Article

Investigation of the convergent validity and reliability of unit position differences of Catapult S5 GPS units in field conditions

Authors:
To read the full-text of this research, you can request a copy directly from the authors.

Abstract

This research aimed to examine the validity and reliability of GPS units located in different positions. Nine recreational soccer players (age: 23.18 6 2.21 years; height: 176 6 7.65 cm; and body mass: 71.13 6 4.67 kg) participated voluntarily in the current study. Athletes were tested through the team sports simulation cycle (TSSC) protocol. This protocol consisted of a total of 1200 m. Each lap consisted of a distance of 150 m, and the athletes were asked to perform eight laps. Two GPS units (OptimEye S5; Catapult Innovations, Scoresby, Victoria) were used for each athlete during the TSSC protocol. The first unit was positioned in the scapula location, and the other GPS unit was positioned in the center of mass (COM) location, and simultaneous data were recorded. A paired-samples t-test was used to determine the difference between the meter values measured in the field and the devices. The main finding of this research was that the player load parameters, which are derived from the accelerometer in GPS units, changes with the player's position (total player load scapula 2 total player Load COM p4 0.001, Cohen'd 22.449). There was no statistical difference between the other parameters (total distance covered, max velocity, deceleration max and acceleration max) examined in the study. CV% and SWC values showing the reliability of total distance covered scapula (CV% = 1.41; SWC = 0.28), total distance covered COM (CV% = 3.64; SWC = 0.73), total player load scapula (CV% = 2.29; SWC = 0.46), total player load COM (CV% = 1.83; SWC = 0.37), deceleration max scapula (CV% = 3.51; SWC = 0.70), deceleration max COM (CV% = 2.78; SWC = 0.56), Acceleration max scapula (CV% = 3.85; SWC = 0.77), and acceleration max COM (CV% = 2.74; SWC = 0.55) were within acceptable limits (CV% 5). The reliability of GPS units in different locations was investigated by CV% SWC analysis. It was found that all values in the scapula and COM locations were measured validly and reliably, but the total player load measurements were statistically different in the scapula and COM.

No full-text available

Request Full-text Paper PDF

To read the full-text of this research,
you can request a copy directly from the authors.

ResearchGate has not been able to resolve any citations for this publication.
Article
Full-text available
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 XX(X): 000-000, 2021-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.
Article
Full-text available
Aim: This systematic review aimed to evaluate various Global Navigation Satellite Systems (GNSS) receivers, based on the frequency applied, the number of satellites available, and the dilution of precision (DOP) presented to measure football player load control. Method: The systematic review followed the PRISMA recommendations. Four hundred and eighty-five articles were selected from two online databases (Scopus and ISI Web of Science) over five years, with 21 studies selected for this review. In these studies, the GNSS frequency ranged from 5 to 18 Hz, with 10 Hz as the most commonly used frequency. Results: Of the 21 selected studies, 20 presented the ideal horizontal dilution of precision (HDOP), and the number of satellites available varied from 5 to 20. There was no consensus on defining speed, acceleration, or deceleration zones. Conclusion: There was no uniformity in data collected from the devices. Most GNSS receivers do not adopt the international system of units (SI).
Article
Full-text available
Purpose: Research establishing relationships between measures of rowing technique and velocity is limited. In this study, measures of technique and their effect on rowing velocity were investigated. Methods: Ten male singles, eight female singles, three male pairs, and six female pairs participated. Data from each stroke for forty-seven 2,000 m races were collected using Peach PowerLine and OptimEye S5 GPS units. General linear mixed modeling established modifying effects on velocity of two within-crew SD of predictor variables for each boat class, with subsequent adjustment for power, and for power and stroke rate in separate analyses. Twenty-two predictor variables were analyzed, including measures of boat velocity, gate force, and gate angle. Results were interpreted using superiority and inferiority testing with a smallest important change in velocity of 0.3%. Results: Substantial relationships with velocity were found between most variables assessed before adjustment for power, and for power and stroke rate. Effect magnitudes were reduced for most variables after adjustment for power and further reduced after adjustment for stroke rate and power, with precision becoming inadequate in many effects. The greatest modifying effects were found for stroke rate, mean and peak force, and power output before adjustment, and for catch angle after adjustment for stroke rate and power. Substantial between-crew differences in effects were evident for most predictors in some boat classes before adjustment and in some predictors and some boat classes after adjustment for stroke rate and power. Conclusion: The results presented reveal variables associated with improvements in rowing performance and can be used to guide technical analysis and feedback by practitioners. Higher stroke rates and greater catch angles should be targeted to improve rowing performance, and rower force development for the improvement of power output. Relationships between rowing technique and velocity can be crew-dependent and are best assessed on an individual basis for some variables.
Article
Full-text available
The purpose of the present study is to analyze the agreement between different sampling frequencies (SF) to quantify the accelerometer-load in soccer. Eight under-16 male soccer players were registered during an in-season training session. Each player wore four inertial measurement units that registered the accelerometer workload index PlayerLoad RT at different sampling frequencies: (a) 10 Hz, (b) 100 Hz, (c) 500 Hz, and (d) 1000 Hz. Additionally, a down-sampling method was performed: (e) 1000 to 100 Hz and (f) 500 to 100 Hz for comparison purposes. Agreement and correlation analysis were determined using the Pearson correlation coefficient, intraclass correlation, Bland-Altman bias, and t-student of independent samples with Cohen's d effect size. Very large to nearly perfect correlations were found between all SF (r. 0.704). An almost perfect agreement was found between all SF (ICC. 0.864), except regular to substantial agreement between 10 Hz and the rest of the sampling frequencies (ICC = 0.357-0.658). Comparison analysis showed statistical differences between all sampling frequencies (p \ 0.01) with the highest differences between 10 Hz and all other sampling frequencies. If trying to compare data collected at different frequencies, researchers should explain their rationale for the chosen sampling frequency to provide greater context for the reader. Accelerometers with greater than 100 Hz frequency should be used to provide more robust data regarding the dynamics in soccer. Based on the goals of the research, a sampling frequency can be selected to register suitable accelerometry-based data.
Article
Full-text available
Curvilinear locomotion is important for team sports performance and requires data collection and monitoring of centripetal forces. Currently, the centripetal force can be measured by different sensors that compose inertial devices, but its accuracy needs to be assessed. Therefore, this research aimed to analyze the accuracy and inter-unit reliability of both global positioning (GPS)-based and ultra-wideband (UWB)-based systems for practical application in the field. Following institutional ethical approval and familiarization, 10 elite-level male soccer players performed six circuits on four tracks (6-m radius circle, 9.15-m radius circle, 12-m radius circle, and combined track locomotion) in both directions (three counterclockwise and three clockwise) and were monitored by two tracking systems (GPS and UWB). The direct measurement was compared with the theoretical centripetal force calculated by photocells and spatial references. The UWB technology showed better accuracy (clockwise, bias =21.34 N; counterclockwise , bias = 1.09 N) than the GPS (clockwise, bias = 22.19 N; counterclockwise , bias = 1.75 N) in centripetal force measurements. However, both tracking technologies obtained very large to nearly perfect reliability results (GPS: ICC = 0.76-0.96; UWB: ICC = 0.76-0.98). In conclusion, even though both technologies proved to be reliable and data could be compared between units, the UWB-based system demonstrated better accuracy than the GPS-based system to detect centripetal force during curvilinear locomotion.
Article
Full-text available
The purpose of this 2-part commentary series is to explain why we believe our ability to control injury risk by manipulating training load (TL) in its current state is an illusion and why the foundations of this illusion are weak and unreliable. In part 1, we introduce the training process framework and contextualize the role of TL monitoring in the injury-prevention paradigm. In part 2, we describe the conceptual and methodologic pitfalls of previous authors who associated TL and injury in ways that limited their suitability for the derivation of practical recommendations. The first important step in the training process is developing the training program: the practitioner develops a strategy based on available evidence, professional knowledge, and experience. For decades, exercise strategies have been based on the fundamental training principles of overload and progression. Training-load monitoring allows the practitioner to determine whether athletes have completed training as planned and how they have coped with the physical stress. Training load and its associated metrics cannot provide a quantitative indication of whether particular load progressions will increase or decrease the injury risk, given the nature of previous studies (descriptive and at best predictive) and their methodologic weaknesses. The overreliance on TL has moved the attention away from the multifactorial nature of injury and the roles of other important contextual factors. We argue that no evidence supports the quantitative use of TL data to manipulate future training with the purpose of preventing injury. Therefore, determining “how much is too much” and how to properly manipulate and progress TL are currently subjective decisions based on generic training principles and our experience of adjusting training according to an individual athlete's response. Our message to practitioners is to stop seeking overly simplistic solutions to complex problems and instead embrace the risks and uncertainty inherent in the training process and injury prevention.
Article
Full-text available
The aims of this study were 1) to analyse session-to-session variations in different external load measures and 2) to examine differences in within-session intervals across different small-sided game (SSG) formats in professional players. Twenty professional soccer players (mean ± SD; age 28.1 ± 4.6 years, height 176.7 ± 4.9 cm, body mass 72.0 ± 7.8 kg, and body fat 10.3 ± 3.8%) participated in 3v3, 4v4, and 6v6 SSGs under different conditions (i.e., touch limitations and presence of goalkeepers vs. free touch and ball possession drill) over three sessions. Selected external load measures—including total distance (TD), high- intensity running (HIR, distance covered > 14.4 km.h-1), high-speed running (HSR, distance covered > 19.8 km.h-1), and mechanical work (MW, accelerations and deceleration > 2.2 m.s2)—were recorded using GPS technology during all SSG sessions. Small to large standardized typical errors were observed in session-to-session variations of selected measures across SSGs. TD.min-1 showed less variability, having a coefficient of variation (CV) of 2.2 to 4.6%, while all other selected external load measures had CV values ranging from 7.2% to 29.4%. Trivial differences were observed between intervals in TD.min-1 and HIR.min-1 for all SSGs, as well as in HSR.min-1 and MW.min-1 for most SSG formats. No reductions or incremental trends in session-to-session variations were observed when employing touch limitations or adding goalkeepers. The increased noise observed in higher speed zones (e.g., high-speed running) suggests a need for more controlled, running-based conditional drills if the aim is greater consistency in these measures.
Article
Full-text available
The use of valid, accurate and reliable systems is decisive for ensuring the data collection and correct interpretation of the values. Several studies have reviewed these aspects on the measurement of movement patterns by high-definition cameras (VID) and Global Positioning Systems (GPS) but not by Local Positioning Systems (LPS). Thus, the aim of the review was to summarize the evidence about the validity and reliability of LPS technology to measure movement patterns at human level in outdoor and indoor stadium-scale. The authors systematically searched three electronic databases (PubMed, Web of Science and SPORTDiscus) to extract studies published before October 21, 2019. A Boolean search phrase was created to include sport (population; 8 keywords), search terms relevant to intervention technology (intervention technology; 6 keywords) and measure outcomes of the technology (outcomes; 7 keywords). From the 62 articles found, 16 were included in the qualitative synthesis. This systematic review revealed that the tested LPS systems proved to be valid and accurate in determining the position and estimating distances and speeds, although they were not valid or their accuracy decreased when measuring instantaneous speed, peak accelerations or decelerations or monitoring particular conditions (e.g., changes of direction, turns). Considering the variability levels, the included studies showed that LPS provide a reliable way to measure distance variables and athletes' average speed.
Article
Full-text available
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 work-load 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: PlayerLoad TM 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.
Article
Full-text available
Player-worn devices, combining global positioning system and inertial monitors, are being used increasingly by professional sports teams. Recent interest focusses on using the data generated to track trainingload and whether this may lead to more effective training prescription with better management of injury risk. The aim of this review is to summarize the development and current use of this technology alongside proposed future applications. PubMed and Medline searches (2000-2017) identified all relevant studies involving use in team sports or comparative studies with other accepted methods. Our review determined that the latest devices are valid and reliably track activity levels. This technology is both accurate and more efficient than previous methods. Furthermore, recent research has shown that measurable changes in trainingload (the acute-to-chronic load ratio) are related to injury risk. However, results remain very sport specific and generalization must be done with caution. Future uses may include injury-prevention strategies and return-to-play judgement.
Article
Full-text available
Electronic performance and tracking systems (EPTS) and microelectromechanical systems (MEMS) allow the measurement of training load (TL) and collective behavior in team sports so that match performance can be optimized. Despite the frequent use of radio-frequency (RF) technology (i.e., global positioning navigation systems (GNSS/global positioning systems (GPS)) and, local position systems (LPS)) and MEMS in sports research, there is no protocol that must be followed, nor are there any set guidelines for evaluating the quality of the data collection process in studies. Thus, this study aims to suggest a survey based on previously used protocols to evaluate the quality of data recorded by RF technology and MEMS in team sports. A quality check sheet was proposed considering 13 general criteria items. Four additional items for GNSS/GPS, eight additional items for LPS, and five items for MEMS were suggested. This information for evaluating the quality of the data collection process should be reported in the methods sections of future studies.
Article
Full-text available
We present a critical reflection on the mechanical variable Player Load, which is based on acceleration data and commonly used in sports. Our motivation to write this paper came from the difficulties that we encountered in the calculation and interpretation of Player Load using our own data, since we did not use the Catapult Sports equipment, which is a merchandise of the company that proposed this variable. We reviewed existing literature in order to understand Player Load better; we found many inconsistencies in PL calculation methods and in the meanings attached to it. Accordingly, this paper presents a brief discussion on the meanings that have been assigned to Player Load, its limitations, and the lack of clear and complete information about Player Load calculation methods. Moreover, the use of arbitrary units and different practical meanings in the literature has associated Player Load with many physical quantities, thereby resulting in difficulties in determining what Player Load measures within the context of sports. It seems that Player Load is related to the magnitude of changes in acceleration, but not the magnitude of acceleration itself. Therefore, coaches and sports scientists should take this information into account when they use Player Load to prescribe and monitor external loads. We concluded that a deeper discussion of Player Load as a descriptor of external load is warranted in the sports sciences literature.
Article
Full-text available
This study aimed to examine the interchangeability of two external training load (ETL) monitoring methods: arbitrary vs. individualized speed zones. Thirteen male outfield players from a professional soccer team were monitored during training sessions using 10-Hz GPS units over an 8-week competitive period (n = 302 observations). Low-speed activities (LSA), moderate-speed running (MSR), high-speed running (HSR) and sprinting were defined using arbitrary speed zones as <14.4, 14.4-19.8, 19.8-25.1 and ≥25.2 km•h-1 , and using individualized speed zones based on a combination of maximal aerobic speed (MAS, derived from the Yo-yo Intermittent recovery test level 1), maximal sprinting speed (MSS, derived from the maximal speed reached during training) and anaerobic speed reserve (ASR) as <80% MAS, 80-100% MAS, 100% MAS or 29% ASR and ≥30% ASR. Distance covered in both arbitrary and individualized methods was almost certainly correlated in all speed zones (p < 0.01; r = 0.67-0.78). However, significant differences between methods were observed in all speed zones (p < 0.01). LSA was almost certainly higher when using the arbitrary method than when using the individualized method (p < 0.01; ES = 5.47 [5.18; 5.76], respectively). Conversely, MSR, HSR and sprinting speed were higher in the individualized method than in the arbitrary method (p < 0.01; ES = 5.10 [4.82; 5.37], 0.86 [0.72; 1.00] and 1.22 [1.08; 1.37], respectively). Arbitrary and individualized methods for ETL quantification based on speed zones showed similar sensitivity in depicting player locomotor demands. However, since these methods significantly differ at absolute level (based on measurement bias), arbitrary and individualized speed zones should not be used interchangeably.
Article
Full-text available
Traditionally, linear transducers have been used to evaluate resistance exercise with linear displacement. The current problem is the assessment of exercises with curvilinear displacement. For this reason, new devices should be assessed during training sessions. The purpose was to evaluate (1) the concurrent validity of mean linear velocity and (2) the convergent validity of mean angular velocity measured by an inertial device during a leg extension exercise. Ten elite-level football players completed six series of five repetitions of a leg extension exercise. WIMU PRO™ inertial device and GymAware ® linear transducers as criterion measure were used to register data. To assess concurrent validity, the bias of the inertial device measures of velocity was analyzed with Bland–Altman plots with limits of agreement set at 95%. Convergent validity of inertial device measures of velocity was assessed with Pearson’s correlation analysis. Concurrent analysis showed a nearly perfect validity between linear transducers and inertial device in linear ( Bias = –0.011 ± 0.006) and angular velocity (–0.34 ± 2.08). A nearly perfect Pearson’s product–moment correlation coefficient between an inertial device and linear transducers in linear velocity ( r = 0.999) and between an inertial device and linear transducers (calculated) in angular velocity ( r = 0.999) was found. In conclusion, WIMU PRO is valid for measuring linear and angular velocity during two-dimensional linear and rotational motions of exercise equipment. This device can be used as a useful tool to assess movement velocity in resistance training exercises, even in curvilinear movements when linear transducers have obvious limitations.
Article
Full-text available
ABSTRACT Gómez-Carmona, CD, Bastida-Castillo, A, González-Custodio, A, Olcina, G, and Pino-Ortega, J. Using an inertial device (WIMU PRO) to quantify neuromuscular load in running: reliability, convergent validity, and influence of type of surface and device location. J Strength Cond Res XX(X): 000–000, 2019—Currently, the use of accelerometers in sport is increasing, and thus, the devices are required to be valid and reliable. This study tested (a) the reliability and validity of WIMU PRO accelerometers to measure PlayerLoad (PL) and (b) the influence of speed, inertial device location, and type of surface where the incremental test is performed. Twenty resistance-trained men (age: 27.32 ± 6.65 years; height: 1.74 ± 0.03 m; body mass: 68.96 ± 4.37 kg; and body mass index: 22.76 ± 1.11 kg·m−2) volunteered to participate in the study that lasted 5 weeks. Four progressive incremental tests were performed in treadmill and athletic track conditions. External load variable (PL) and physiological variables (heart rate [HR] and SmO2) were recorded by 4 WIMU PRO inertial devices (scapulae, center of mass, knee, and ankle), a GARMIN HR band, and a MOXY near-infrared spectroscopy device, respectively. High reliability was found on both types of surface, showing the best values at the ankle (treadmill: intraclass correlation coefficient [ICC] = 0.99, coefficient of variation [CV] = 4.65%; track: ICC = 0.96, CV = 6.54%). A nearly perfect convergent validity was shown with HRAVG (r = 0.99) and a moderate one with SmO2 (r = −0.69). Significant differences in the PL variable between surfaces were reported in all locations except the scapulae (p = 0.173), and the higher values were found on the track. In the analysis per location, the ankle location reported the highest values at all speeds and on the 2 surfaces analyzed. Assessment needs to be individualized, due to the great variability of gait biomechanics among subjects. The accelerometer location should be chosen according to the purpose of the measurement, with the ankle location being recommended for neuromuscular load analysis in running.
Article
Full-text available
This study aimed at determining the reliability and concurrent validity of the WIMU ® system when measuring barbell velocity during the half-squat exercise by comparing data with the gold standard. A total of 19 male competitive powerlifters performed an incremental loading test using the half-squat exercise. The mean velocity, mean propulsive velocity and maximum velocity of all repetitions were recorded through both WIMU and T-Force systems. As a measure of reliability, coefficient of variations ranged from 6%–17% and standard error of means ranged from 0.02–0.11 m/s, showing very close reliability of data from both devices. Validity, in terms of coefficient of correlations and pairwise comparisons, was also tested. Except for some relative loads, the Pearson correlation analysis revealed significant correlations between both devices for mean velocity, mean propulsive velocity and maximum velocity (r > 0.6, p < 0.05). The mean velocity, mean propulsive velocity and maximum velocity were underestimated for the WIMU system compared to T-Force data at some points of the load–velocity relationship. The linear regression models performed revealed a strong load–velocity relationship in the half-squat exercise for each individual using mean velocity, mean propulsive velocity and maximum velocity, regardless of the instrument used (R ² > 0.77 in all cases). Bland–Altman plots revealed low systematic bias (≤0.06 m s ⁻¹ ) and random error (≤0.07 m s ⁻¹ ) for the mean velocity and mean propulsive velocity obtained from the WIMU system as compared to the T-Force, while the maximum velocity resulted in an underestimation by the WIMU system (–0.16 m s ⁻¹ ) as compared to the linear position transducer system. The results indicate that the WIMU system is a reliable tool for tracking barbell velocity in the half squat, but these data also reveal some limitations regarding its concurrent validity as compared to the gold standard, with velocity measures slightly underestimated in the tested conditions.
Article
Full-text available
Balloch, AS, Meghji, M, Newton, RU, Hart, NH, Weber, JA, Ahmad, I, and Habibi, D. Assessment of a novel algorithm to determine change-of-direction angles while running using inertial sensors. J Strength Cond Res XX(X): 000-000, 2019-The ability to detect and quantify change-of-direction (COD) movement may offer a unique approach to load-monitoring practice. Validity and reliability of a novel algorithm to calculate COD angles for predetermined COD movements ranging from 45 to 1808 in left and right directions was assessed. Five recreationally active men (age: 29.0 6 0.5 years; height: 181.0 6 5.6 cm; and body mass: 79.4 6 5.3 kg) ran 5 consecutive predetermined COD trials each, at 4 different angles (45, 90, 135, and 1808), in each direction. Participants were fitted with a commercially available microtechnol-ogy unit where inertial sensor data were extracted and processed using a novel algorithm designed to calculate precise COD angles for direct comparison with a high-speed video (remotely piloted , position-locked aircraft) criterion measure. Validity was assessed using Bland-Altman 95% limits of agreement and mean bias. Reliability was assessed using typical error (expressed as a coefficient of variation [CV]). Concurrent validity was present for most angles. Left: (458 = 43.8 6 2.08; 908 = 88.1 6 2.08; 1358 = 136.3 6 2.18; and 1808 = 181.8 6 2.58) and Right: (458 = 46.3 6 1.68; 908 = 91.9 6 2.28; 1358 = 133.4 6 2.08; 1808 = 179.2 6 5.98). All angles displayed excellent reliability (CV , 5%) while greater mean bias (3.6 6 5.18, p , 0.001), weaker limits of agreement, and reduced precision were evident for 1808 trials when compared with all other angles. High-level accuracy and reliability when detecting COD angles further advocates the use of inertial sensors to quantify sports-specific movement patterns.
Article
Full-text available
The purpose of this study was to (1) provide data on maximal sprinting speed (MSS) and maximal acceleration (Amax) in elite rugby sevens players measured with GPS devices, (2) test the concurrent validity of the signal derived from a radar device and a commercially available 16 Hz GPS device, and (2) assess the between-device reliability of MSS and Amax of the same GPS. Fifteen elite rugby sevens players (90 ± 12 kg; 181 ± 8 cm; 26 ± 5 y) participated in the maximal sprinting test. A subset of five players participated in the concurrent validity and between-devices reliability study. A concurrent validity protocol compared the GPS units and a radar device (Stalker ATS II). The between-device reliability of the GPS signal during maximal sprint running was also assessed using 6 V2 GPS units (Sensoreverywhere, Digital Simulation, Paris, France) attached to a custom-made steel sled and pushed by the five athletes who performed a combined total of 15 linear 40m sprints. CV ranged from 0.5, ±0.1 % for MSS and smoothed MSS to 6.4, ±1.1 % for Amax. TEM was trivial for MSS and smoothed MSS (0.09, ±0.01) and small for Amax and smoothed Amax (0.54, ±0.09 and 0.39, ±0.06 respectively). Mean bias ranged from -1.6, ±1.0 % to -3.0, ±1.1 % for smoothed MSS and MSS respectively. TEE were small (2.0, ±0.55 to 1.6, ±0.4 %, for MSS and smoothed MSS respectively. The main results indicate that the GPS units were highly reliable for assessing MSS and provided acceptable signal to noise ratio for measuring Amax, especially when a smoothing 0.5-s moving average is used. This 16 Hz GPS device provides sport scientists and coaches with an accurate and reliable means to monitor running performance in elite rugby sevens.
Article
Full-text available
Advances in global navigation satellite system (GNSS) technology have resulted in smaller and more accurate GNSS receivers, which have become increasingly suitable for calculating instantaneous performance parameters during sports competitions, for example by providing the difference in time between athletes at any location along a course. This study investigated the accuracy of three commercially available GNSS receivers directed at the sports market and evaluated their applicability for time analysis in endurance racing sports. The receivers evaluated were a 1 Hz wrist-worn standalone receiver (Garmin Forerunner 920XT, Gar-920XT), a 10 Hz standalone receiver (Catapult Optimeye S5, Cat-S5), and a 10 Hz differential receiver (ZXY-Go). They were validated against a geodetic, multi-frequency receiver providing differential position solutions (accuracy < 5 cm). Six volunteers skied four laps on a 3.05 km track prepared for cross-country skiing, with all four GNSS receivers measuring simultaneously. Deviations in position (horizontal plane, vertical, direction of travel) and speed (horizontal plane and direction of travel) were calculated. In addition, the positions of all receivers were mapped onto a mapping trajectory along the ski track, and a time analysis of all 276 possible pairs of laps was performed. Specifically, the time difference between any two skiers for each integer meter along the track was calculated. ZXY-Go, CAT-S5, and GAR-920XT had horizontal plane position errors of 2.09, 1.04, and 5.29 m (third quartile, Q3), and vertical precision 2.71, 3.89, and 13.35 m (interquartile range, IQR), respectively. The precision in the horizontal plane speed was 0.038, 0.072, and 0.66 m s-1 (IQR) and the time analysis precision was 0.30, 0.13, and 0.68 s (IQR) for ZXY-Go, Cat-S5, and Gar-920XT, respectively. However, the error was inversely related to skiing speed, implying that for the low speeds typically attained during uphill skiing, substantially larger errors can occur. Specifically, at 2.0 m s-1 the Q3 was 0.96, 0.36, and 1.90 s for ZXY-Go, Cat-S5, and Gar-920XT, respectively. In summary, the differential (ZXY-Go) and 10 Hz standalone (Cat-S5) receivers performed substantially better than the wrist-worn receiver (Gar-920XT) in terms of horizontal position and horizontal speed calculations. However, all receivers produced sub-second accuracy in the time analysis, except at very low skiing speeds.
Article
Full-text available
This study compared the outputs of three different commercially-available GPS player-tracking devices for a range of commonly used displacement and energetic variables in activities replicating team sport movements. Professional male soccer players (n = 7), simultaneously wore three GPS devices (Catapult OptimEye S5, GPExe Pro 1, StatSport ViperPod) whilst completing four separate drills, comprising progressively more complex changes in speed and direction. Displacement (distance, speed) and energetic (energy cost, metabolic power, energy expenditure) variables were compared for each device. All three devices tended to under-estimate distance compared to the known value for each drill, with only minor and inconsistent differences between devices. There were no differences between devices for average speed. For energetic variables, substantial differences were found between each device, and these differences magnified as movement tasks became more erratic. Given that energetic variables are derived from measures of instantaneous speed, and also incorporate the magnitude and direction of change between successive data points, these differences may be attributable to disparities in raw data quality, filtering techniques and calculation methods. In order to provide comparable estimates of energetic variables in team sports, player-tracking devices must be capable of accurately recording instantaneous velocity in activities comprising frequent changes in speed and direction.
Article
Full-text available
Purpose: To establish the inter-unit reliability of a range of Global Positioning System (GPS)-derived movement indicators, determine the variation between manufacturers, and investigate the difference between software-derived and raw data. Methods: A range of movement variables were obtained from 27 GPS units from three manufacturers (GPSports EVO; 10 Hz, n = 10: STATSports Apex; 10 Hz, n = 10: and Catapult S5; 10 Hz, n = 7) that measured the same team-sports simulation session while positioned on a sled. The inter-unit reliability was determined using the coefficient of variation (CV; %) and 90% confidence limits (CL), whereas between manufacturer comparisons, and also comparisons of software versus raw processed data were established using standardized effect sizes (ES) and 90% CL. Results: The inter-unit reliability for both software and raw processed data ranged from good to poor (CV = 0.2%; ±1.5% to 78.2%; ±1.5%), with distance, speed, and maximal speed exhibiting the best reliability. There were substantial differences between manufacturers, particularly for threshold-based acceleration and deceleration variables (ES; ±90% CL [-2.0%; ±0.1 to 1.9%; ±0.1%]), and there were substantial differences between data processing methods for a range of movement indicators. Conclusions: The inter-unit reliability of most movement indicators were deemed as good regardless of processing method, suggesting that practitioners can have confidence within systems. Standardized data processing methods are recommended, due to the large differences between data outputs from various manufacturer-derived software.
Article
Full-text available
The increasing interest in assessing physical demands in team sports has led to the development of multiple sports related monitoring systems. Due to technical limitations, these systems primarily could be applied to outdoor sports, whereas an equivalent indoor locomotion analysis is not established yet. Technological development of inertial measurement units (IMU) broadens the possibilities for player monitoring and enables the quantification of locomotor movements in indoor environments. The aim of the current study was to validate an IMU measuring by determining average and peak human acceleration under indoor conditions in team sport specific movements. Data of a single wearable tracking device including an IMU (Optimeye S5, Catapult Sports, Melbourne, Australia) were compared to the results of a 3D motion analysis (MA) system (Vicon Motion Systems, Oxford, UK) during selected standardized movement simulations in an indoor laboratory (n = 56). A low-pass filtering method for gravity correction (LF) and two sensor fusion algorithms for orientation estimation [Complementary Filter (CF), Kalman-Filter (KF)] were implemented and compared with MA system data. Significant differences (p < 0.05) were found between LF and MA data but not between sensor fusion algorithms and MA. Higher precision and lower relative errors were found for CF (RMSE = 0.05; CV = 2.6%) and KF (RMSE = 0.15; CV = 3.8%) both compared to the LF method (RMSE = 1.14; CV = 47.6%) regarding the magnitude of the resulting vector and strongly emphasize the implementation of orientation estimation to accurately describe human acceleration. Comparing both sensor fusion algorithms, CF revealed slightly lower errors than KF and additionally provided valuable information about positive and negative acceleration values in all three movement planes with moderate to good validity (CV = 3.9-17.8%). Compared to x-and y-axis superior results were found for the z-axis. These findings demonstrate that IMU-based wearable tracking devices can Roell et al. Inertial Sensors for Player Monitoring successfully be applied for athlete monitoring in indoor team sports and provide potential to accurately quantify accelerations and decelerations in all three orthogonal axes with acceptable validity. An increase in accuracy taking magnetometers in account should be specifically pursued by future research.
Article
Full-text available
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.
Article
Full-text available
The purpose of this study was to investigate the validity of global positioning system (GPS) and micro-electrical-mechanical-system (MEMS) data generated in real-time via a dedicated receiver. Post-session data acted as criterion as it is used to plan the volume and intensity of future training and is downloaded directly from the device. 25 professional rugby league players completed two training sessions wearing a MEMS device (Catapult S5, firmware version: 2.27). During sessions, real-time data was collected via the manufacturer receiver and dedicated software (Openfield v1.14) which was positioned outdoors at the same location for every session. GPS variables included total-, low- (0 to 3 m∙s-1), moderate- (3.1 to 5 m∙s-1), high- (5.1 to 7 m∙s-1) and very-high-speed (> 7.1 m∙s-1) distances. MEMS data included total session PlayerLoad™. When compared to post-session data, mean bias for total-, low-, moderate-, high- and very-high-speed distances were all trivial, with the typical error of the estimate (TEE) small, small, trivial, trivial and small respectively. Pearson correlation coefficients for total-, low-, moderate-, high- and very-high-speed distances were nearly perfect, nearly perfect, perfect, perfect and nearly perfect respectively. For PlayerLoad™, mean bias was trivial whilst TEE was moderate and correlation nearly perfect. Practitioners should be confident that when interpreting real-time speed-derived metrics, the data generated in real-time is comparable to that downloaded directly from the device post-session. However, practitioners should refrain from interpreting accelerometer derived data (i.e. PlayerLoad™) or acknowledge the moderate error associated with this real-time measure.
Article
Full-text available
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.
Article
Full-text available
Objectives: Collision frequency during rugby league matches is associated with team success, greater and longer lasting fatigue and increased injury risk. This study researched the sensitivity and specificity of microtechnology to count collision events during rugby league matches. Design: Diagnostic accuracy study. Methods: While wearing a microtechnology device (Catapult, S5), eight professional rugby league players were subjected to a total of 380 collision events during matches. Video footage of each match was synchronised with microtechnology data. The occurrence of each collision event was coded in comparison with whether that event was or was not detected by microtechnology. Results: Microtechnology detected 371 true-positive collision events (sensitivity=97.6±1.5%). When low-intensity (<1 PlayerLoad AU), short duration (<1s) events were excluded from the analysis, specificity was 91.7±2.5%, accuracy was 92.7±1.3%, positive likelihood ratio was 11.4×/÷1.4 and the typical error of estimate was 7.8%×/÷1.9 (d=0.29×/÷1.9, small). Microtechnology collisions were strongly and positively correlated with video coded collision events (r=0.96). The ability of microtechnology to detect collision events improved as the intensity and duration of the collision increased. Conclusions: Microtechnology can identify 97.6% of collision events during rugby league match-play. The typical error associated with measuring contact events can be reduced to 7.8%, with accuracy (92.7%) and specificity (91.7%) improving, when low-intensity (<1 PlayerLoad AU) and short duration (<1s) collision reports are excluded. This provides practitioners with a measurement of contact workload during professional rugby league matches.
Article
Full-text available
Purpose: Sprints and accelerations are popular performance indicators in applied sport. The methods used to define these efforts using athlete-tracking technology could affect the number of efforts reported. This study aimed to determine the influence of different techniques and settings for detecting high-intensity efforts using global positioning system (GPS) data. Methods: Velocity and acceleration data from a professional soccer match were recorded via 10-Hz GPS. Velocity data were filtered using either a median or an exponential filter. Acceleration data were derived from velocity data over a 0.2-s time interval (with and without an exponential filter applied) and a 0.3-second time interval. High-speed-running (≥4.17 m/s2), sprint (≥7.00 m/s2), and acceleration (≥2.78 m/s2) efforts were then identified using minimum-effort durations (0.1-0.9 s) to assess differences in the total number of efforts reported. Results: Different velocity-filtering methods resulted in small to moderate differences (effect size [ES] 0.28-1.09) in the number of high-speed-running and sprint efforts detected when minimum duration was <0.5 s and small to very large differences (ES -5.69 to 0.26) in the number of accelerations when minimum duration was <0.7 s. There was an exponential decline in the number of all efforts as minimum duration increased, regardless of filtering method, with the largest declines in acceleration efforts. Conclusions: Filtering techniques and minimum durations substantially affect the number of high-speed-running, sprint, and acceleration efforts detected with GPS. Changes to how high-intensity efforts are defined affect reported data. Therefore, consistency in data processing is advised.
Article
Full-text available
Athlete tracking devices that include global positioning system (GPS) and micro electrical mechanical system (MEMS) components are now commonplace in sport research and practice. These devices provide large amounts of data that are used to inform decision-making on athlete training and performance. However, the data obtained from these devices are often provided without clear explanation of how these metrics are obtained. At present, there is no clear consensus regarding how these data should be handled and reported in a sport context. Therefore, the aim of this review was to examine the factors that affect the data produced by these athlete tracking devices to provide guidelines for collecting, processing, and reporting of data. Many factors including device sampling rate, positioning and fitting of devices, satellite signal and data filtering methods can affect the measures obtained from GPS and MEMS devices. Therefore researchers are encouraged to report device brand/model, sampling frequency, number of satellites, horizontal dilution of precision (HDOP) and software/firmware versions in any published research. Additionally, details of data inclusion/exclusion criteria for data obtained from these devices are also recommended. Considerations for the application of speed zones to evaluate the magnitude and distribution of different locomotor activities recorded by GPS are also presented, alongside recommendations for both industry practice and future research directions. Through a standard approach to data collection and procedure reporting, researchers and practitioners will be able to make more confident comparisons from their data, which will improve the understanding and impact these devices can have on athlete performance.
Article
Full-text available
Purpose: The purpose of this study was to investigate the validity of timing gates and 10 Hz GPS units (Catapult Optimeye S5) against a criterion measure (50 Hz radar gun) for assessing maximum sprint velocity (Vmax). Methods: Nine male professional rugby union players performed three maximal 40 m sprints with three minutes rest between each effort with Vmax assessed simultaneously via timing gates, 10 Hz GPSOpen (Openfield software), GPSSprint (Sprint software) and radar gun. Eight players wore 3 GPS units, while one player wore a single unit during each sprint. Results: When compared to the radar gun, mean bias for GPSOpen, GPSSprint and timing gates was trivial, small and small respectively. The typical error of the estimate (TEE) was small for timing gate and GPSOpen, while moderate for GPSSprint. Correlations with radar gun were nearly perfect for all measures. Mean bias, TEE and correlations between GPS units were trivial, small and nearly perfect respectively, while small TEE existed when GPSOpenfield was compared to GPSSprint. Conclusions: Based on these findings both 10 Hz GPS and timing gates provide valid measures of 40 m Vmax assessment when compared with a radar gun. However, as error did exist between measures, the same testing protocol should be used when assessing 40 m Vmax over time. Furthermore, in light of the above results, it is recommended that when assessing changes in GPS derived Vmax over time, practitioners should use the same unit for each player and perform the analysis with the same software, preferably Catapult Openfield.
Article
Full-text available
Purpose: The aim of this study was to quantify and predict relationships between RPE and GPS training load variables in professional Australian Football (AF) players using group and individualised modelling approaches. Methods: Training load data (GPS and RPE) for 41 professional AF players was obtained over a period of 27 weeks. A total of 2711 training observations were analysed with a total of 66 ±13 sessions per player (range; 39 to 89). Separate generalised estimating equations (GEE) and artificial neural network analyses (ANN) were conducted to determine the ability to predict RPE from training load variables (i.e. session distance, high-speed running (HSR), high-speed running %, m·min-1) on a group and individual basis. Results: Prediction error for the individualised ANN (root mean square error [RMSE]; 1.24 ±0.41) was lower than the group ANN (RMSE; 1.42 ±0.44), individualised GEE (RMSE; 1.58 ±0.41) and group GEE (RMSE; 1.85 ±0.49). Both the GEE and ANN models determined session distance as the most important predictor of RPE. Further, importance plots generated from the ANN revealed session distance was most predictive of RPE in 36 of the 41 players, whereas, HSR was predictive of RPE in just 3 players and m·min-1 as predictive as session distance in just 2 players. Conclusions: This study demonstrates that machine learning approaches may outperform more traditional methodologies with respect to predicting athlete responses to training load. These approaches enable further individualisation of load monitoring, leading to more accurate training prescription and evaluation.
Article
Full-text available
The knowledge about physical demands in different sports has increased, thanks to the application of global positioning system devices. The reliability and validity of 10 Hz global positioning system devices have been assessed by some authors. The majority of the studies only addressed the reliability of the devices or, in other words, the ability of scores of global positioning system device to differentiate among subjects or objects. The reliability is based on correlations (such as the intraclass correlation coefficient) which do not give the researcher information that can be interpreted in a practical way. In this way, the aim of this study was to assess the grade of agreement among repeated measurements made on the same subject using two global positioning system devices simultaneously. Four trained male tennis players participated in the study. The participants completed tennis-simulated point-games (n = 32), each player wearing two devices at the same time. Global indicators, such as Player Load (PL), Exertion Index (EI) and Equivalent Distance Index (EDI) per minute, were monitored through the use of global positioning system devices (MinimaxX v4.0; Catapult Innovations, Melbourne, Australia) operating at the above-mentioned sampling frequency of 10 Hz. The systematic error is that there is tendency of the global positioning system devices to measure systematically different from others Vmean (−1.03 m · min−1), Vpeak (−10.31 m · min−1), Equivalent Distance Index (0.63 ratio), PLmin (0.35 UA min−1) and EImin (−0.01) variables. As for random error (limit of agreement), we would expect that in PLmin, the global positioning systems would differ in 95% of the cases between 2.12 and −1.42 m · min−1; any value out of the limits of agreement would result relevant for the practical point of view. We concluded that the global positioning system devices produce systematically different results from one another; therefore, the bias from one global positioning system to another should be subtracted to compare the results between the global positioning systems.
Article
The aims of this study were to (i) analyze within-group (starters and non-starters) for the weekly acute (wAW), chronic (wCW), and acute:chronic workload ratio (wACWR) throughout the pre-, early-, mid-, and end-season periods, and (ii) analyze the within-group differences for the weekly total distance (wTD), sprint total distance (wSTD), high-speed running distance (wHSRd), and repeated sprint (wRS) throughout the soccer season. The study included a professional soccer team that participated in the highest level of the Iranian Persian Gulf Pro League during a full season. A Global Positioning System was used for data collection during the study. Results revealed significant differences between season periods for wAW and wACWR for both starters (wAW: p = 0.003, h P 2 = 0.541; wACWR: p \ 0.001, h P 2 = 0.964) and non-starters (wAW: p \ 0.001, h P 2 = 0.696; wACWR: p \ 0.001, h P 2 = 0.943). Only non-starters had meaningful differences for wCW (p = 0.009, h P 2 = 0.408). There were significant differences in wTD and wSTD for both starters (wTD: p \ 0.001, h P 2 = 0.810; wSTD: p = 0.014, h P 2 = 0.457) and non-starters (wTD: p \ 0.001, h P 2 = 0.895; wSTD: p \ 0.001, h P 2 = 0.781). Only non-starters showed significant differences (p \ 0.001, h P 2 = 0.722) for wRS, while both groups showed no significant differences for wHSRd. In conclusion, these results revealed that both groups experienced significant differences in wAW, wACWR, wTD, and wSTD, while non-starters presented significant differences in wCW and wRS. Coaches should consider these group differences when planning training sessions. Exposure to wSTD and wRS should be addressed for non-starters, as well as fatigue monitoring for starters, especially for players with full match participation.
Article
Quantifying the external training load across the season related to the starting status of players could be relevant for physical conditioning staff, since one of the main goals is to apply the adequate individual training load. Thus, the aims of this study were to (1) monitor the acute workload (wAW), chronic workload (wCW), and acute/chronic workload ratio (wACWR) on a weekly basis using the body load (BL) in starter and non-starter professional soccer players; and (2) analyze the differences between starters and non-starters for wAW, wCW, and wACWR using BL, and (3) analyze the weekly average of distance and sprint variables during four periods of the season (pre-, early-, mid-, and end-season). Twenty-one professional soccer players (28.3 6 3.8 years; 181.2 6 7.0 cm; 74.4 6 7.7 kg) belonging to the same team competing in the Iranian Persian Gulf Pro League were evaluated for a period of 48 weeks (one soccer season). The season was divided into pre-season (weeks 1-5), early-season (weeks 6-19), mid-season (weeks 20-35), and end-season (weeks 36-48). Players were classified according to their starting status: players who were in the starting line-up (i.e. starters) and players who did not make the starting line-up (i.e. non-starters). The results showed greater weekly wAW and wCW for starters compared to non-starters during the mid-season (wAW: p = 0.008, g = 21.24; wCW: p = 0.006; g = 21.31) and end-season (wAW: p = 0.001, g = 21.66; wCW: p = 0.001; g = 21.62). Starters also showed greater weekly total distance (wTD), sprint total distance (wSTD), high-speed running distance (wHSRd), and repeated sprints compared with non-starters across all four periods (p \ 0.05; g = 21.36 to 24.95), higher wHSRd/wTD during pre-season (p = 0.007, g = 21.28) and mid-season (p = 0.001, g = 21.62) and a greater wSTD/wTD during pre-season (p = 0.029, g = 20.99). Based on these findings, coaches and strength and conditioning specialists should individualize training according to match exposure throughout a competitive season.
Article
Given the accuracy in data collection, radar-based local positioning systems (LPS) are a promising technology to monitor training load in team sports. The objective of this study was to systematically review articles that compare the validity and reliability of LPS to other electronic performance and tracking system (EPTS) in team sports. The authors searched three electronic databases (SPORTDiscus, PubMed, and Web of Science) to identify relevant studies published by October 21, 2019. A Boolean search was performed, including sport (population), search terms related to intervention technology (inter-vention technology), and outcome measures of the technology (outcomes). Seven studies evaluated the validity and reliability of LPS in team sports in comparison with other EPTS, including semi-automatic video technology (VID) and Global Positioning System (GPS). Two articles compared LPS to VID, three articles compared LPS to GPS, and two articles compared LPS to both GPS and VID. LPS is considered a valid and reliable EPTS in the field of load monitoring of team sports, usually resulting in higher accuracy than VID or GPS. However, special care should be taken when analyzing load indicators at high speeds or different trajectories, since the validity and reliability depend on the EPTS itself.
Article
This study aimed to analyze the intersession reliability of global positioning system (GPS-based) distances and accelerometer-based (acceleration) variables in small-sided soccer games (SSG) with and without the offside rule, as well as compare variables between the tasks. Twenty-four high-level U-17 soccer athletes played 3 versus 3 (plus goalkeepers) SSG in two formats (with and without the offside rule). SSG were performed on eight consecutive weeks (4weeks for each group), twice a week. The physical demands were recorded using a GPS with an embedded triaxial accelerometer. GPS-based variables (total distance, average speed, and distances covered at different speeds) and accelerometer-based variables (Player Load�, root mean square of the acceleration recorded in each movement axis, and the root mean square of resultant acceleration) were calculated. Results showed that the inclusion of the offside rule reduced the total distance covered (large effect) and the distances covered at moderate speed zones (7–12.9 km/h – moderate effect; 13– 17.9 km/h – large effect). In both SSG formats, GPS-based variables presented good to excellent reliability (intraclass correlation coefficients – ICC . 0.62) and accelerometer-based variables presented excellent reliability (ICC values . 0.89). Based on the results of this study, the offside rule decreases the physical demand of 3 versus 3 SSG and the physical demands required in these SSG present high intersession reliability.
Article
Chest bands have been the most used device to monitor heart rate during running. However, some runners feel uncomfortable with the use of bands due to the friction and pressure exerted on the chest. Thus, the aim of this study was to determine if the photoplethysmography (PPG) system Polar Precision Prime used in the Polar Vantage M watch could replace chest bands (Polar V800-H10) to monitor heart rate with the same precision. A group of 37 people, middle-distance and long-distance professional runners, participated in this study. The submaximal speed was determined using 50% of the participants' maximum speed in the height of their season. The Polar Vantage M reported high correlation (r. 0.84) and high ICC (ICC. 0.86) when comparing its heart rate monitor with the Polar V800 synchronised with H10 chest strap during recording intervals of more than 2 min. The systematic bias and random error were very small (\ 1 bpm), especially for the 600 s recording interval (0.26 6 5.10 bpm). Nevertheless, the error increased for 10 s (25.13 6 9.20 bpm), 20 s (28.65 6 12.60 bpm) and 30 s (210.71 6 14.99 bpm) time intervals. In conclusion, the PPG Polar Precision Prime included in the Polar Vantage M demonstrates that it could be a valid alternative to chest bands for monitoring heart rate while running, taking into account some usage considerations, good strap adjustment and an initial calibration time during the first 2-3 min.
Article
The aim of this study was to compare the weekly average training monotony new body load (wTMNBL) and strain (wTSNBL), as well as the weekly average training monotony metabolic power average (wTMMPA) and strain (wTSMPA) between four periods of a season (preseason, early-season, mid-season, and end-season), considering starters and non-starters. Twenty-one professional soccer players (age: 28.27 ± 3.78 years) were monitored throughout a season in the highest level of professional football Premier League in Iran. Data were captured by Global Positioning System (GPS) devices. Independent samples T-tests were applied to analyze the between-group differences for all dependent derived-GPS variables for the full season and its different periods (preseason, early-season, mid-season, and end-season). Based on the amount of time attending in match and training, players were divided into two groups (starters and non-starters) each week. The magnitude of the between-group difference revealed a very large significant greater weekly average TMNBL (p<0.001, d = −2.42), TSNBL (p<0.001; d = −2.74), TMMPA (p<0.001; d =–2.79) and TSMPA (p<0.001; d = −3.27) for starters when compared to non-starters during the early-season. The findings also revealed a very large significant difference when starters were compared to non-starters during the mid-season (TMNBL: p<0.001, d = −2.89; TSNBL: p<0.001, d = −2.99; TMMPA: p<0.001, d = −3.28; and TSMPA: p<0.001, d = −3.25) and end-season (TMNBL: p<0.001, d = −2.89; TSNBL: p<0.001, d = −3.07; TMMPA: p<0.001, d = −3.16; and TSMPA: p<0.001, d = −3.58). In summary, the results of this study revealed that starters present regularly higher values of NBL, MPA-based weekly training monotony, and training strain than non-starters. This result must be taken into account when planning weekly workloads for these groups. Specifically, starters might experience high values of external workloads because of match-related demands. Therefore, weekly adjustments in their training workload are required to reduce injury risk.
Article
This study aimed to investigate the accuracy and reliability of Polar Team Pro GPS units (10 Hz) when used to measure distance and total distance covered in different speed zones. Eight amateur soccer players (age: 21.37 6 1.40 years, height: 176.75 6 5 cm, body mass: 176.75 6 9.47 kg) completed a team sport simulation cycle. Two Polar Team Pro GPS units were positioned on each player's chest, and one GPSports GPS unit (15 Hz) was positioned between the scapulae. The data obtained from the two Polar Team Pro GPS units were compared to determine inter-unit reliability. The data obtained from one of the Polar Team Pro GPS units and the GPSports GPS unit (reference standard) were compared to determine concurrent accuracy. There was acceptable inter-unit reliability of Polar Team Pro GPS units for total distance (TD), low speed running (LSR) (0.00-13.99 km h 21), high speed running (HSR) (14.00-19.99 km h 21) and very high speed running (VHSR) (. 20.0 km h 21) with high ICCs (0.63, 0.99, 0.99 and 0.99, respectively), and low typical error of measurement (%) (TEM%) (4.64, 5.05, 1.06 and 2.89, respectively). Regarding accuracy, the ICCs were extremely high for LSR and HSR (0.99 and 0.92, respectively), but high for TD and VHSR (0.63 and 0.65, respectively). Moreover, TEM (%) values were very low for TD and LSR (0.6 and 1.6, respectively), but they were high for HSR and VHSR (13.8 and 13.1, respectively). Consequently, acceptable inter-unit reliability was observed, indicating that the Polar Team Pro GPS unit is suitable for tracking pertinent team-sport variables. Moreover, the Polar Team Pro GPS units (10 Hz) are accurate under the same conditions. However, the research showed that the two systems cannot be used interchangeably for quantifying distances covered at higher speeds.
Article
Whereas 3D optical motion capture (OMC) systems are considered the gold standard for kinematic assessment in sport science, they present some drawbacks that limit its use in the field. Inertial measurement units (IMUs) incorporating gyroscopes have been considered as a more practical alternative. Thus, the aim of the study was to evaluate the level of agreement for angular velocity between IMU gyroscopes and an OMC system for varying tennis strokes and intensities. In total, 240 signals of angular velocity from different body segments and types of strokes (forehand, backhand and service) were recorded from four players (two competition players and two beginners). The angular velocity of the IMU gyroscopes was compared to the angular velocity from the OMC system. Level of agreement was evaluated by correlation coefficients, magnitudes of errors in absolute and relative values and Bland-Altman plots. Differences between both systems were highly consistent within players’ skill (i.e., along the broad range of velocities) and axes (x, y, z). Correlations ranged from 0.951 to 0.993, indicating a very strong relationship and concordance. The magnitude of the differences ranged from 4.4 to 35.4 deg·s-1. The difference relative to the maximum angular velocity achieved was less than 5.0%. The study concluded that IMUs and OMC systems showed comparable values. Thus, IMUs seem to be a valid alternative to detect meaningful differences in angular velocity during tennis groundstrokes in field-based experimentation.
Article
The noncontact and soft-tissue injuries to lower extremities that occur as a result of excessive running loads are largely preventable. This study investigated the relationship between global positioning system variables and noncontact soft-tissue injuries in female field hockey players based on their position on the field. Fifty-two players enrolled in the Korea National Team were monitored using global positioning system units in game-based training and competitions. The measurements obtained were total distance covered, high-intensity running distance, work–rest ratio, meters per minute, repeated high-intensity effort bouts, maximal velocity, and acceleration and deceleration bouts. Noncontact soft-tissue injuries in lower extremities were documented throughout the same period. For measuring the absolute external workload of each global positioning system variable, players’ data were averaged for 1- and 4-week periods before they were injured (injury-related block), averaging values across 1 and 4 weeks before the injury-related block (non-injury block), as well as averaging values from the beginning of the data collection to the point of injury (total average). These blocks were compared to each other and to the corresponding total averages for the 1- and 4-week periods, depending on their position on the field. Of the 52 players, 28 players (8 forwards, 11 midfielders, and 9 defenders) injured their lower extremities for a total of 38 injuries. Of these injuries, 11 occurred in forwards, 17 occurred in midfielders, and 10 occurred in defenders with some players experiencing more than one injury. Different positions on the field have different global positioning system variables related to the occurrence of noncontact soft-tissue injuries in lower extremities, but there was a significant difference in global positioning system variable of injury-related block for only the 4-week period among their position on the field. Especially, increases in high-intensity running distance and repeated high-intensity effort bouts of defenders during the 4-week period were significantly related to the occurrence of injuries. To decrease the risk of injury in female field hockey players, different global positioning system variables should be monitored and modified in planned future training or competitions.
Article
The main aim of this work was to review the use of technological tracking methods to assess collective spatial-positioning variables in team sports. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and PICO design for systematic reviews, study identification was performed in four databases (PubMed, SPORTDiscus, ProQuest Central, and Web of Science). Articles were selected if they focused on player position and technological tracking methods. After duplicate removal, 2194 articles were identified based on the established search criteria, of which 72 articles were selected and analysed. Semi-automatic optic-based systems, Global Positioning System/Global Navigation Satellite Systems, and local positioning systems were used in 60%, 33% and 7% of the studies, respectively. All studies that measured tactical variables by local positioning system technology in team sports used local position measurement technology. Optic-based systems were used more often in the early years to analyse collective tactical behaviour during competition. Later, Global Positioning System/Global Navigation Satellite Systems became more frequent to measure behaviour in team sports during the training process. The possibility of using the same system during competition and training will facilitate the assessment of collective tactical behaviour in team sports.
Article
The aim of the study was to examine the perceptions of training data feedback from key stakeholders within the coaching process of professional soccer clubs. A survey assessed the importance of training data towards reflection and decision-making, potential barriers and player preferences. 176 participants comprising coaches, players and performance staff completed the survey. The training data coaches most commonly identified as wanting to see to support reflection was ‘high-intensity’ actions and variables recognised by the coach as ‘work rate/intensity’. All stakeholders reported training data as at least somewhat important in guiding their coaches’ practices, with lack of a common goal and high volumes of information being the main barriers to effective feedback of training data. Players deemed feedback as positive to changing their behaviour, with total distance, high-speed running and sprint distances as the information they would most like to see. It would be likely to be looked at via message or pinned up in the changing room. Training data is seen as an impactful and effective tool for use by all key stakeholders. Despite this, its use can be optimised by increasing opportunities for informal reflection, using less information, and improving communication of data.
Article
Kyprianou, E, Di Salvo, V, Lolli, L, Al Haddad, H, Villanueva, AM, Gregson, W, and Weston, M. To measure peak velocity in soccer, let the players sprint. J Strength Cond Res XX(X): 000-000, 2019-Expressing externals loads relative to a player's individual capacities has potential to enhance understanding of dose-response. Peak velocity is an important metric for the individualization process and is usually measured during a sprint test. Recently, however, peak velocity was reported to be faster during soccer matches when compared with a 40-m sprint test. With the aim of developing the practice of individualized training prescription and match evaluation, we examined whether the aforementioned finding replicates in a group of elite youth soccer players across a broader range of soccer activities. To do this, we compared the peak velocities of 12 full-time male youth soccer players (age 16.3 ± 0.8 years) recorded during a 40-m sprint test with peak velocity recorded during their routine activities (matches, sprints, and skill-based conditioning drills: small-sided games [SSG], medium-sided games [MSG], large-sided games [LSG]). All activities were monitored with 10-Hz global positioning systems (Catapult Optimeye S5, version 7.32) with the highest speed attained during each activity retained as the instantaneous peak velocity. Interpretation of clear between-activity differences in peak velocity was based on nonoverlap of the 95% confidence intervals for the mean difference between activities with sprint testing. Peak velocity was clearly faster for the sprint test (8.76 ± 0.39 m·s) when compared with matches (7.94 ± 0.49 m·s), LSG (6.94 ± 0.65 m·s), MSG (6.40 ± 0.75 m·s), and SSG (5.25 ± 0.92 m·s), but not sprints (8.50 ± 0.36 m·s). Our data show the necessity for 40-m sprint testing to determine peak velocity.
Article
This study aimed to examine the concurrent validity of inertial measurement unit–based knee flexion strength-power test variables. Ten physically active males performed a knee flexion strength-power test, consisting of serial right knee flexion-extension motions. Two trials were performed, each at 50%, 75% and 100% effort. Lower-extremity motion during the trial was recorded using a motion capture system and an inertial measurement unit. For inertial measurement unit data, the measured length of each lower-extremity segment was used to estimate segment endpoint coordinates. Knee flexion kinetic variables were then computed using inverse dynamics analysis for both systems. The inertial measurement unit provided comparable values with the motion capture system for angular impulse, mean moment, positive work and mean power (−0.8%, 1.0%, −0.9%, and 1.5%, respectively). Moreover, intraclass correlation coefficients and correlation coefficients for angular impulse, mean moment, positive work and mean power of knee flexion were acceptably high (ICC or r = 0.903–0.970). For positive mean power, however, a Bland–Altman plot showed heteroscedasticity. For knee flexion negative work and mean power, the inertial measurement unit clearly showed an overestimation of the values (32.5% and 23.5%, respectively). Moreover, the intraclass correlation coefficients and correlation coefficients were not acceptably high for knee flexion negative work and mean power (ICC or r = 0.541–0.899). These results indicate that the angular impulse, mean moment and positive work can be measured accurately and validly using an inertial measurement unit for knee flexion strength-power test variables. Given its simplicity, the suggested inertial measurement unit–based knee flexion strength-power test would improve on-the-field physical fitness evaluation.
Article
Electronic performance and tracking systems (EPTS) traditionally rely on one of two body positions as the ultimate representative for the entire body in space: the upper torso between the scapulae (GPS- and radar-based systems) or the body's estimated center (optical and some radar-based systems). The aim of this study was to quantify the impact of the respective reference point upon the resulting kinematic tracking variables. We present a marker-based method comparing center of pelvis (COP) derived tracking variables with center of scapulae (COS) derived tracking variables in a 30 × 30 m (900 m²) VICON measurement area. Fourteen male soccer players completed a running circuit with prescribed team-sport specific movements. Results showed that differences between COP and COS heavily depend on the underlying movement characteristic. Low-speed running showed the lowest deviations whereas accelerated movements and movements with sharp changes in direction lead to a significant increase in the observed differences. Results further showed that COS sprinting distance was on average −44.65% (p < 0.001) lower in comparison to COP. Similarly, maximum speed obtained from COS was −2.94% (p = 0.001) lower in comparison to COP. On the contrary, maximum acceleration values of COS were on average 16.15% (p = 0.02) higher compared to COP. Our work illustrates that the anatomical reference point used to represent the entire body in space needs to be carefully considered in the interpretation of tracking variables delivered by different EPTS.
Article
IN SOCCER, GLOBAL POSITIONING SYSTEM (GPS) MONITORING OF PLAYER WORKLOADS IS NOW EXTENSIVELY USED ACROSS ALL LEVELS OF THE SPORT. TO MAKE BETTER USE OF THIS TECHNOLOGY IT IS IMPORTANT TO APPRECIATE HOW IT WORKS. FURTHER, WHEN THE LIMITATIONS OF GPS USE ARE APPRECIATED AND THE RATIONALE OF USE IS AGREED AND ARTICULATED, THEN THE POTENTIAL OF GPS MONITORING CAN BE EFFECTIVELY REALIZED TO BETTER MANAGE PLAYERS' PERFORMANCE, WORKLOAD AND WELFARE. (SEE VIDEO, SUPPLEMENTARY DIGITAL CONTENT, NUMBER 1, WHICH SUMMARIZES GPS USE, LIMITATIONS, AND POTENTIAL IN SOCCER, HTTP:// LINKS.LWW.COM/SCJ/A238).
Article
This study had two main goals. The first was to determine the reliability of the Wimu® system (accelerometer) for mean velocity measurements during resistance exercises at 40% and 80% 1 repetition maximum (1RM). The second was to compare the results for the Wimu system to a linear encoder (gold standard) for mean velocity measurements when clipped to the bar during back squat exercises using the Smith machine. In all, 23 trained men (aged 22.3 ± 3.2 years) participated in this study. At maximum velocity in the concentric phase, they performed 10 repetitions with 40% 1RM and eight repetitions with 80% 1RM while using the Wimu system and T-Force linear encoder simultaneously to record data. Reliability was analysed using intraclass correlation, standard error of measurement and coefficient of variation. The validity was assessed using R², intraclass correlation and Bland-Altman plots. The differences in test–retest reliability of both systems and systematic biases were non-significant (p = 0.08–0.85) and very close to 0. The random errors averaged ±0.010 m/s. All the calculated coefficient of variations were less than 5% and all measurements had high intraclass correlations (mean: 0.936). Least-square linear regression and intraclass correlations for validity were very close to 1. Significant systematic biases were observed between the linear encoder and the Wimu system (p < 0.001), although the effect sizes were small (0.21–0.44) and standard error of the estimate in concentric and eccentric phases at both intensities was less than 0.030. In conclusion, the findings of this study suggest that the Wimu system is a reliable and valid tool for the assessment of mean velocity during the back squat exercise using the Smith machine. These findings could help coaches and sport researchers evaluate athletes performing resistance exercises similar to squats with a reliable, valid and portable tool.
Article
Purpose: The purpose of this study was to assess the reliability and sensitivity of commercially available inertial measurement units (IMU) to measure physical activity in team handball. Method: Twenty-two handball players were instrumented with two IMUs (OptimEye S5, Catapult Sports, Australia) taped together. They participated in either a laboratory assessment (n=10), consisting of seven team handball specific tasks, or field assessment (n=12) conducted in twelve training sessions. Variables, including PlayerLoad™ and inertial movement analysis (IMA) magnitude and counts, were extracted from the manufactures software. IMA count was divided into intensity bands of low (1.5-2.5m·s(-1)), medium (2.5-3.5m·s(-1)), high (>3.5m·s(-1)), medium/high (>2.5m·s(-1)), and total (>1.5m·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 count (CV: 1.8%, SWD: 2.5%), PlayerLoad™ (CV: 0.9 % SWD: 2.1%), and its 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 count were good, when data was displayed as total, high or medium/high counts. A good reliability for PlayerLoad™ and associated variables was evident. The CV of the aforementioned variables was well below the SWD, suggesting that OptimEye IMU and its software are sensitive for use in team handball.
Article
Purpose: The principle aim of the study was to assess the validity of measuring locomotor activities and PlayerLoad using Real-Time (RT) data collection during soccer training. Methods: Twenty-nine (n=29) English soccer players participated. Each player wore the same MEMS device (S5, Optimeye, CatapultSports, Melbourne, Australia) during twenty-one training sessions (n= 331 data sets) in the 2015/2016 and 2016/2017 season. A Real-Time receiver (TRX, Catapultsports, Melbourne, Australia) was used to collect the locomotor activities and PlayerLoad data in RT and compared with the post-event downloaded (PED) data. PlayerLoad and locomotor activities (total distance covered, TDC; total high speed running distance covered, >5.5m/s, HSR; total sprinting distance covered, >7m/s, SP; maximum velocity, VEL) were analysed. Results: Correlations were near perfect for all variables analysed (r=0.98-1.00), with a varied level of noise between RT and PED also (0.3-9.7% CV). Conclusions: Locomotor activities and PlayerLoad can be used both RT and PED concurrently to quantify a players physical output during a training session. Caution should be taken with higher velocity based locomotor activities during RT compared to PED.
Article
Wearable microsensor technology incorporating triaxial accelerometry is used to quantify an index of mechanical stress associated with sport-specific movements termed PlayerLoad™. The test-retest reliability of PlayerLoad™ in the environmental-setting of ice-hockey is unknown. The primary aim of this study was to quantify the test-retest reliability of PlayerLoad™ in ice-hockey players during performance of tasks simulating game-conditions. Division I collegiate male ice-hockey players (N=8) wore Catapult Optimeye S5 monitors during repeat performance of 9 ice-hockey tasks simulating game-conditions. Ordered ice-hockey tasks during repeated bouts included: acceleration (forward/backward), 60% top-speed, top-speed (forward/backward), repeated shift circuit, ice-coasting, slap-shot, and bench-sitting. Coefficient of variation (CV), intraclass correlation coefficient (ICC), and minimum differences (MD) were used to assess PlayerLoad™ reliability. Test-retest CVs and ICCs of PlayerLoad™ were: Forward (8.6, 0.54) or backward (13.8, 0.78) acceleration, 60% top-speed (2.2, 0.96), forward (7.5, 0.79) or backwards (2.8, 0.96) top-speed, repeated-shift test (26.6, 0.95), slap-shot (3.9, 0.68), coasting (3.7, 0.98), and bench-sitting (4.1, 0.98), respectively. Raw differences between bouts were not significant for ice-hockey tasks (P>0.05). For each task, between bout raw differences were lower versus MD: Forward (0.06 vs. 0.35) or backward (0.07 vs. 0.36) acceleration, 60% top-speed (0.00 vs. 0.06), forward (0.03 vs. 0.20) or backwards (0.02 vs. 0.09) top-speed, repeated-shift test (0.18 vs. 0.64), slap-shot (0.02 vs. 0.10), coasting (0.00 vs. 0.10), and bench-sitting (0.01 vs. 0.11), respectively. These data suggest PlayerLoad™ demonstrates moderate-to-large test-retest reliability in the environmental-setting of male Division I collegiate ice-hockey. Without previously testing reliability, these data are important as PlayerLoad™ is routinely quantified in male collegiate ice-hockey to assess on ice physical activity.