Accuracy and Reliability of Local Positioning Systems for Measuring Sport Movement Patterns in Stadium-Scale: A Systematic Review

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

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

Validity and reliability of an eight antennae ultra-wideband local positioning system to measure performance in an indoor environment

Validity and reliability have become crucial factors in tracking player load and positioning. One of the most important parameters to guarantee accurate measurements with radiofrequency systems is the number of reference nodes used to calculate player position. However, the accuracy of ultra-wideband (UWB) technology has only been analysed with 6 antennae. So, the purpose of the present study was to analyse the accuracy and inter-unit reliability of an UWB system with eight antennae. Three well-trained males covered 18 trajectories for the analysis of x- and y- coordinate accuracy assessment related to the positional variation among eight antennae UWB data and lines on a basketball court. This was achieved using geographical information system mapping software that calculated, for each interval and participant, the distance from the main axis of locomotion and the opposite side of the field every 0.5 s. The results showed that this is a valid system (Mean = 0.03 m; magnitude differences = 0.21% with real measures as reference; %CV <1% in all cases) for measuring locomotion and positioning. Besides, the inter-unit, test-retest and inter-subject analysis did not influence the reliability results. So, an eight antennae UWB system can be considered suitable for locomotion and positioning in an indoor environment.

Examination of the ZXY Arena Tracking System for Association Football Pitches

Modern analyses of football games require precise recordings of positions and movements. The ZXY arena tracking system reports the position of players wearing a dedicated chip (transponder) at high time resolution. The main issue addressed here is the quality of the system's output data. Filtering the data to reduce noise may affect the outcome adversely. Therefore, we have examined the precision of the data given, possible influence by sources of noise, the effect of the filtering, and the accuracy of the built-in calculations. The system's reported positions of the transponders at rest and during different types of movements, including accelerations, were recorded and compared with the true positions, speeds, and accelerations. The reported position has a random error of ≈0.2 m, defining the system's upper spatial resolution. The error in signals interrupted by a human body was of that magnitude or less. There was no significant influence of nearby transponders. Filtering the data delayed the time resolution. Consequently, accelerations were dampened and delayed, causing an error of 1 m for sudden changes in position. Moreover, fluctuations of the foot speed of a running person were not accurately reproduced, but rather, averaged over time periods >1 s. Results calculated from measured values appeared accurate and were readily reproduced in a spreadsheet output. In conclusion, the ZXY system reports the position with little random error. Its main limitation is caused by averaging of the signals.

Peak Locomotor Intensity in Elite Handball Players: A First Insight Into Player Position Differences and Training Practices

ABSTRACT

Fleureau, A, Rabita, G, Leduc, C, Buchheit, M, and Lacome, M. Peak locomotor intensity in elite handball players: a first insight into player position differences and training practices. J Strength Cond Res 37(2): 432-438, 2023-The aims of the study were to (a) describe the peak locomotor intensity sustained during handball matches and (b) compare them with small-sided games (SSGs) programmed during training in elite handball players. Small-sided game ( n = 342) and match ( n = 121) data were collected among 11 players (25 ± 7 years, 191 ± 8 cm, 89 ± 12 kg) belonging to an elite French Handball team. Players' locomotor activity was recorded using 20-Hz Local Positioning System. Peak total (TD[m]) and high-speed running distance (HS[m]) and mechanical load (Accel'Rate [a.u.]) were calculated during different time periods (1-15 minutes different rolling averages). A plot of log (locomotor variables) against log (time) allowed to obtain a straight line with a slope and an intercept for each variable. Between-position differences during matches and difference between matches and SSGs were assessed with linear mixed model and magnitude-based decisions. Almost certainly higher peak locomotor intensity (intercept) was found in Wingers (TD: 156 ± 13; HS: 96 ± 12; Accel'Rate: 13 ± 3) compared with other playing positions for TD (Back players: 127 ± 10; Pivots: 136 ± 13), HS (Back players: 56 ± 9; Pivots: 57 ± 11), and Accel'Rate (Back players: 11 ± 2; Pivots: 11 ± 2). However, no clear between-position difference was found regarding the slope. Additionally, none of the SSGs format produced an overload in peak locomotor intensity in comparison with matches (TD: 138 ± 16; HS: 66 ± 20; Accel'Rate: 12 ± 2). Because reaching the peak locomotor intensity sustained during match is not possible using SSGs, practitioners should consider using isolated conditioning drills (e.g., short or long intervals, repeated sprints). Moreover, specific attention should be paid for Winger's work supplementation because they present the highest peak locomotor intensity in the team.

Accuracy of a local positioning system for time-series speed and acceleration and performance indicators in game sports

The objective was to determine the reliability and validity of a local positioning system (LPS) promising high accuracy at reduced product costs. Fifty-five random static positions in a gym (54.8  × 26.0 m) were obtained 10 times via LPS (50 Hz) and measuring tape. An athlete's LPS-derived peak and time-series speed and acceleration during dynamic movements (n = 80) were compared with Vicon (100 Hz). Reliability and validity were assessed via Intraclass and Concordance Correlation Coefficients (ICC/CCC), root mean square errors, Bland-Altman plots, and analysis of variance. ICC3,1 (≥0.999) and CCC (0.387-0.999) were calculated for static positions (errors <0.22 m). CCC for time-series speed and acceleration, and peak speed, acceleration, and deceleration were 0.884-0.902, 0.777-0.854, 0.923, 0.486, and 0.731, respectively. Errors were larger in time-series acceleration (14.37 ± 3.77%) than in speed (11.99 ± 5.78%) (η p 2  = 0.472, p < 0.001) and in peak acceleration (28.04 ± 14.34%) and deceleration (25.07 ± 14.90%) than in speed (7.34 ± 6.07%) (η p 2  = 0.091, p < 0.01). LPS achieved excellent reliability and moderate-to-excellent validity of time-series speed and acceleration. The system accurately measured peak speed but not peak acceleration and deceleration. The system is suitable for analyses based on instantaneous speed and acceleration in game sports (e.g., energy estimations).

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

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

External Load Analysis in Beach Handball Using a Local Positioning System and Inertial Measurement Units

Beach handball is a young discipline that is characterized by numerous high-intensity actions. By following up on previous work, the objective was to perform in-depth analyses evaluating external load (e.g., distance traveled, velocity, changes in direction, etc.) in beach handball players. In cross-sectional analyses, data of 69 players belonging to the German national or prospective team were analyzed during official tournaments using a local positioning system (10 Hz) and inertial measurement units (100 Hz). Statistical analyses comprised the comparison of the first and second set and the effects of age and sex (female adolescents vs. male adolescents vs. male adults) and playing position (goalkeepers, defenders, wings, specialists, and pivots) on external load measures. We found evidence for reduced external workload during the second set of the matches (p = 0.005, ηp2 = 0.09), as indicated by a significantly lower player load per minute and number of changes in direction. Age/sex (p < 0.001, ηp2 = 0.22) and playing position (p < 0.001, ηp2 = 0.29) also had significant effects on external load. The present data comprehensively describe and analyze important external load measures in a sample of high-performing beach handball players, providing valuable information to practitioners and coaches aiming at improving athletic performance in this new sport.

Impact and workload are dominating on-field data monitoring techniques to track health and well-being of team-sports athletes

Participation in sports has become an essential part of healthy living in today's world. However, injuries can often occur during sports participation. With advancements in sensor technology and data analytics, many sports have turned to technology-aided, data-driven, on-field monitoring techniques to help prevent injuries and plan better player management. This review searched three databases, Web of Science, IEEE, and PubMed, for peer-reviewed articles on on-field data monitoring techniques that are aimed at improving the health and well-being of team-sports athletes. It was found that most on-field data monitoring methods can be categorized as either player workload tracking or physical impact monitoring. Many studies covered during this review attempted to establish correlations between captured physical and physiological data, as well as injury risk. In these studies, workloads are frequently tracked to optimize training and prevent overtraining in addition to overuse injuries, while impacts are most often tracked to detect and investigate traumatic injuries. This review found that current sports monitoring practices often suffer from a lack of standard metrics and definitions. Furthermore, existing data-analysis models are created on data that are limited in both size and diversity. These issues need to be addressed to create ecologically valid approaches in the future.

Impact of Microcycle Structures on Physical and Technical Outcomes During Professional Rugby League Training and Matches

PURPOSE

To assess the impact of microcycle (MC) structures on physical and technical performances in rugby league training and matches.

METHODS

Thirty-four professional rugby league players were monitored during all training sessions and matches across a single season wherein 2 different competition-phase MC structures were implemented. The first MC structure involved the first session on match day (MD) + 2 and the main stimulus delivered MD - 3, and the second structure delayed all sessions by 1 day (first session on MD + 3 and main session MD - 2; MC structure in the second half of the season). Physical output was quantified via relative total speed (in meters per minute), high-speed running (per minute; ≥4.0 m·s-1), and very-high-speed running (per minute; ≥5.5 m·s-1), measured using a global positioning system (10 Hz) in addition to accelerometer (100 Hz) metrics (PlayerLoad per minute and PlayerLoadslow per minute]) during training and matches. Technical performance (number of runs, meters gained, tackles made and missed) was recorded during matches. Generalized linear mixed models and equivalence tests were used to identify the impact of MC structure on physical and technical output.

RESULTS

Nonequivalent increases in meters per minute, high-speed running per minute, and PlayerLoad per minute were observed for the first training stimulus in MC structure in the second half of the season with no practical difference in midcycle sessions observed. The MC structure in the second half of the season structure resulted in increased high-speed running per minute and decreased PlayerLoadslow per minute during MD with no differences observed in technical performance.

CONCLUSIONS

Delaying the first training stimulus of the MC allowed for greater training load accumulation without negative consequences in selected match running and technical performance measures. This increased MC load may support the maintenance of physical capacities across the in-season.

A new approach to quantify angles and time of changes-of-direction during soccer matches

BACKGROUND AND AIMS

Soccer players frequently perform change-of-directions (CODs) at various speeds during matches. However, tracking systems have shown limitations to measure these efforts. Therefore, the aim of the present study was to propose a new approach to measure CODs using a local positioning system (LPS), and clarify position-related difference in profile of CODs by using the approach.

METHODS

The x- and y-coordinate data for each soccer player were measured with a local positioning system. Speed, acceleration, jerk, and direction of speed were derived from the coordinate data. Based on accelerations of above 2 m/s2, the onsets and ends of CODs derived from jerk were identified (COD duration). Changes of direction of speed (θCOD) were determined for the corresponding period. Six collegiate male soccer players performed CODs according to 13 set angles (0-180°; every 15°) so that differences between θCOD and set angle could be determined (Exp. 1). Relative frequency distributions of θCOD and number of CODs were determined in 79 collegiate and amateur male soccer players during 9 soccer matches (Exp. 2).

RESULTS

In Exp. 1, θCOD was positively related to set angle (r = 0.99). Each θCOD was smaller than the corresponding set angle, and the difference became greater with increasing COD angle. In Exp. 2, The number of CODs in a match was 183 ± 39 across all positions. There were no significant position-related differences in the number of CODs. The duration of a COD was 0.89 ± 0.49 s across all positions. The relative frequency distribution of θCOD revealed that the number of CODs at 0-15° and 105-135° tended to be higher than those at other angles during soccer matches. Further, θCOD was affected by the speed at the onset of COD during soccer matches (Exp. 2).

CONCLUSIONS

The current findings demonstrate that θCOD derived from direction of speed and jerk may be a new indicator for evaluating COD during soccer matches.

Specific Absolute Velocity Thresholds during Male Basketball Games Using Local Positional System; Differences between Age Categories

The aim of this study was (I) to establish absolute specific velocity thresholds during basketball games using local positional system (LPS) and (II) to compare the speed profiles between various levels of competitions. The variables recorded were total distance (TD); meters per minute (m·min); real time (min); maximum speed (Km h−1), distance (m), percentage distance, and percentage duration invested in four speed zones (standing–walking; jogging; running; and high-speed running). Mean and standard deviation (±SD) were calculated, and a separate one-way analysis of variance was undertaken to identify differences between competitions. TD (3188.84 ± 808.37 m) is covered by standing–walking (43.51%), jogging (36.58%), running (14.68%), and sprinting (5.23%) activities. Overall, 75.22% of the time is invested standing–walking, jogging (18.43%), running (4.77%), and sprinting (1.89%). M·min (large effect size), % duration zone 2 (moderate effect size); distance zone 4 (large effect size), and % distance zone 4 (very large effect size) are significantly higher during junior than senior. However, % distance zone 1 (large effect size) and % duration zone 1 (large effect size) were largely higher during senior competition. The findings of this study reveal that most of the distance and play time is spent during walking and standing activities. In addition, the proportion of time spent at elevated intensities is higher during junior than in senior competition.

The Influence of Antenna Height on the Measurement of Collective Variables Using an Ultra-Wide Band Based Local Positioning System in Team Sports

Ultra-wide band (UWB) based local positioning systems (LPS) are based on devices and a portable antenna set. The optimal installation height of the antennae is crucial to ensure data accuracy. Collective variables are metrics that consider at least two pairs of coordinates, which may lead to lower precision than an individual one. Therefore, the aim of this study was to compare the influence of antenna height with collective metrics using a UWB (i.e., IMU; WIMU PRO™, RealTrack Systems, Almeria, Spain) based LPS. Data acquisition was carried out in a basketball court measuring 28 × 15 m. Five devices were used; one of which was carried by a healthy and well-trained athlete (age: 38 years, mass: 76.34 kg, height 1.70 m), while each of the remaining four was positioned on a tripod in one of the four corners of the court. Four kinds of variables were extracted: (1) static distances, (2) dynamic distances, (3) static areas and (4) dynamic areas in all antenna installation modes of 0.15, 1.30 and 2.00 m. The results showed that the antenna of 1.30 m provided better accuracy for all measures (% difference range from -0.94 to 1.17%) followed by the antenna of 2.00 m (% difference range from -2.50 to 2.15%), with the antenna of 0.15 m providing the worst accuracy level (% difference range from -1.05 to 3.28%). Overall, the measurements of distance metrics showed greater accuracy than area metrics (distance % difference range from -0.85 to 2.81% and area % difference range from -2.50 to 3.28). In conclusion, the height of the antennae in basketball courts should be similar to the height at which the devices are attached to a player's upper back. However, as the precision is sensitive to the magnitude of the measure, further studies should assess the effects of the relative height of antennae in team sports with greater playing spaces.

Validation of Player and Ball Tracking with a Local Positioning System

The aim of this study was the validation of player and ball position measurements of Kinexon's local positioning system (LPS) in handball and football. Eight athletes conducted a sport-specific course (SSC) and small sided football games (SSG), simultaneously tracked by the LPS and an infrared camera-based motion capture system as reference system. Furthermore, football shots and handball throws were performed to evaluate ball tracking. The position root mean square error (RMSE) for player tracking was 9 cm for SSCs, the instantaneous peak speed showed a percentage deviation from the reference system of 0.7-1.7% for different exercises. The RMSE for SSGs was 8 cm. Covered distance was overestimated by 0.6% in SSCs and 1.0% in SSGs. The 2D RMSE of ball tracking was 15 cm in SSGs, 3D position errors of shot and throw impact locations were 17 cm and 21 cm. The methodology for the validation of a system's accuracy in sports tracking requires extensive attention, especially in settings covering both, player and ball measurements. Most tracking errors for player tracking were smaller or in line with errors found for comparable systems in the literature. Ball tracking showed a larger error than player tracking. Here, the influence of the positioning of the sensor must be further reviewed. In total, the accuracy of Kinexon's LPS has proven to represent the current state of the art for player and ball position detection in team sports.

Validity of a Local Positioning System during Outdoor and Indoor Conditions for Team Sports

This study aimed to compare the validity of a local positioning system (LPS) during outdoor and indoor conditions for team sports. The impact of different filtering techniques was also investigated. Five male team sport athletes (age: 27 ± 2 years; maximum oxygen uptake: 48.4 ± 5.1 mL/min/kg) performed 10 trials on a team sport-specific circuit on an artificial turf and in a sports hall. During the circuit, athletes wore two devices of a recent 20-Hz LPS. From the reported raw and differently filtered velocity data, distances covered during different walking, jogging, and sprinting sections within the circuit were computed for which the circuit was equipped with double-light timing gates as criterion measures. The validity was determined by comparing the known and measured distances via the relative typical error of estimate (TEE). The LPS validity for measuring distances covered was good to moderate during both environments (TEE: 0.9–7.1%), whereby the outdoor validity (TEE: 0.9–6.4%) was superior than indoor validity (TEE: 1.2–7.1%). During both environments, validity outcomes of an unknown manufacturer filter were superior (TEE: 0.9–6.2%) compared to those of a standard Butterworth filter (TEE: 0.9–6.4%) and to unprocessed raw data (TEE: 1.0–7.1%). Our findings show that the evaluated LPS can be considered as a good to moderately valid tracking technology to assess running-based movement patterns in team sports during outdoor and indoor conditions. However, outdoor was superior to indoor validity, and also impacted by the applied filtering technique. Our outcomes should be considered for practical purposes like match and training analyses in team sport environments.