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.

Training and match demands differ between the regular season and finals in semi-professional basketball

Basketball competitions often include a scheduled regular season followed by knock-out finals. Understanding training and match demands through the season can help optimize performance and reduce injury risk. This study investigated whether training and/or match demands differed between the regular season and finals, and whether these differences were dependent on player role. Average session intensity and volume and durations of relative exercise intensities (inactive, light, moderate-vigorous, maximal, supramaximal) were quantified during training sessions and matches using accelerometry in two semi-professional basketball teams (n = 23; 10 women, 13 men). Training and match demands were compared between the regular season (training: 445 observations; matches: 387 observations) and finals (training: 113 observations, matches: 75 observations) with consideration of player role (starters, in-rotation bench, out-rotation bench). During finals matches, starters received 4.4 min more playing time (p = 0.03), performed 14% more absolute maximal activity (p < 0.01) and had 8% less relative inactive time (p = 0.02) when compared to the regular season. Out-rotation bench players received 2.1 min less playing time (p < 0.01), performed 33% less absolute maximal activity (p = 0.01) and 57% less absolute supramaximal activity (p < 0.01) in finals when compared to the regular season. During finals training sessions, average training intensity was 5% higher (p = 0.02), absolute moderate-vigorous activity was 3% higher (p = 0.04), relative maximal activity was 12% higher (p < 0.01), and relative inactive time was 5% lower (p = 0.03) when compared to the regular season. These findings suggest starters need to be physically prepared for greater match demands during finals, while out-rotation bench players should supplement their training during finals with extra supramaximal activity to maintain their conditioning levels for matches.

Residual neuromuscular fatigue influences subsequent on-court activity in basketball

AbstractThe aim of this study was to determine if residual neuromuscular fatigue influenced subsequent match and training activity in professional women's basketball. Prior to matches and training sessions throughout a season, players performed countermovement jumps while wearing a magnetic, angular rate and gravity (acceleration) sensor on their upper back. Flight time to contraction time ratio was used to determine neuromuscular performance and to identify neuromuscular fatigue. Average session intensity and volume, proportion of live time spent in different intensity bands (matches), and absolute and relative time spent in different intensity bands (training) were quantified using accelerometry. Residual neuromuscular fatigue was deemed to be present when the decrement in neuromuscular performance relative to pre-season baseline was greater than the smallest worthwhile change. Players displayed residual neuromuscular fatigue before 16% of matches and 33% of training sessions. When players were fatigued prior to matches, the proportion of live time undertaking supramaximal activity was 5.7% less (p = 0.02) and moderate-vigorous activity was 3.7% more than when not fatigued (p = 0.02). When fatigued prior to training, the players displayed a 2.6% decrement in average intensity (p = 0.02), 2.8% decrement in absolute (p = 0.01) and 5.0% decrement in relative (p = 0.01) maximal activity, as well as 13.3% decrement in absolute (p < 0.01) and 6.8% decrement in relative (p < 0.01) supramaximal activity when compared to not being fatigued. These findings suggest that residual neuromuscular fatigue influences players' ability to perform supramaximal activity, which highlights the importance of monitoring neuromuscular performance throughout a professional season.

On-Court Activity and Game-Related Statistics during Scoring Streaks in Basketball: Applied Use of Accelerometers

The aim of this observational study was to determine if on-court activity and match statistics differed between periods of scoring streaks and regular play in basketball. Thirty-seven basketballers including professional women, semi-professional women and semi-professional men wore accelerometers during competitive matches throughout a season. Accelerometry-derived live-time individual on-court exercise intensity and team game-related statistics were compared between scoring streaks (periods of play where the teams participating in the study scored at least three times in a row), streaks against (periods of play where the opposition teams scored at least three times in a row) and regular play. Few differences existed in the average exercise intensity between streak types. During streaks against, there was a 5–15% lower proportion of 2-point attempts, 0.8–1.3 fewer defensive rebounds per minute and 0.3–1.6 fewer shot attempts per minute compared to regular play and scoring streaks, and there were 0.3 fewer offensive rebounds per minute compared to regular play. During scoring streaks, there were 0.5 more defensive rebounds per minute, 1.3 more shot attempts per minute, a 43% greater shooting percentage and a 10% lower proportion of 3-point attempts compared to regular play. To reduce the chances of streaks against, teams should focus on facilitating 2-point shot attempts and consider implementing a 3:1 ratio of 2-point to 3-point attempts to maximize scoring success, and they should focus on winning rebounds to facilitate more shot attempts.

Submaximal Fitness Tests in Team Sports: A Theoretical Framework for Evaluating Physiological State

Team-sports staff often administer non-exhaustive exercise assessments with a view to evaluating physiological state, to inform decision making on athlete management (e.g., future training or recovery). Submaximal fitness tests have become prominent in team-sports settings for observing responses to a standardized physical stimulus, likely because of their time-efficient nature, relative ease of administration, and physiological rationale. It is evident, however, that many variations of submaximal fitness test characteristics, response measures, and monitoring purposes exist. The aim of this scoping review is to provide a theoretical framework of submaximal fitness tests and a detailed summary of their use as proxy indicators of training effects in team sports. Using a review of the literature stemming from a systematic search strategy, we identified five distinct submaximal fitness test protocols characterized in their combinations of exercise regimen (continuous or intermittent) and the progression of exercise intensity (fixed, incremental, or variable). Heart rate-derived indices were the most studied outcome measures in submaximal fitness tests and included exercise (exercise heart rate) and recovery (heart rate recovery and vagal-related heart rate variability) responses. Despite the disparity between studies, these measures appear more relevant to detect positive chronic endurance-oriented training effects, whereas their role in detecting negative transient effects associated with variations in autonomic nervous system function is not yet clear. Subjective outcome measures such as ratings of perceived exertion were less common in team sports, but their potential utility when collected alongside objective measures (e.g., exercise heart rate) has been advocated. Mechanical outcome measures either included global positioning system-derived locomotor outputs such as distance covered, primarily during standardized training drills (e.g., small-sided games) to monitor exercise performance, or responses derived from inertial measurement units to make inferences about lower limb neuromuscular function. Whilst there is an emerging interest regarding the utility of these mechanical measures, their measurement properties and underpinning mechanisms are yet to be fully established. Here, we provide a deeper synthesis of the available literature, culminating with evidence-based practical recommendations and directions for future research.

Automated Classification of Changes of Direction in Soccer Using Inertial Measurement Units

Changes of direction (COD) are an important aspect of soccer match play. Understanding the physiological and biomechanical demands on players in games allows sports scientists to effectively train and rehabilitate soccer players. COD are conventionally recorded using manually annotated time-motion video analysis which is highly time consuming, so more time-efficient approaches are required. The aim was to develop an automated classification model based on multi-sensor player tracking device data to detect COD > 45°. Video analysis data and individual multi-sensor player tracking data (GPS, accelerometer, gyroscopic) for 23 academy-level soccer players were used. A novel 'GPS-COD Angle' variable was developed and used in model training; along with 24 GPS-derived, gyroscope and accelerometer variables. Video annotation was the ground truth indicator of occurrence of COD > 45°. The random forest classifier using the full set of features demonstrated the highest accuracy (AUROC = 0.957, 95% CI = 0.956-0.958, Sensitivity = 0.941, Specificity = 0.772. To balance sensitivity and specificity, model parameters were optimised resulting in a value of 0.889 for both metrics. Similarly high levels of accuracy were observed for random forest models trained using a reduced set of features, accelerometer-derived variables only, and gyroscope-derived variables only. These results point to the potential effectiveness of the novel methodology implemented in automatically identifying COD in soccer players.

Effect of Player Role and Competition Level on Player Demands in Basketball

This study compared basketball training and match demands between player roles (starters, in-rotation bench players, out-rotation bench players) and between competition levels (semi-professional, professional). Thirty-seven players from one professional women's team, one semi-professional women's team, and one semi-professional men's team wore accelerometers during training and matches throughout a competitive season. All teams were used for player role comparisons and the women's teams were used to compare competition levels. Match and training session average intensity and volume, and durations of relative exercise intensities (inactive, light, moderate-vigorous, maximal, supramaximal) were calculated. Compared to out-rotation bench players, starters experienced twice the average match intensity and volume, spent 50% less match time being inactive, and spent 1.7-4.2× more match time in all other activity categories (p < 0.01). Compared to in-rotation bench players, starters experienced 1.2× greater average match intensity and volume, spent 17% less match time being inactive, and spent 1.4-1.5× more match time performing moderate-vigorous and maximal activity (p < 0.01). No differences in match demands were found between women's competition levels, however the professional team experienced double the cumulative weekly training volume of the semi-professional team and spent 1.6-2.1× more cumulative weekly time in all activity categories (p < 0.01). To improve performance and reduce injury risk, players should prepare for the greatest match demands they could encounter during a season while considering potential changes to their role. Additionally, players might need their training volume managed when transitioning from a semi-professional to a professional season to reduce the injury risk from sharp increases in training demands.

Preseason Training Improves Perception of Fatigue and Recovery From a Futsal Training Session

PURPOSE

To compare the posttraining recovery timeline of elite Brazilian futsal athletes before (Pre-PS) and after 10 weeks of the preseason (Post-PS) period of high-intensity technical-tactical training.

METHODS

At the start (n = 13) and at the end of the preseason (n = 7), under-20 male futsal players undertook fitness testing for maximal aerobic power, the countermovement jump (CMJ), and the 10-m sprint with change of direction. Furthermore, at both Pre-PS and Post-PS, the players participated in a training session where performance and psychophysiological measures were recorded before, immediately, 3, 24, and 48 hours postsession. The measures included CMJ, 10-m sprint, creatine kinase, Total Quality Recovery Scale, and Brunel Mood Scale. Effect size (ES) analyses compared fitness and posttraining recovery values for each parameter at Pre-PS versus Post-PS.

RESULTS

Only trivial ES (-0.02 to 0.11) was evident in maximal aerobic power, CMJ, and 10-m sprint at Post-PS compared with Pre-PS. For the timeline of recovery, only trivial and small ESs were evident for the 10-m sprint (-0.12 to 0.49), though CMJ recovery was improved at 3 hours (0.87) and 48 hours (1.27) at Post-PS and creatine kinase was lower at 48 hours (-1.33) at Post-PS. Perception of recovery was improved in Post-PS at 3 hours (1.50) and 24 hours postsession (0.92). Furthermore, perception of effort was lower immediately after the session (-0.29), fatigue was lower at 3 hours (-0.63), and vigor responses were improved in all postseason assessments (0.59 to 1.13).

CONCLUSION

Despite minimal changes in fitness, preseason training attenuated players' perception of effort and fatigue and improved their recovery profile following a high-intensity technical-tactical training session.

Measuring Physical Demands in Basketball: An Explorative Systematic Review of Practices

BACKGROUND

Measuring the physical work and resultant acute psychobiological responses of basketball can help to better understand and inform physical preparation models and improve overall athlete health and performance. Recent advancements in training load monitoring solutions have coincided with increases in the literature describing the physical demands of basketball, but there are currently no reviews that summarize all the available basketball research. Additionally, a thorough appraisal of the load monitoring methodologies and measures used in basketball is lacking in the current literature. This type of critical analysis would allow for consistent comparison between studies to better understand physical demands across the sport.

OBJECTIVES

The objective of this systematic review was to assess and critically evaluate the methods and technologies used for monitoring physical demands in competitive basketball athletes. We used the term 'training load' to encompass the physical demands of both training and game activities, with the latter assumed to provide a training stimulus as well. This review aimed to critique methodological inconsistencies, establish operational definitions specific to the sport, and make recommendations for basketball training load monitoring practice and reporting within the literature.

METHODS

A systematic review of the literature was performed using EBSCO, PubMed, SCOPUS, and Web of Science to identify studies through March 2020. Electronic databases were searched using terms related to basketball and training load. Records were included if they used a competitive basketball population and incorporated a measure of training load. This systematic review was registered with the International Prospective Register of Systematic Reviews (PROSPERO Registration # CRD42019123603), and approved under the National Basketball Association (NBA) Health Related Research Policy.

RESULTS

Electronic and manual searches identified 122 papers that met the inclusion criteria. These studies reported the physical demands of basketball during training (n = 56), competition (n = 36), and both training and competition (n = 30). Physical demands were quantified with a measure of internal training load (n = 52), external training load (n = 29), or both internal and external measures (n = 41). These studies examined males (n = 76), females (n = 34), both male and female (n = 9), and a combination of youth (i.e. under 18 years, n = 37), adults (i.e. 18 years or older, n = 77), and both adults and youth (n = 4). Inconsistencies related to the reporting of competition level, methodology for recording duration, participant inclusion criteria, and validity of measurement systems were identified as key factors relating to the reporting of physical demands in basketball and summarized for each study.

CONCLUSIONS

This review comprehensively evaluated the current body of literature related to training load monitoring in basketball. Within this literature, there is a clear lack of alignment in applied practices and methodological framework, and with only small data sets and short study periods available at this time, it is not possible to draw definitive conclusions about the true physical demands of basketball. A detailed understanding of modern technologies in basketball is also lacking, and we provide specific guidelines for defining and applying duration measurement methodologies, vetting the validity and reliability of measurement tools, and classifying competition level in basketball to address some of the identified knowledge gaps. Creating alignment in best-practice basketball research methodology, terminology and reporting may lead to a more robust understanding of the physical demands associated with the sport, thereby allowing for exploration of other research areas (e.g. injury, performance), and improved understanding and decision making in applying these methods directly with basketball athletes.

The Relationships between Internal and External Load Measures for Division I College Football Practice

The aim of this study is to explore the relationships between internal and external load measures in American football. Thirty football players wore a portable integrated monitor unit for 10 weeks during the fall football season. Relationships between internal and external load measurements were determined. Internal load consisted of heart rate zones and heart rate-derived measures and session Ratings of Perceived Exertion (sRPE). External load consisted of distance in different speed zones, total distance traveled, and accelerations. There were many significant positive relationships, but the meaningful relationships (r > 0.5) were between heart rate-derived measures of load (Training Impulse and heart rate reserve) and low-intensity movement and total distance. Only accelerations between 1 and 1.99 m·s⁻² were moderately correlated to heart rate-derived internal load. RPE values alone did not correlate strong enough with any of the measure but sRPE training load (sRPE-TL) correlated to most external values. Overall, moderate correlations were present between heart rate-derived internal load to total distance and lower intensity movement. sRPE-TL values had high correlations but were highly dependent on duration, not perceived exertion. When addressing load in American football, duration of the session is a key component in determining internal load as HR data and sRPE alone do not correlate highly with external loads.

Accelerometry as a method for external workload monitoring in invasion team sports. A systematic review

Accelerometry is a recent method used to quantify workload in team sports. A rapidly increasing number of studies supports the practical implementation of accelerometry monitoring to regulate and optimize training schemes. Therefore, the purposes of this study were: (1) to reflect the current state of knowledge about accelerometry as a method of workload monitoring in invasion team sports according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines, and (2) to conclude recommendations for application and scientific investigations. The Web of Science, PubMed and Scopus databases were searched for relevant published studies according to the following keywords: "accelerometry" or "accelerometer" or "microtechnology" or "inertial devices", and "load" or "workload", and "sport". Of the 1383 studies initially identified, 118 were selected for a full review. The main results indicate that the most frequent findings were (i) devices' body location: scapulae; (b) devices brand: Catapult Sports; (iii) variables: PlayerLoadTM and its variations; (iv) sports: rugby, Australian football, soccer and basketball; (v) sex: male; (vi) competition level: professional and elite; and (vii) context: separate training or competition. A great number of variables and devices from various companies make the comparability between findings difficult; unification is required. Although the most common location is at scapulae because of its optimal signal reception for time-motion analysis, new methods for multi-location skills and locomotion assessment without losing tracking accuracy should be developed.

Sensitivity, reliability and construct validity of GPS and accelerometers for quantifying peak periods of rugby competition

Training prescription and monitoring of team-sport athletes rely on accurate quantification of player movement. Our aim was to determine the sensitivity, reliability and construct validity of measures derived from a wearable device incorporating Global Positioning System (GPS) and accelerometer technology to quantify the peak periods of rugby competition. Match movement data were collected from 30 elite and 30 sub-elite rugby union players across respective competitive seasons. Accelerometer and GPS measures were analysed using a rolling average to identify peak movement for epochs ranging from 5 to 600 seconds. General linear mixed modelling was used to quantify the effects of playing position and match-half on the peak movement and variabilities within and between players represented reliability of each measure. Mean positional differences and match-half changes were assessed via standardisation and magnitude-based decisions. Sensitivity of measures was quantified via evaluation of ("signal") and typical error of measurement ("noise"). GPS and accelerometer measures had poor sensitivity for quantifying peak movement across all epochs and both levels of rugby union competition (noise 4× to 5× the signal). All measures displayed correspondingly low reliability across most epochs and both levels of competition (ICC<0.50). Construct validity was evident in mean differences between playing positions and match halves that were consistent with expected activity profiles in rugby union. However, it was clear from the pattern of differences across epoch durations and levels of competition that GPS and accelerometer measures provided different information about player movement. The poor sensitivity and low reliability of GPS and accelerometer measures of peak movement imply that rugby union players need to be monitored across many matches to obtain adequate precision for assessing individuals. Although all measures displayed construct validity, accelerometers provided meaningful information additional to that of GPS. We recommend using accelerometers alongside GPS to monitor and prescribe match respresentative training.

Influence of Faster and Slower Recovery-Profile Classifications, Self-Reported Sleep, Acute Training Load, and Phase of the Microcycle on Perceived Recovery in Futsal Players

PURPOSE

To determine whether daily perceived recovery is explained from a multifactorial single-session classification of recovery (ie, faster vs slower) or other circumstantial factors (ie, previous training load, self-reported sleep, or phase of the microcycle).

METHODS

Nineteen elite male futsal players were initially allocated to a recovery-classification group (faster recovery, slower physiological, or slower perceptual) based on previous research using a multifactorial cluster-analysis technique. During 4 ensuing weeks of preseason, training loads were monitored via player load, training impulse, and session rating of perceived exertion. Before each day's training, players reported their perception of recovery (Total Quality of Recovery scale [TQR]) and the number of hours and perceived quality of sleep the night prior. A hierarchical linear mixed model was used to analyze the effect of the different recovery profiles, training load, sleep, and phase of the microcycle (ie, start, middle, end) on daily TQR.

RESULTS

The recovery classification of players (P = .20), training load (training impulse, P = .32; player load, P = .23; session rating of perceived exertion, P = .46), and self-reported hours slept the night before (P = .45) did not significantly influence TQR. However, perceived sleep quality (P < .01) and phase of the microcycle (P < .01) were significantly associated with TQR (r2 = .41).

CONCLUSIONS

Neither recovery classification nor prior training load influenced perceived recovery during the preseason. However, higher TQR was evident with better self-reported sleep quality, whereas lower values were associated with phases of the training week.

The relative contribution of training intensity and duration to daily measures of training load in professional rugby league and union

This study examined the relative contribution of exercise duration and intensity to team-sport athlete's training load. Male, professional rugby league (n = 10) and union (n = 22) players were monitored over 6- and 52-week training periods, respectively. Whole-session (load) and per-minute (intensity) metrics were monitored (league: session rating of perceived exertion training load [sRPE-TL], individualised training impulse, total distance, BodyLoad™; union: sRPE-TL, total distance, high-speed running distance, PlayerLoad™). Separate principal component analyses were conducted on the load and intensity measures to consolidate raw data into principal components (PC, k = 4). The first load PC captured 70% and 74% of the total variance in the rugby league and rugby union datasets, respectively. Multiple linear regression subsequently revealed that session duration explained 73% and 57% of the variance in first load PC, respectively, while the four intensity PCs explained an additional 24% and 34%, respectively. Across two professional rugby training programmes, the majority of the variability in training load measures was explained by session duration (~60-70%), while a smaller proportion was explained by session intensity (~30%). When modelling the training load, training intensity and duration should be disaggregated to better account for their between-session variability.

Pacing characteristics of whole and part-game players in professional rugby union

Contemporary theories on players' intensity distribution in team sports suggest that they regulate their outputs using pacing strategies. There is currently limited information on how movement patterns and pacing strategies of rugby union players in different position groups (forwards and backs) vary when exposed to different bout types (whole game, starter or finisher). Global positioning system (GPS) and accelerometer data were collected from 100 professional match participations to determine temporal effects on movement patterns. For forwards, finishers (players who entered the game as substitutes) demonstrated significantly greater high-speed running distance (% difference, ± 90%CI; magnitude-based inference and effect size) (↑ 55, ±17%; very likely large) and acceleration frequency (↑ 78, ±59%; very likely large) than whole game players. For backs, starters (players who started the game and were later substituted) displayed greater high-speed running distance than whole game players (↑ 27, ±21%; ES = likely medium) but this difference did not achieve statistical significance (p = .07). Forwards displayed "slow-positive" pacing strategies regardless of bout type, while backs displayed "flat" pacing strategies. Forwards and backs adopt different pacing strategies regardless of bout type, with forwards demonstrating progressively greater performance decrements over the course of the match. These findings reflect differing physical demands, notably contact and running loads, of players in different positions.

The Use of Microtechnology to Quantify the Peak Match Demands of the Football Codes: A Systematic Review

BACKGROUND

Quantifying the peak match demands within the football codes is useful for the appropriate prescription of external training load. Wearable microtechnology devices can be used to identify the peak match demands, although various methodologies exist at present.

OBJECTIVES

This systematic review aimed to identify the methodologies and microtechnology-derived variables used to determine the peak match demands, and to summarise current data on the peak match demands in the football codes.

METHODS

A systematic search of electronic databases was performed from earliest record to May 2018; keywords relating to microtechnology, peak match demands and football codes were used.

RESULTS

Twenty-seven studies met the eligibility criteria. Six football codes were reported: rugby league (n = 7), rugby union (n = 5), rugby sevens (n = 4), soccer (n = 6), Australian Football (n = 2) and Gaelic Football (n = 3). Three methodologies were identified: moving averages, segmental and 'ball in play'. The moving averages is the most commonly used (63%) and superior method, identifying higher peak demands than other methods. The most commonly used variables were relative distance covered (63%) and external load in specified speed zones (57%).

CONCLUSION

This systematic review has identified moving averages to be the most appropriate method for identifying the peak match demands in the football codes. Practitioners and researchers should choose the most relevant duration-specific period and microtechnology-derived variable for their specific needs. The code specific peak match demands revealed can be used for the prescription of conditioning drills and training intensity.

Modelling Movement Energetics Using Global Positioning System Devices in Contact Team Sports: Limitations and Solutions

Quantifying the training and competition loads of players in contact team sports can be performed in a variety of ways, including kinematic, perceptual, heart rate or biochemical monitoring methods. Whilst these approaches provide data relevant for team sports practitioners and athletes, their application to a contact team sport setting can sometimes be challenging or illogical. Furthermore, these methods can generate large fragmented datasets, do not provide a single global measure of training load and cannot adequately quantify all key elements of performance in contact team sports. A previous attempt to address these limitations via the estimation of metabolic energy demand (global energy measurement) has been criticised for its inability to fully quantify the energetic costs of team sports, particularly during collisions. This is despite the seemingly unintentional misapplication of the model's principles to settings outside of its intended use. There are other hindrances to the application of such models, which are discussed herein, such as the data-handling procedures of Global Position System manufacturers and the unrealistic expectations of end users. Nevertheless, we propose an alternative energetic approach, based on Global Positioning System-derived data, to improve the assessment of mechanical load in contact team sports. We present a framework for the estimation of mechanical work performed during locomotor and contact events with the capacity to globally quantify the work done during training and matches.

Training Load Monitoring in Team Sports: A Novel Framework Separating Physiological and Biomechanical Load-Adaptation Pathways

There have been considerable advances in monitoring training load in running-based team sports in recent years. Novel technologies nowadays offer ample opportunities to continuously monitor the activities of a player. These activities lead to internal biochemical stresses on the various physiological subsystems; however, they also cause internal mechanical stresses on the various musculoskeletal tissues. Based on the amount and periodization of these stresses, the subsystems and tissues adapt. Therefore, by monitoring external loads, one hopes to estimate internal loads to predict adaptation, through understanding the load-adaptation pathways. We propose a new theoretical framework in which physiological and biomechanical load-adaptation pathways are considered separately, shedding new light on some of the previously published evidence. We hope that it can help the various practitioners in this field (trainers, coaches, medical staff, sport scientists) to align their thoughts when considering the value of monitoring load, and that it can help researchers design experiments that can better rationalize training-load monitoring for improving performance while preventing injury.

The Fit Matters: Influence of Accelerometer Fitting and Training Drill Demands on Load Measures in Rugby League Players

PURPOSE

To determine the relationship between drill type and accelerometer-derived loads during various team-sport activities and examine the influence of unit fitting on these loads.

METHODS

Sixteen rugby league players were fitted with microtechnology devices in either manufacturer vests or playing jerseys before completing standardized running, agility, and tackling drills. Two-dimensional (2D) and 3-dimensional (3D) accelerometer loads (BodyLoad™) per kilometer were compared across drills and fittings (ie, vest and jersey).

RESULTS

When fitted in a vest, 2D BodyLoad was higher during tackling (21.5 [14.8] AU/km) than during running (9.5 [2.5] AU/km) and agility (10.3 [2.7] AU/km). Jersey fitting resulted in more than 2-fold higher BodyLoad during running (2D = 9.5 [2.7] vs 29.3 [14.8] AU/km, 3D = 48.5 [14.8] vs 111.5 [45.4] AU/km) and agility (2D = 10.3 [2.7] vs 21.0 [8.1] AU/km, 3D = 40.4 [13.6] vs 77.7 [26.8] AU/km) compared with a vest fitting. Jersey fitting also produced higher BodyLoad during tackling drills (2D = 21.5 [14.8] vs 27.8 [18.6] AU/km, 3D = 42.0 [21.4] vs 63.2 [33.1] AU/km).

CONCLUSIONS

This study provides evidence supporting the construct validity of 2D BodyLoad for assessing collision/tackling load in rugby league training drills. Conversely, the large values obtained from 3D BodyLoad (which includes the vertical load vector) appear to mask small increases in load during tackling drills, rendering 3D BodyLoad insensitive to changes in contact load. Unit fitting has a large influence on accumulated accelerometer loads during all drills, which is likely related to greater incidental unit movement when units are fitted in jerseys. Therefore, it is recommended that athletes wear microtechnology units in manufacturer-provided vests to provide valid and reliable information.

Reliability of Wearable Inertial Measurement Units to Measure Physical Activity in Team Handball

PURPOSE

To assess the reliability and sensitivity of commercially available inertial measurement units to measure physical activity in team handball.

METHOD

Twenty-two handball players were instrumented with 2 inertial measurement units (OptimEye S5; Catapult Sports, Melbourne, Australia) taped together. They participated in either a laboratory assessment (n = 10) consisting of 7 team handball-specific tasks or field assessment (n = 12) conducted in 12 training sessions. Variables, including PlayerLoad™ and inertial movement analysis (IMA) magnitude and counts, were extracted from the manufacturers' software. IMA counts were divided into intensity bands of low (1.5-2.5 m·s^-1), medium (2.5-3.5 m·s^-1), high (>3.5 m·s^-1), medium/high (>2.5 m·s^-1), and total (>1.5 m·s^-1). Reliability between devices and sensitivity was established using coefficient of variation (CV) and smallest worthwhile difference (SWD).

RESULTS

Laboratory assessment: IMA magnitude showed a good reliability (CV = 3.1%) in well-controlled tasks. CV increased (4.4-6.7%) in more-complex tasks. Field assessment: Total IMA counts (CV = 1.8% and SWD = 2.5%), PlayerLoad (CV = 0.9% and SWD = 2.1%), and their associated variables (CV = 0.4-1.7%) showed a good reliability, well below the SWD. However, the CV of IMA increased when categorized into intensity bands (2.9-5.6%).

CONCLUSION

The reliability of IMA counts was good when data were displayed as total, high, or medium/high counts. A good reliability for PlayerLoad and associated variables was evident. The CV of the previously mentioned variables was well below the SWD, suggesting that OptimEye's inertial measurement unit and its software are sensitive for use in team handball.

Trends Supporting the In-Field Use of Wearable Inertial Sensors for Sport Performance Evaluation: A Systematic Review

Recent technological developments have led to the production of inexpensive, non-invasive, miniature magneto-inertial sensors, ideal for obtaining sport performance measures during training or competition. This systematic review evaluates current evidence and the future potential of their use in sport performance evaluation. Articles published in English (April 2017) were searched in Web-of-Science, Scopus, Pubmed, and Sport-Discus databases. A keyword search of titles, abstracts and keywords which included studies using accelerometers, gyroscopes and/or magnetometers to analyse sport motor-tasks performed by athletes (excluding risk of injury, physical activity, and energy expenditure) resulted in 2040 papers. Papers and reference list screening led to the selection of 286 studies and 23 reviews. Information on sport, motor-tasks, participants, device characteristics, sensor position and fixing, experimental setting and performance indicators was extracted. The selected papers dealt with motor capacity assessment (51 papers), technique analysis (163), activity classification (19), and physical demands assessment (61). Focus was placed mainly on elite and sub-elite athletes (59%) performing their sport in-field during training (62%) and competition (7%). Measuring movement outdoors created opportunities in winter sports (8%), water sports (16%), team sports (25%), and other outdoor activities (27%). Indications on the reliability of sensor-based performance indicators are provided, together with critical considerations and future trends.

Validity and reliability of an accelerometer-based player tracking device

This study aimed to determine the intra- and inter-device accuracy and reliability of wearable athletic tracking devices, under controlled laboratory conditions. A total of nineteen portable accelerometers (Catapult OptimEye S5) were mounted to an aluminum bracket, bolted directly to an Unholtz Dickie 20K electrodynamic shaker table, and subjected to a series of oscillations in each of three orthogonal directions (front-back, side to side, and up-down), at four levels of peak acceleration (0.1g, 0.5g, 1.0g, and 3.0g), each repeated five times resulting in a total of 60 tests per unit, for a total of 1140 records. Data from each accelerometer was recorded at a sampling frequency of 100Hz. Peak accelerations recorded by the devices, Catapult PlayerLoad™, and calculated player load (using Catapult’s Cartesian formula) were used for the analysis. The devices demonstrated excellent intradevice reliability and mixed interdevice reliability. Differences were found between devices for mean peak accelerations and PlayerLoad™ for each direction and level of acceleration. Interdevice effect sizes ranged from a mean of 0.54 (95% CI: 0.34–0.74) (small) to 1.20 (95% CI: 1.08–1.30) (large) and ICCs ranged from 0.77 (95% CI: 0.62–0.89) (very large) to 1.0 (95% CI: 0.99–1.0) (nearly perfect) depending upon the magnitude and direction of the applied motion. When compared to the player load determined using the Cartesian formula, the Catapult reported PlayerLoad™ was consistently lower by approximately 15%. These results emphasize the need for industry wide standards in reporting validity, reliability and the magnitude of measurement errors. It is recommended that device reliability and accuracy are periodically quantified.

Quantification of Accelerometer Derived Impacts Associated With Competitive Games in National Collegiate Athletic Association Division I College Football Players

Wellman, AD, Coad, SC, Goulet, GC, and McLellan, CP. Quantification of accelerometer derived impacts associated with competitive games in National Collegiate Athletic Association division I college football players. J Strength Cond Res 31(2): 330-338, 2017-The aims of the present study were to (a) examine positional impact profiles of National Collegiate Athletic Association (NCAA) division I college football players using global positioning system (GPS) and integrated accelerometry (IA) technology and (b) determine if positional differences in impact profiles during competition exist within offensive and defensive teams. Thirty-three NCAA division I Football Bowl Subdivision players were monitored using GPS and IA (GPSports) during 12 regular season games throughout the 2014 season. Individual player data sets (n = 294) were divided into offensive and defensive teams, and positional subgroups. The intensity, number, and distribution of impact forces experienced by players during competition were recorded. Positional differences were found for the distribution of impacts within offensive and defensive teams. Wide receivers sustained more very light and light to moderate (5-6.5 G force) impacts than other position groups, whereas the running backs were involved in more severe (>10 G force) impacts than all offensive position groups, with the exception of the quarterbacks (p ≤ 0.05). The defensive back and linebacker groups were subject to more very light (5.0-6.0 G force) impacts, and the defensive tackle group sustained more heavy and very heavy (7.1-10 G force) impacts than other defensive positions (p ≤ 0.05). Data from the present study provide novel quantification of positional impact profiles related to the physical demands of college football games and highlight the need for position-specific monitoring and training in the preparation for the impact loads experienced during NCAA division I football competition.

Application of Global Positioning System and Microsensor Technology in Competitive Rugby League Match-Play: A Systematic Review and Meta-analysis

BACKGROUND

The use of global positioning system (GPS) devices with the inclusion of microsenor technology in rugby league enables measurement of player activity profiles to understand the demands of match-play and optimise on-field performance.

OBJECTIVE

The aim of this review was to systematically review the use of GPS and microsensor technology to quantify player activity profiles in match-play, and conduct a meta-analysis of relevant movement variables in order to present the contemporary and emerging themes within rugby league.

METHODS

A systematic search of electronic databases (MEDLINE, SPORTDiscus, CINAHL, Web of Science, Scopus, ScienceDirect, EMBASE, and Google Scholar) from the earliest record to February 2015 was conducted. Permutations of key words included GPS, microtechnology, activity profiles, match demands (movement or physical demands), and rugby league. A meta-analysis was conducted to provide a pooled mean and confidence intervals on comparable data from at least three studies.

RESULTS

Twenty-seven studies met the eligibility criteria and included 1270 male participants. The studies reported on GPS use in elite competition (n = 16) with limited representation of other competition standards: sub-elite (n = 6), amateur (n = 1) and junior (n = 3). All studies reported on movement variables (distance, relative distance, speed and accelerations), with studies analysing movement at high speed (n = 18, 66.7%), evaluating collision or impact variables (n = 15, 55.6%) and determining the metabolic energy (n = 2, 7.4%) associated with rugby league match-play. Activity profiles of varying positions, positional groups and levels of rugby league competition were described. Meta-analysis indicated that the total distance covered by backs and adjustables were both greater than forward positions, but adjustables covered greater relative distance than forwards and backs. Speed zones were typically categorised into six speed zones ranging from 0 to 36 km·h(-1), or into low- and high-intensity movement. Vast inconsistencies were apparent across studies in categorising movement at high speed, posing difficulties for comparison. Meta-analysis indicated that, although the number of repeated high-intensity effort (RHIE) bouts in elite players were similar to sub-elite (and both greater than juniors), the number of efforts per RHIE were significantly greater in elite than sub-elite players. Differential pacing strategies were adopted according to player selection (whole-match vs. interchange), time period within match-play and match outcome, in order to maintain high-intensity performance or to challenge for a win. Sizeable inconsistencies were also identified in the definitions of reported collisions (classified as mild, moderate and heavy) and impacts (six zone categories provided by manufacturer), making comparisons across studies difficult. Collision profiles were different between competition standard and position where elite players and forwards sustained more moderate- and high-intensity collisions than sub-elite players and backs, respectively. The recent inclusion of GPS-derived metabolic indices to activity profiles has also accentuated the distinctive workloads of positional groups during match-play where adjustables demonstrate the highest energy expenditure and metabolic power.

CONCLUSIONS

This review and the results of the meta-analysis have demonstrated that positional groups have varied kinematic and metabolic demands. During match play, forwards sustain the greatest number of collisions and RHIE bouts, outside backs participate in more high-speed running and cover the greatest distance, and adjustables work at high intensity covering the greatest relative distance with the highest metabolic cost. Therefore, specific training for each positional group should address their match requirements. In addition, sub-elite players exhibit lower intensity of play compared with elite players, as indicated by lower relative distance and less number of efforts per RHIE bout despite similarities in total distance covered and number of RHIE bouts. To prepare them for elite-level play, their training should incorporate higher intensity drills in which greater relative distance and number of efforts per RHIE bout are performed. Furthermore, the lack of consistency in the definition of speed zones, high-intensity movement, collisions and impacts, underscores the difficulties encountered in meaningful comparisons of player activity profiles between studies. Consensus of these definitions would facilitate direct comparisons within rugby league.

Mechanical Player Load™ using trunk-mounted accelerometry in football: Is it a reliable, task- and player-specific observation?

The aim of the present study was to examine reliability and construct convergent validity of Player Load™ (PL) from trunk-mounted accelerometry, expressed as a cumulative measure and an intensity measure (PL · min^-1). Fifteen male participants twice performed an overground football match simulation that included four different multidirectional football actions (jog, side cut, stride and sprint) whilst wearing a trunk-mounted accelerometer inbuilt in a global positioning system unit. Results showed a moderate-to-high reliability as indicated by the intra-class correlation coefficient (0.806-0.949) and limits of agreement. Convergent validity analysis showed considerable between-participant variation (coefficient of variation range 14.5-24.5%), which was not explained from participant demographics despite a negative association with body height for the stride task. Between-task variations generally showed a moderate correlation between ranking of participants for PL (0.593-0.764) and PL · min^-1 (0.282-0.736). It was concluded that monitoring PL^® in football multidirectional actions presents moderate-to-high reliability, that between-participant variability most likely relies on the individual's locomotive skills and not their anthropometrics, and that the intensity of a task expressed by PL · min^-1 is largely related to the running velocity of the task.