rate, without altering perceived effort during repeated sprint training. In addition, velocity-loss thresholds may be a feasible method of prescription if athletes have diverse physical qualities and reductions in sprint performance during repeated sprint training are undesirable. Practitioners should consider these outcomes when designing repeated sprint training sessions because the strategic use of these methods can alter sprint performance and internal load without changing perceptions of intensity.

The Validity, Reliability, and Agreement of Global Positioning System Units-Can We Compare Research and Applied Data?

ABSTRACT

Brosnan, RJ, Watson, G, Stuart, W, Twentyman, C, Kitic, CM, and Schmidt, M. The validity, reliability, and agreement of GPS units-Can we compare research and applied data? J Strength Cond Res 36(12): 3330-3338, 2022-This study's aim was to investigate the validity, within-brand interunit reliability, and between-brand agreement of movement indicators from 3 commonly used global positioning system (GPS) units used in applied and research settings. Forty-two units (GPSports EVO; 10 Hz, n = 13: GPSports HPU; 5 Hz, n = 14: and Catapult S5; 10 Hz, n = 15) were investigated across 3 experiments: a 40-m linear track with all units pushed on a trolley, a sport simulation circuit with all units pulled on a sled, and a similar circuit with 3 models of units placed in a modified GPS vest worn by an athlete between the scapulae. Distance, speed, and acceleration indices were obtained and analyzed with the level of significance set ( ρ < 0.05). The results demonstrated good to moderate (% mean difference; 0-6.5%) validity with criterion and good (coefficient of variation [CV] ± 90% confidence interval [CI]: 0-3.9%) interunit reliability for distance and speed in units. Ten hertz units demonstrated good to moderate (CV ± 90% CI: 0.21-5.58%) interunit reliability in all acceleration and deceleration measures, with 5 Hz units having good to poor (CV ± 90% CI: 4.54-12.78%) results. Agreement ranged from good to moderate (% mean difference; 0.01-7.8%) for distance, speed, and absolute acceleration/deceleration. Agreement ranged from good to poor (% mean difference; 2.21-32.74%) in average acceleration. The GPS units investigated can be compared within and between applied and research settings for distance and speed. However, caution is warranted in acceleration indices. This highlights the importance of testing other commonly used GPS models and brands.

Prototype Machine Learning Algorithms from Wearable Technology to Detect Tennis Stroke and Movement Actions

This study evaluated the accuracy of tennis-specific stroke and movement event detection algorithms from a cervically mounted wearable sensor containing a triaxial accelerometer, gyroscope and magnetometer. Stroke and movement data from up to eight high-performance tennis players were captured in match-play and movement drills. Prototype algorithms classified stroke (i.e., forehand, backhand, serve) and movement (i.e., "Alert", "Dynamic", "Running", "Low Intensity") events. Manual coding evaluated stroke actions in three classes (i.e., forehand, backhand and serve), with additional descriptors of spin (e.g., slice). Movement data was classified according to the specific locomotion performed (e.g., lateral shuffling). The algorithm output for strokes were analysed against manual coding via absolute (n) and relative (%) error rates. Coded movements were grouped according to their frequency within the algorithm's four movement classifications. Highest stroke accuracy was evident for serves (98%), followed by groundstrokes (94%). Backhand slice events showed 74% accuracy, while volleys remained mostly undetected (41-44%). Tennis-specific footwork patterns were predominantly grouped as "Dynamic" (63% of total events), alongside successful linear "Running" classifications (74% of running events). Concurrent stroke and movement data from wearable sensors allows detailed and long-term monitoring of tennis training for coaches and players. Improvements in movement classification sensitivity using tennis-specific language appear warranted.

The Maximal Intensity Period: Rationalising its Use in Team Sports Practice

Quantifying the highest intensity of competition (the maximal intensity period [MIP]) for varying durations in team sports has been used to identify training targets to inform the preparation of players. However, its usefulness has recently been questioned since it may still underestimate the training intensity required to produce specific physiological adaptations. Within this conceptual review, we aimed to: (i) describe the methods used to determine the MIP; (ii) compare the data obtained using MIP or whole-match analysis, considering the influence of different contextual factors; (iii) rationalise the use of the MIP in team sports practice and (iv) provide limitations and future directions in the area. Different methods are used to determine the MIP, with MIP values far greater than those derived from averaging across the whole match, although they could be affected by contextual factors that should be considered in practice. Additionally, while the MIP might be utilised during sport-specific drills, it is inappropriate to inform the intensity of interval-based, repeated sprint and linear speed training modes. Lastly, MIP does not consider any variable of internal load, a major limitation when informing training practice. In conclusion, practitioners should be aware of the potential use or misuse of the MIP.

Using global navigation satellite systems for modeling athletic performances in elite football players

This study aims to predict individual Acceleration-Velocity profiles (A-V) from Global Navigation Satellite System (GNSS) measurements in real-world situations. Data were collected from professional players in the Superleague division during a 1.5 season period (2019–2021). A baseline modeling performance was provided by time-series forecasting methods and compared with two multivariate modeling approaches using ridge regularisation and long short term memory neural networks. The multivariate models considered commercial features and new features extracted from GNSS raw data as predictor variables. A control condition in which profiles were predicted from predictors of the same session outlined the predictability of A-V profiles. Multivariate models were fitted either per player or over the group of players. Predictor variables were pooled according to the mean or an exponential weighting function. As expected, the control condition provided lower error rates than other models on average (p = 0.001). Reference and multivariate models did not show significant differences in error rates (p = 0.124), regardless of the nature of predictors (commercial features or extracted from signal processing methods) or the pooling method used. In addition, models built over a larger population did not provide significantly more accurate predictions. In conclusion, GNSS features seemed to be of limited relevance for predicting individual A-V profiles. However, new signal processing features open up new perspectives in athletic performance or injury occurrence modeling, mainly if higher sampling rate tracking systems are considered.

The field and resistance training loads of academy rugby league players during a pre-season: Comparisons across playing positions

Male academy rugby league players are required to undertake field and resistance training to develop the technical, tactical and physical qualities important for success in the sport. However, limited research is available exploring the training load of academy rugby league players. Therefore, the purpose of this study was to quantify the field and resistance training loads of academy rugby league players during a pre-season period and compare training loads between playing positions (i.e., forwards vs. backs). Field and resistance training load data from 28 adolescent male (age 17 ± 1 years) rugby league players were retrospectively analysed following a 13-week pre-season training period (85 total training observations; 45 field sessions and 40 resistance training sessions). Global positioning system microtechnology, and estimated repetition volume was used to quantify external training load, and session rating of perceived exertion (sRPE) was used to quantify internal training load. Positional differences (forwards n = 13 and backs n = 15) in training load were established using a linear mixed effect model. Mean weekly training frequency was 7 ± 2 with duration totaling 324 ± 137 minutes, and a mean sRPE of 1562 ± 678 arbitrary units (AU). Backs covered more high-speed distance than forwards in weeks two (p = 0.024), and 11 (p = 0.028). Compared to the forwards, backs completed more lower body resistance training volume in week one (p = 0.02), more upper body volume in week three (p< 0.001) and week 12 (p = 0.005). The findings provide novel data on the field and resistance-based training load undertaken by academy rugby league players across a pre-season period, highlighting relative uniformity between playing positions. Quantifying training load can support objective decision making for the prescription and manipulation of future training, ultimately aiming to maximise training within development pathways.

A Validation Study of Heart Rate Variability Index in Monitoring Basketball Training Load

This study aimed to investigate whether the heart rate variability index (TL_HRV) during five ball-drills could be used to quantify training load (TL) in collegiate basketball players. Ten elite male college basketball athletes (18.2 ± 0.4 years) were recruited to perform five ball-drills (1V1, 2V2, 3V3, 4V4, and 5V5) which lasted 10 min and varied in intensity. During each drill, TL_HRV, training impulse (TRIMP), rating of perceived exertion (RPE), speed, and distance were recorded by Firstbeat, Foster’s RPE scale, and SiMi Scout. The correlation (Spearman’s and Pearson’s correlation coefficient), reliability (intra-class correlation coefficient, ICC), and agreement (Bland-Altman plots) among TL_HRV, TRIMP, RPE, speed, and distance were examined. TL_HRV was significantly correlated with TRIMP (r = 0.34, p = 0.015) and RPE (r = 0.42, p = 0.002). TL_HRV was significantly correlated with training intensity (r = 0.477, p = 0.006) but not with volume (r = 0.272, p = 0.056). TL_HRV and TRIMP, RPE showed significant intraclass relationships (ICC = 0.592, p = 0.0003). Moreover, TL_HRV differentiated basketball drills of equal volume and varying intensity. We concluded that TL_HRVmay serve as an objective and rational measure to monitor TL in basketball players.

Validating an algorithm from a trunk-mounted wearable sensor for detecting stroke events in tennis

This study analysed the accuracy of a prototype algorithm for tennis stroke detection from wearable technology. Strokes from junior-elite tennis players over 10 matches were analysed. Players wore a GPS unit containing an accelerometer, gyroscope and magnetometer. Manufacturer-developed algorithms determined stoke type and count (forehands, backhands, serves and other). Matches were video recorded to manually code ball contacts and shadow swing events for forehands, backhands and serves and further by stroke classifications (i.e., drive, volley, slice, end-range). Comparisons between algorithm and coding were analysed via ANOVA and Bland-Altman plots at the match-level and error rates for specific stroke-types. No significant differences existed for stroke count between the algorithm and manual coding (p > 0.05). Significant (p < 0.0001) overestimation of "Other" strokes were observed from the algorithm, with no difference in groundstrokes and serves (p > 0.05). Serves had the highest accuracy of all stroke types (≥98%). Forehand and backhand "drives" were the most accurate (>86%), with volleys mostly undetected (58-60%) and slices and end-range strokes likely misclassified (49-51%). The prototype algorithm accurately quantifies serves and forehand and backhand "drives" and serves. However, underestimations of shadow swings and overestimations of "other" strokes suggests strokes with reduced trunk rotation have poorer detection accuracy.

Overtraining Syndrome Symptoms and Diagnosis in Athletes: Where Is the Research? A Systematic Review

CONTEXT

To understand overtraining syndrome (OTS), it is important to detail the physiological and psychological changes that occur in athletes.

OBJECTIVES

To systematically establish and detail the physiological and psychological changes that occur as a result of OTS in athletes.

METHODS

Databases were searched for studies that were (1) original investigations; (2) English, full-text articles; (3) published in peer-reviewed journals; (4) investigations into adult humans and provided (5) objective evidence that detailed changes in performance from prior to the onset of OTS diagnosis and that performance was suppressed for more than 4 weeks and (6) objective evidence of psychological symptoms.

RESULTS

Zero studies provided objective evidence of detailed changes in performance from prior to the onset of OTS diagnosis and demonstrated suppressed performance for more than 4 weeks accompanied by changes in psychological symptoms.

CONCLUSIONS

All studies failed to provide evidence of changes in performance and mood from "healthy" to an overtrained state with evidence of prolonged suppression of performance. While OTS may be observed in the field, little data is available describing how physiological and psychological symptoms manifest. This stems from vague terminology, difficulties in monitoring for prolonged periods of time, and the need for prospective testing. Real-world settings may facilitate the collection of such data, but the ideal testing battery that can easily be conducted on a regular basis does not yet exist. Consequently, it must be concluded that an evidence base of sufficient scientific quality for understanding OTS in athletes is lacking.

The inter-device reliability of global navigation satellite systems during team sport movement across multiple days

OBJECTIVES

(1) Determine the inter-device and inter-manufacturer reliability; and (2) investigate the variation in reliability over time for common global navigation satellite systems.

DESIGN

Repeated measures.

METHODS

A total of twenty 10-Hz devices manufactured by StatSports (n = 10, Apex Pro; StatSports, Newry, Ireland) and Catapult Sports (n = 10, Vector S7; Catapult Sports, Melbourne, Australia) were towed on a sprint sled during 8 × 40-minute team sport movement protocol over a 4-week period. The coefficient of variations for distance, velocity and acceleration/deceleration metrics were calculated to show dispersion of the data relative to the mean or median for each manufacturer and interpreted as good, ≤5%; moderate, <10%; and poor, coefficient of variation ≥10%. The coefficient of variation range described the variation in reliability and was interpreted as small, ≤5%; moderate, <10% and large, ≥10%. Inter-manufacturer agreement was represented as a Cohen d (±95% confidence interval) standardised effect size.

RESULTS

Inter-device reliability for distance, peak velocity and average acceleration was good (coefficient of variation = 0.1 to 3.9%) for both manufacturers, with small variation across sessions. For most threshold-based acceleration and deceleration counts, StatSports devices showed good to moderate reliability, with moderate variation across sessions; Catapult showed good to poor reliability, with large variation across sessions. Inter-manufacturer agreement demonstrated moderate to very large effect sizes reported for most metrics.

CONCLUSIONS

Reliability was suitable and consistent for measures of distance, velocity, and average acceleration. StatSports devices generally possessed suitable reliability and consistency for threshold-based accelerations and decelerations, though Catapult devices did not. Most metrics should not be compared between manufacturers.

The Global Session Metric Score (GSMs): A Modified Session-Specific Exertional Index

Monitoring session training load to optimize the training stress that drives athlete adaptation and subsequent performance, is fundamental to periodization and programming. Analyzing the internal load experienced by the individual in response to the external load prescribed by coaching staff is crucial to avoid overtraining and optimize training adaptation. Subjective measures provide more information regarding individual training load, as heart rate measures alone do not account for collisions, eccentric muscle actions, muscle soreness, weather conditions, or accumulated training loads, which are paramount to the athlete experience. However, the current subjective metric for interpreting session training load (sRPE) is poorly shaped to the athlete's global response to the whole session, often showing poorer correlations to heart rate (HR) measures during intermittent or high-intensity activity. This study introduces a new metric, the Global Session Metric Score (GSMs), which creates a symmetrical relation between the verbal descriptor and numeric values, as well as more applicable session-specific verbal descriptors for the highest level of exertion. Twenty-four D1 male college soccer field players (age: 20.5 +/– 1.42) wore HR monitors and reported GSMs for all practices and games within an entire season. Linear regression with 10-fold cross validation was used to test the relation between GSMs with B-TRIMP and E-TRIMP, respectively. These models demonstrate good performance with consistency and reliability in the estimation of GSMs to predict both B-TRIMP (R² = 0.75–0.77) and E-TRIMP (R² = 0.76–0.78). The findings show promise for the GSMs index as a reliable means for measuring load in both training and matches during a high-intensity intermittent team sport. Future studies should directly compare GSMs to the existing sRPE scale within a controlled laboratory setting and across various other sports. GSMs provides coaches and clinicians a simple and cost-effective alternative to heart rate monitors, as well as a proficient measure of internal training load experienced by the individual.

Validity and Reliability of the Inertial Measurement Unit for Barbell Velocity Assessments: A Systematic Review

The use of inertial measurement unit (IMU) has become popular in sports assessment. In the case of velocity-based training (VBT), there is a need to measure barbell velocity in each repetition. The use of IMUs may make the monitoring process easier; however, its validity and reliability should be established. Thus, this systematic review aimed to (1) identify and summarize studies that have examined the validity of wearable wireless IMUs for measuring barbell velocity and (2) identify and summarize studies that have examined the reliability of IMUs for measuring barbell velocity. A systematic review of Cochrane Library, EBSCO, PubMed, Scielo, Scopus, SPORTDiscus, and Web of Science databases was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. From the 161 studies initially identified, 22 were fully reviewed, and their outcome measures were extracted and analyzed. Among the eight different IMU models, seven can be considered valid and reliable for measuring barbell velocity. The great majority of IMUs used for measuring barbell velocity in linear trajectories are valid and reliable, and thus can be used by coaches for external load monitoring.