Investigating the Relevance of Maximal Speed and Acceleration in Varsity-Level Female Ice Hockey Players

PURPOSE

To characterize and compare female ice hockey players' peak skating speed and acceleration ability during linear sprints and gameplay. We also sought to quantify the time spent at various speeds and the frequency of accelerations at different thresholds during games.

METHODS

Seventeen varsity-level female ice hockey players (20 [1.4] y, 68.9 [4.9] kg, 167.6 [4.7] cm) participated in an on-ice practice session (performing 3 × 40-m linear sprints) and 4 regular-season games while being monitored using a local positioning system. Speed and acceleration were recorded from the sprint and within-game monitoring. Time on ice spent in relative skating speed zones and the frequency of accelerations at different intensities were recorded.

RESULTS

Players' greatest peak speeds (29.5 [1.3] vs 28.3 [1.1] km/h) and accelerations (4.39 [0.48] vs 3.34 [0.36] m/s2) reached during gameplay were higher than those reached in linear sprinting (both P < .01). Peak in-game values were moderately predicted by linear sprint values for speed (r = .69, P < .01) but not for acceleration (r < .01, P = .95). Players spent little time at near-peak linear sprint speeds (≥80% [22.7 km/h], ∼3% time on ice; ≥90% [25.5 km/h], <1% of time on ice) during gameplay. However, 26% to 35% of accelerations recorded during the 4 games were ≥90% of linear sprint acceleration.

CONCLUSIONS

Although skating speed may be advantageous in specific game situations, our results suggest that players spend little time at near-maximal speeds while accelerating frequently during games. This warrants further investigation of direction changes, skating transitions, repeated sprints, and other determinant variables potentially related to on-ice success and the implementation of training strategies to improve repeated acceleration or qualities beyond maximal skating speed.

Age-Related Reference Intervals for Physical Performance Test Outcomes Relevant to Male Youth Middle Eastern Football Players

PURPOSE

To develop age-specific reference intervals for physical performance test outcomes relevant to male youth Middle Eastern football players.

METHODS

We analyzed mixed-longitudinal data (observations range: 1751-1943 assessments) from a sample of 441 male youth outfield football players (chronological age range: 11.7-18.4 y) as part of the Qatar Football Association and Aspire Academy development program over 14 competitive seasons. Semiparametric generalized additive models for location, scale, and shape estimated age-specific reference centiles for 10-m sprinting, 40-m sprinting, countermovement jump height, and maximal aerobic speed variables.

RESULTS

The estimated reference intervals indicated that the distribution of the physical performance test scores increased monotonically and nonlinearly with advancing chronological age for sprinting and countermovement jump outcome measures, reaching a plateau after 16 years common to each of these performance variables. The maximal aerobic speed median score increased substantially until ∼14.5 years, with the nonlinear trend flattening off toward relatively older chronological ages.

CONCLUSIONS

We developed age-related reference intervals for physical performance test outcomes relevant to youth Qatari football players. Country-wide age-specific reference intervals can assist in the longitudinal tracking of the individual players' progress over time against benchmark values derived from the reference population.

Accumulated Workload Differences in Collegiate Women's Soccer: Starters versus Substitutes

The purpose of this study was to estimate the workloads accumulated by collegiate female soccer players during a competitive season and to compare the workloads of starters and substitutes. Data from 19 college soccer players (height: 1.58 ± 0.06 m; body mass: 61.57 ± 6.88 kg) were extracted from global positioning system (GPS)/heart rate (HR) monitoring sensors to quantify workload throughout the 2019 competitive season. Total distance, distance covered in four speed zones, accelerations, and time spent in five HR zones were examined as accumulated values for training sessions, matches, and the entire season. Repeated-measures ANOVA and Student's t tests were used to determine the level of differences between starter and substitute workloads. Seasonal accumulated total distance (p < 0.001), sprints (≥19.00 km/h; p < 0.001), and high-speed distance (≥15.00 km/h; p = 0.005) were significantly greater for starters than substitutes. Accumulated training load (p = 0.08) and training load per minute played in matches (p = 0.08) did not differ between starters and substitutes. Substitutes had similar accumulated workload profiles during training sessions but differed in matches from starters. Coaches and practitioners should pursue strategies to monitor the differences in workload between starters and substitutes.

A Query Language for Exploratory Analysis of Video-Based Tracking Data in Padel Matches

Recent advances in sensor technologies, in particular video-based human detection, object tracking and pose estimation, have opened new possibilities for the automatic or semi-automatic per-frame annotation of sport videos. In the case of racket sports such as tennis and padel, state-of-the-art deep learning methods allow the robust detection and tracking of the players from a single video, which can be combined with ball tracking and shot recognition techniques to obtain a precise description of the play state at every frame. These data, which might include the court-space position of the players, their speeds, accelerations, shots and ball trajectories, can be exported in tabular format for further analysis. Unfortunately, the limitations of traditional table-based methods for analyzing such sport data are twofold. On the one hand, these methods cannot represent complex spatio-temporal queries in a compact, readable way, usable by sport analysts. On the other hand, traditional data visualization tools often fail to convey all the information available in the video (such as the precise body motion before, during and after the execution of a shot) and resulting plots only show a small portion of the available data. In this paper we address these two limitations by focusing on the analysis of video-based tracking data of padel matches. In particular, we propose a domain-specific query language to facilitate coaches and sport analysts to write queries in a very compact form. Additionally, we enrich the data visualization plots by linking each data item to a specific segment of the video so that analysts have full access to all the details related to the query. We demonstrate the flexibility of our system by collecting and converting into readable queries multiple tips and hypotheses on padel strategies extracted from the literature.

Reference values for performance test outcomes relevant to English female soccer players

The purpose of this study was to present reference standards for physical performance test outcomes relevant to elite female soccer players. We analysed mixed-longitudinal data (n = 1715 observations) from a sample of 479 elite youth and senior players as part of the English Football Association's national development programme (age range: 12.7 to 36.0 years). Semi-parametric generalized additive models for location, scale and shape (GAMLSS) estimated age-related reference centiles for 5-m sprinting, 30-m sprinting, countermovement jump (CMJ) height, and Yo-Yo Intermittent Recovery Test Level 1 (Yo-Yo IR1) performance. The estimated reference centiles indicated that the median of the distribution of physical performance test scores varied non-linearly with advancing chronological age, improving until around 25 years for each performance variable. These are the first reference ranges for performance test outcomes in elite English female soccer players. These data can assist practitioners when interpreting physical test performance outcomes to track an individual's progress over time and support decision-making regarding player recruitment and development.

Estimating Player Positions from Padel High-Angle Videos: Accuracy Comparison of Recent Computer Vision Methods

The estimation of player positions is key for performance analysis in sport. In this paper, we focus on image-based, single-angle, player position estimation in padel. Unlike tennis, the primary camera view in professional padel videos follows a de facto standard, consisting of a high-angle shot at about 7.6 m above the court floor. This camera angle reduces the occlusion impact of the mesh that stands over the glass walls, and offers a convenient view for judging the depth of the ball and the player positions and poses. We evaluate and compare the accuracy of state-of-the-art computer vision methods on a large set of images from both amateur videos and publicly available videos from the major international padel circuit. The methods we analyze include object detection, image segmentation and pose estimation techniques, all of them based on deep convolutional neural networks. We report accuracy and average precision with respect to manually-annotated video frames. The best results are obtained by top-down pose estimation methods, which offer a detection rate of 99.8% and a RMSE below 5 and 12 cm for horizontal/vertical court-space coordinates (deviations from predicted and ground-truth player positions). These results demonstrate the suitability of pose estimation methods based on deep convolutional neural networks for estimating player positions from single-angle padel videos. Immediate applications of this work include the player and team analysis of the large collection of publicly available videos from international circuits, as well as an inexpensive method to get player positional data in amateur padel clubs.

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.

A New Foot-Mounted Inertial Measurement System in Soccer: Reliability and Comparison to Global Positioning Systems for Velocity Measurements During Team Sport Actions

The aims of this study were to i) compare a foot-mounted inertial system (PlayerMaker™) to three commercially available Global Positioning Systems (GPS) for measurement of velocity-based metrics during team sport movements and ii) evaluate the inter-unit reliability of the PlayerMaker™. Twelve soccer players completed a soccer simulation, whilst wearing a PlayerMaker™ and three GPS (GPS#1, #2 and #3). A sub-sample (n = 7) also wore two PlayerMaker™ systems concurrently. The PlayerMaker™ measured higher (p < 0.05) total distance (518 ± 15 m) compared to GPS#1 (488 ± 15 m), GPS#2 (486 ± 15 m), and GPS#3 (501 ± 14 m). This was explained by greater (p < 0.05) distances in the 1.5-3.5 m/s zone (356 ± 24 m vs. 326 ± 26 m vs. 324 ± 18 m vs. 335 ± 24 m) and the 3.51-5.5 m/s zone (64 ± 18 m vs. 35 ± 5 vs. 43 ± 8 m vs. 41 ± 8 m) between the PlayerMaker™, GPS#1, GPS#2 and GPS#3, respectively. The PlayerMaker™ recorded higher (p < 0.05) distances while changing speed. There were no systematic differences (p > 0.05) between the two PlayerMaker™ systems. The PlayerMaker™ is reliable and records higher velocity and distances compared to GPS.

Criterion Validity of Catapult ClearSky T6 Local Positioning System for Measuring Inter-Unit Distance

The validity of a local positioning system (LPS) to measure inter-unit distance was investigated during a team sport movement circuit. Eight recreationally active, female indoor team-sport players completed a circuit, comprising seven types of movements (walk, jog, jump, sprint, 45° change of direction and shuffle), on an indoor court. Participants wore a receiver tag (ClearSky T6, Catapult Sports) and seven reflective markers, to allow for a comparison with the reference system (©Vicon Motion Systems, Oxford Metrics, UK). Inter-unit distance was collected for each combination of participants. Validity was assessed via root mean square error, mean bias and percentage of variance accounted for, both as an overall dataset and split into distance bands. The results presented a mean root mean square error of 0.20 ± 0.05 m, and mean bias detected an overestimation for all distance bands. The LPS shows acceptable accuracy for measuring inter-unit distance, opening up opportunities to utilise player tracking for tactical variables indoors.

Validity and Reliability of a Commercially Available Indoor Tracking System to Assess Distance and Time in Court-Based Sports

The aim of this study was to evaluate the validity and reliability of a commercially available local position measurement (LPM) tracking system when assessing distance and running time at different speeds. Fifteen male healthy athletes performed 15 m displacements at walking, running and sprinting speed. Data recorded by the LPM system were compared to those from the reference equipment, consisting of measuring tape and electronic timing gates placed at 0, 5, 10, and 15 m. Mean error, mean absolute error (MAE), standard deviation (SD) of the measurement error, maximum measurement error and root mean square error (RMSE) were calculated to determine the validity for distance and the running time variables. Product-moment correlation and intraclass correlation coefficient (ICC) were also used for the running time. Finally, the reliability of the distance was carried out comparing data from the three repetitions with the standard tape measure using a linear mixed model and the typical error as mean coefficient of variation (CV) (%). MAE shows errors under 0.18 m for the distance variable at all speeds and under 0.08 s for the running time variable at all speeds, except from 15 m at walking. Product-moment correlations were high to nearly perfect for running time (range: 0.60–0.99), ICC varied between high (0.75–0.90) and extremely high (>0.99) for most measures, and coefficients of variation remained almost invariable as speed increased (walking: 2.16; running: 2.52; sprinting: 2.20). The tested LPM system represents a valid and reliable method for monitoring distance during different constant speeds over a straight line, as long as there is no signal loss. However, the running time errors could be too large for performance tests that require acute precision.

Modeling the Quality of Player Passing Decisions in Australian Rules Football Relative to Risk, Reward, and Commitment

The value of player decisions has typically been measured by changes in possession expectations, rather than relative to the value of a player's alternative options. This study presents a mathematical approach to the measurement of passing decisions of Australian Rules footballers that considers the risk and reward of passing options. A new method for quantifying a player's spatial influence is demonstrated through a process called commitment modeling, in which the bounds and density of a player's motion model are fit on empirical commitment to contests, producing a continuous representation of a team's spatial ownership. This process involves combining the probability density functions of contests that a player committed to, and those they did not. Spatiotemporal player tracking data was collected for AFL matches played at a single stadium in the 2017 and 2018 seasons. It was discovered that the probability of a player committing to a contest decreases as a function of their velocity and of the ball's time-to-point. Furthermore, the peak density of player commitment probabilities is at a greater distance in front of a player the faster they are moving, while their ability to participate in contests requiring re-orientation diminishes at higher velocities. Analysis of passing decisions revealed that, for passes resulting in a mark, opposition pressure is bimodal, with peaks at spatial dominance equivalent to no pressure and to a one-on-one contest. Density of passing distance peaks at 17.3 m, marginally longer than the minimum distance of a legal mark (15 m). Conversely, the model presented in this study identifies long-range options as have higher associated decision-making values, however a lack of passes in these ranges may be indicative of differing tactical behavior or a difficulty in identifying long-range options.

Characteristics of Very High Intensity Runs of Soccer Players in Relation to their Playing Position and Playing Half in the 2013-14 Spanish La Liga Season

The objective of this study was to carry out a detailed quantitative analysis of the very high intensity runs during actual play in the 2013-2014 Spanish First Division, at a general level and according to the specific playing position and half. 380 matches of the Spanish First Division in the 2013 - 2014 season were monitored using the Mediacoach video motion analysis tool. Total distance, very high intensity (above 21 km/h) running distance and the number of runs at very high intensity of 230 players from 20 teams in the Spanish First Division were analysed. The main findings of the study were that the performance indicators at very high intensities decreased from the first half to the second half for all outfield players (covered distance: 4694 ± 538 m vs 4485 ± 437 m, sprint distance: 256 ± 72 m vs 239 ± 67 m, number of sprints: 14.3 ± 3.5 vs 13.2 ± 3.1), except the central defenders (sprint distance: 166 ± 37 vs 166 ± 40 m, number of sprints: 10.0 ± 2.1 vs 9.8 ± 3.8). Secondly, although wide defenders (9759 ± 665 m) and central midfielders (9776 ± 942 m) covered the most distance during matches, it were the wide defenders (30 ± 5), centre-forwards (28 ± 7) and wide midfielders (31 ± 8) who performed the most runs at very high intensity. Consequently, the distance they ran at these very high intensity runs followed the same pattern. Such results enable general and specific profiles by demarcation to be established based on the demands of the game at high-level competitive play.

Metabolic Power: A Step in the Right Direction for Team Sports

The ability of the "metabolic power" model to assess the demands of team-sport activity has been the subject of some interest-and much controversy-in team-sport research. Because the cost of acceleration depends on the initial speed and the costs of acceleration and deceleration are not "equal and opposite," changes in speed must be accounted for when evaluating variable-speed locomotion. The purpose of this commentary is to address some of the misconceptions regarding "metabolic power," acknowledge its limitations, and highlight some of the benefits that energetic analysis offers over alternative approaches to quantifying the demands of team sports.

Player Tracking Data Analytics as a Tool for Physical Performance Management in Football: A Case Study from Chelsea Football Club Academy

BACKGROUND

Global positioning system (GPS) based player movement tracking data are widely used by professional football (soccer) clubs and academies to provide insight into activity demands during training and competitive matches. However, the use of movement tracking data to inform the design of training programmes is still an open research question.

OBJECTIVES

The objective of this study is to analyse player tracking data to understand activity level differences between training and match sessions, with respect to different playing positions.

METHODS

This study analyses the per-session summary of historical movement data collected through GPS tracking to profile high-speed running activity as well as distance covered during training sessions as a whole and competitive matches. We utilise 20,913 data points collected from 53 football players aged between 18 and 23 at an elite football academy across four full seasons (2014⁻2018). Through ANOVA analysis and probability distribution analysis, we compare the activity demands, measured by the number of high-speed runs, the amount of high-speed distance, and distance covered by players in key playing positions, such as Central Midfielders, Full Backs, and Centre Forwards.

RESULTS AND IMPLICATIONS

While there are significant positional differences in physical activity demands during competitive matches, the physical activity levels during training sessions do not show positional variations. In matches, the Centre Forwards face the highest demand for High Speed Runs (HSRs), compared to Central Midfielders and Full Backs. However, on average the Central Midfielders tend to cover more distance than Centre Forwards and Full Backs. An increase in high-speed work demand in matches and training over the past four seasons, also shown by a gradual change in the extreme values of high-speed running activity, was also found. This large-scale, longitudinal study makes an important contribution to the literature, providing novel insights from an elite performance environment about the relationship between player activity levels during training and match play, and how these vary by playing position.

Relationship between Impact Velocity and Resulting Head Accelerations during Head Impacts in Youth Football

Football helmet testing standards for youth players make use of the same testing protocol for adult helmets despite research showing differences in head impact exposure between these populations. The objective of this study was to pair estimated impact velocities with linear acceleration data collected from on-field head impacts in youth football to inform youth-specific helmet testing methods. A total of 49 youth football players received helmets instrumented with accelerometer arrays to measure head acceleration throughout the season. Using video recordings of games from a single camera, impact velocities were estimated for impacts with known acceleration magnitudes. On-field accelerations ranged from 40 to 85 g, while impact velocities ranged from 0.5 to 5.5 m/s. The average error associated with these velocity estimates was below 10%, and a zoomed-in camera view provided results more consistent with true velocity. Velocities estimated from direct helmet-to-helmet impacts matched more closely with linear acceleration than other kinds of impacts. These findings may be used to inform testing methods/conditions that are more representative of impacts experienced by youth football players.

Accuracy of a Basketball Indoor Tracking System Based on Standard Bluetooth Low Energy Channels (NBN23®)

The present study aims to identify the accuracy of the NBN23^&reg; system, an indoor tracking system based on radio-frequency and standard Bluetooth Low Energy channels. Twelve capture tags were attached to a custom cart with fixed distances of 0.5, 1.0, 1.5, and 1.8 m. The cart was pushed along a predetermined course following the lines of a standard dimensions Basketball court. The course was performed at low speed (<10.0 km/h), medium speed (>10.0 km/h and <20.0 km/h) and high speed (>20.0 km/h). Root mean square error (RMSE) and percentage of variance accounted for (%VAF) were used as accuracy measures. The obtained data showed acceptable accuracy results for both RMSE and %VAF, despite the expected degree of error in position measurement at higher speeds. The RMSE for all the distances and velocities presented an average absolute error of 0.30 ± 0.13 cm with 90.61 ± 8.34 of %VAF, in line with most available systems, and considered acceptable for indoor sports. The processing of data with filter correction seemed to reduce the noise and promote a lower relative error, increasing the %VAF for each measured distance. Research using positional-derived variables in Basketball is still very scarce; thus, this independent test of the NBN23^&reg; tracking system provides accuracy details and opens up opportunities to develop new performance indicators that help to optimize training adaptations and performance.

When Is a Sprint a Sprint? A Review of the Analysis of Team-Sport Athlete Activity Profile

The external load of a team-sport athlete can be measured by tracking technologies, including global positioning systems (GPS), local positioning systems (LPS), and vision-based systems. These technologies allow for the calculation of displacement, velocity and acceleration during a match or training session. The accurate quantification of these variables is critical so that meaningful changes in team-sport athlete external load can be detected. High-velocity running, including sprinting, may be important for specific team-sport match activities, including evading an opponent or creating a shot on goal. Maximal accelerations are energetically demanding and frequently occur from a low velocity during team-sport matches. Despite extensive research, conjecture exists regarding the thresholds by which to classify the high velocity and acceleration activity of a team-sport athlete. There is currently no consensus on the definition of a sprint or acceleration effort, even within a single sport. The aim of this narrative review was to examine the varying velocity and acceleration thresholds reported in athlete activity profiling. The purposes of this review were therefore to (1) identify the various thresholds used to classify high-velocity or -intensity running plus accelerations; (2) examine the impact of individualized thresholds on reported team-sport activity profile; (3) evaluate the use of thresholds for court-based team-sports and; (4) discuss potential areas for future research. The presentation of velocity thresholds as a single value, with equivocal qualitative descriptors, is confusing when data lies between two thresholds. In Australian football, sprint efforts have been defined as activity >4.00 or >4.17 m·s⁻¹. Acceleration thresholds differ across the literature, with >1.11, 2.78, 3.00, and 4.00 m·s⁻² utilized across a number of sports. It is difficult to compare literature on field-based sports due to inconsistencies in velocity and acceleration thresholds, even within a single sport. Velocity and acceleration thresholds have been determined from physical capacity tests. Limited research exists on the classification of velocity and acceleration data by female team-sport athletes. Alternatively, data mining techniques may be used to report team-sport athlete external load, without the requirement of arbitrary or physiologically defined thresholds.

A Comparison of Speed Profiles During Training and Competition in Elite Wheelchair Rugby Players

PURPOSE

To investigate the speed profiles of individual training modes in comparison with wheelchair rugby (WCR) competition across player classifications.

METHODS

Speed profiles of 15 international WCR players were determined using a radio-frequency-based indoor tracking system. Mean and peak speed (m/s), work:rest ratios, and the relative time spent in (%) and number of high-speed activities performed were measured across training sessions (n = 464) and international competition (n = 34). Training was classified into 1 of 4 modes: conditioning (n = 71), skill-based (n = 133), game-related (n = 151), and game-simulation drills (n = 109). Game-simulation drills were further categorized by the structured duration, which were 3-min game clock (n = 44), 8-min game clock (n = 39), and 10-min running clock (n = 26). Players were grouped by their International Wheelchair Rugby Federation classification as either low-point (≤1.5; n = 8) or high-point players (≥2.0; n = 7).

RESULTS

Conditioning drills were shown to exceed the demands of competition, irrespective of classification (P ≤ .005; effect size [ES] = 0.6-2.0). Skill-based and game-related drills underrepresented the speed profiles of competition (P ≤ .005; ES = 0.5-1.1). Mean speed and work:rest ratios were significantly lower during 3- and 8-min game-simulation drills in relation to competition (P ≤ .039; ES = 0.5-0.7). However, no significant differences were identified between the 10-min running clock and competition.

CONCLUSIONS

Although game-simulation drills provided the closest representation of competition, the structured duration appeared important since the 10-min running clock increased training specificity. Coaches can therefore modify the desired training response by making subtle changes to the format of game-simulation drills.

The use of personalized behavioral feedback for online gamblers: an empirical study

Over the last few years, online gambling has become a more common leisure time activity. However, for a small minority, the activity can become problematic. Consequently, the gambling industry has started to acknowledge their role in player protection and harm minimization and some gambling companies have introduced responsible gambling tools as a way of helping players stay in control. The present study evaluated the effectiveness of mentor (a responsible gambling tool that provides personalized feedback to players) among 1,015 online gamblers at a European online gambling site, and compared their behavior with matched controls (n = 15,216) on the basis of age, gender, playing duration, and theoretical loss (i.e., the amount of money wagered multiplied by the payout percentage of a specific game played). The results showed that online gamblers receiving personalized feedback spent significantly less time and money gambling compared to controls that did not receive personalized feedback. The results suggest that responsible gambling tools providing personalized feedback may help the clientele of gambling companies gamble more responsibly, and may be of help those who gamble excessively to stay within their personal time and money spending limits.

Effect of team rank and player classification on activity profiles of elite wheelchair rugby players

The aim of the current study was to establish which indicators of mobility are associated with successful wheelchair rugby performance and determine whether these indicators differed across classification. Data were collected from 11 international teams during 30 matches (353 match observations) using a radio-frequency-based, indoor tracking system across two tournaments. Players (n = 111) were first grouped by team rank as determined by their International Wheelchair Rugby Federation (IWRF) world ranking (LOW, MID, HIGH) and then into one of four groups based on their IWRF classification: Group I (0.5), Group II (1.0-1.5), Group III (2.0-2.5) and Group IV (3.0-3.5). The volume of activity (relative distance and mean speed), peak speed and time spent within classification-specific arbitrary speed zones were calculated for each individual. Although no differences were identified in the volume of activity, playing time was significantly reduced in LOW (34:51 ± 8:35) compared to MID (48:54 ± 0:51) and HIGH (45:38 ± 9:53), which was further supported by the greater number of substitutions performed by LOW. HIGH achieved greater peak speeds (3.55 ± 0.40 m · s-(1)) than LOW (3.27 ± 0.42 m · s(-1)) and MID (3.45 ± 0.41 m · s(-1)). Peak speed was further shown to be classification-dependent (P ≤ 0.005), whereby HIGH Groups III and IV players achieved greater peak speeds than LOW and MID. The time spent performing high-intensity activities was also greater in HIGH compared to LOW and MID, whilst further influenced by classification (P ≤ 0.0005). To conclude, peak speed and the ability to perform a greater number of high-intensity activities were associated with successful performance in wheelchair rugby.

Data logger device applicability for wheelchair tennis court movement

Assessment of movement logging devices is required to ensure suitability for the determination of court-movement variables during competitive sports performance and allow for practical recommendations to be made. Hence, the purpose was to examine wheelchair tennis speed profiles to assess data logger device applicability for court-movement quantification, with match play stratified by rank (HIGH, LOW), sex (male, female) and format (singles, doubles). Thirty-one wheelchair tennis players were monitored during competitive match play. Mixed sampling was employed (male = 23, female = 8). Friedman's test with Wilcoxon signed-rank post hoc testing revealed a higher percentage of time below 2.5 m · s(-1) [<2.5 vs. ≥2.5 m · s(-1): 89.4 (5.0) vs. 1.2 (3.5)%, Z = -4.860, P < 0.0005, r = 0.87] with the remaining time [9.0 (4.9%)] spent stationary. LOW-ranked players were stationary for longer than HIGH-ranked counterparts [12.6 (8.7) vs. 8.2 (5.1)%, U = 30.000, P = 0.011, r = 0.46] with more time at low propulsion speeds (<1.0 m · s(-1)). HIGH-ranked and doubles players spent more time in higher speed zones than respective counterparts. Females spent more time in the 1.0-1.49 m · s(-1) zone (U = 48.000, P = 0.047, r = 0.36). Regardless of rank, sex or format, propulsion speeds during wheelchair tennis match play are consistent with data logger accuracy. Hence, data logging is appropriate for court-movement quantification.

Accuracy of an UWB-based position tracking system used for time-motion analyses in game sports

The main aim of this study was to determine the accuracy of the ultra-wideband (UWB)-based positioning system Ubisense, which is used for time-motion analysis in sports. Furthermore, some alternatives for positioning the system's transponders on the atheletes, as well as the accuracy depending on the location of measurement, were tested. Therefore, in a pre-study, some basic issues were examined (measurement assumptions and consistency and location of the system's transponder used for position detection), and position measurements at the borders and in the centre of a basketball field were performed. In the main study, 13 male basketball players (15.8 years ± 0.6; 187.9 height ± 3.4; 77.5 weight ± 3.7), equipped with a Ubisense transponder mounted on top of their heads, handled a trundle wheel during simulated match play. The players with the trundle wheel participated passively in the match by following one of the ten competing players. The distance measurements of the trundle wheel were used as reference values and compared to the Ubisense distance estimations. Best results were found with the measurements of a single mounted transponder on top of the athlete's heads. No differences were detectable in the accuracy between measurements in the centre and at the borders of the basketball field. The (Ubisense) system's difference to the (trundle wheel) reference was 3.45 ± 1.99%, resulting in 95% limits of agreement of -0.46-7.35%. The study indicates the examined system's sufficient accuracy for time-motion analysis in basketball.