Validation of electronic performance and tracking systems EPTS under field conditions

Exploring turn demands of an English Premier League team across league and knockout competitions over a full season

Turns are key performance actions in soccer, but can also induce high mechanical loads resulting in tissue damage or injury. This study aimed to quantify the turn demands of an elite English Premier League soccer team. Turning data were obtained from 49 soccer matches (2022-23 season), from a single team that played 35 Premier League, 5 UEFA Europa League, 5 League Cup and 4 FA Cup matches using Sportlight LiDAR technology. Turns were analysed from 29 players who were categorised in playing position groups: goalkeeper (GK), central defenders (CD), full-backs (FB), central-midfielders (CM), wide-midfielders (WM), central-forwards (CF). Turn categories: high (120-180°), medium (60-119°) and low (20-60°) angled, and very high (>7.0ms-1), high (5.5-7.0ms-1), medium (3.0-5.5ms-1), and low (<3.0ms-1) entry speed (ES) was analysed. Primary findings show, on average, per match, CM performed more total turns (~35), than all other playing positions. Additionally, CM performed significantly more low and medium entry speed and high angled turns than other outfield positions. There were no significant differences between turn frequencies and turn characteristics in different competitions (p >0.05). The turning demands of soccer appear to vary significantly between player position. These findings may help inform position-specific return-to-play protocols, physical preparation strategies, drill design and rehabilitation programmes.

Physical and technical performance in and after the worst-case scenario in matches of the Chinese Super League of soccer

This study aims to investigate the changes in physical and technical performance of professional soccer players during effective playing time after the worst-case scenario (WCS) identified by the high-intensity running (HIR) distance using rolling average. A total of 576 matches (n = 13,298 observations) from the 2019 to 2021 season of the Chinese Super League (CSL) were analyzed by a video tracking system. Generalized mixed linear models were established to determine the mean changes in the value of 7 physical and 24 technical performance-related parameters in the effective playing time from the 5 min of WCS (Peak5) to the initial 5 minutes post-WCS (Post5). Results showed that: (1) For all the players in the Post5 total distance, HIR distance, and Sprint decreased by 16.6% (ES; ± 99%CL: 0.57; ± 0.04), 77.2% (2.78; ± 0.06), and 86.1% (2.11; ± 0.08), respectively. The number of efforts, average duration, average speed, and average length of HIR declined by 70.8% (2.26; ± 0.06), 31.7% (0.78; ± 0.05), 3.1% (0.52; ± 0.05), and 22.9% (0.83; ± 0.05), respectively; (2) In the Post5, a substantial decrement in the number (0.23; ± 0.03), average speed (0.32; ± 0.06) and average length (0.37; ± 0.06) of running with the ball, and average speed receiving the ball (0.5; ± 0.05) was observed for all players. While only trivial changes were detected in all the other technical performance-related parameters. It can be concluded that, in the Post5, there is a temporary decline in physical output and the physical-related technical parameters for players, however, there are no meaningful changes in other technical performancerelated parameters.

'Setting the Benchmark' Part 4: Contextualising the Match Demands of Teams at the FIFA Women's World Cup Australia and New Zealand 2023

The aims of the present study were to: (1) analyse the upper and lower match physical performance benchmarks and variability of teams at the FIFA Women's World Cup Australia and New Zealand 2023, (2) examine the evolving team sprint ranking across three Women's World Cups and (3) investigate noteworthy relationships between collective physical and tactical metrics. With FIFA's official approval, all sixty-four games at the tournament were analysed using an optical tracking system alongside FIFA's Enhanced Football Intelligence metrics. On average, teams at the FIFA Women's World Cup 2023 covered 103.3 ± 4.4 km in total, with 6.7 ± 0.6 km and 1.9 ± 0.3 km covered at the higher intensities (≥19.0 & ≥23.0 km · h-1), respectively. The top five ranked teams from a high-intensity running perspective (Zambia, Spain, Brazil, Canada, Denmark) covered 24-44% more distance than the bottom five ranked teams (Jamaica, Columbia, Costa Rica, Switzerland, Vietnam) at the tournament (P < 0.01; Effect Size [ES]: 2.3-2.5). Match-to-match variation of teams revealed Italy and Panama were particularly consistent for the distances covered at higher intensities (Coefficient of Variation [CV]: 0.3-4.5%), while Costa Rica demonstrated considerable variation (CV: 23.4-40.7%). Teams generally covered more total distance on a per-minute basis in the first versus the second half (P < 0.01; ES: 1.1), but no differences existed at higher intensities (P > 0.05; ES: 0.1-0.2). Correlations were found between the number of high-intensity runs and various phase of play events for defensive transitions and recoveries, in addition to progressions up the pitch and into the final third (r = 0.48-0.88; P < 0.01). A basic comparative analysis revealed Spain demonstrated the most pronounced increase (2015 = 9th, 2019 = 35th, 2023 = 90th percentile; CV: 92.6%) and China PR the most marked decrease (2015 = 22nd, 2019 = 30th, 2023 = 0 percentile; CV: 89.6%) in their sprinting percentile rank across the last three FIFA Women's World Cups. The present findings provide a depiction of the current collective demands of international women's football. This information could be useful for practitioners to benchmark team performances and to potentially understand the myriad of contextual factors impacting physical performances.

Beyond boundaries: a location-based toolkit for quantifying group dynamics in diverse contexts

Existing toolkits for analyzing movement dynamics in animal ecology primarily focus on individual or group behavior in habitats without predefined boundaries, while methods for studying human activity often cater to bounded environments, such as team sports played on defined fields. This leaves a gap in tools for modeling and analyzing human group dynamics in large-scale, unbounded, or semi-constrained environments. Examples of such contexts include tourist groups, cycling teams, search and rescue teams, and military units. To address this issue, we survey existing methods and metrics for characterizing individual and collective movement in humans and animals. Using a rich GPS dataset from groups of military personnel engaged in a foot march, we develop a comprehensive, general-purpose toolkit for quantifying group dynamics using location-based metrics during goal-directed movement in open environments. This toolkit includes a repository of Python functions for extracting and analyzing movement data, integrating cognitive factors such as decision-making, situational awareness, and group coordination. By extending location-based analytics to non-traditional domains, this toolkit enhances the understanding of collective movement, group behavior, and emergent properties shaped by cognitive processes. To demonstrate its practical utility, we present a use case utilizing metrics derived from the foot march data to predict group performance during a subsequent strategic and tactical exercise, highlighting the influence of cognitive and decision-making behaviors on team effectiveness.

Accuracy of an Ultra-Wideband-Based Tracking System for Time-Motion Analysis in Tennis

Player-tracking systems provide vital time-motion and tactical data for analyzing athletic performance. Ultra-wideband (UWB) systems are promising for racquet sports due to their accuracy and cost-effectiveness compared to GNSS and optical systems. This study evaluated the accuracy of a UWB tracking system (GenGee Insait KS) for tennis-specific movements by comparing it with an optical motion capture system (VICON). Ten amateur players (International Tennis Numbers: 2-5) participated, performing seven exercises, including warm-up, agility drills, and tactical drills, with and without racquets. Raw data from both systems were processed to calculate the distances traversed. The average root mean square error between the two systems was 0.65 m (X-axis) and 0.76 m (Y-axis). Significant measurement discrepancies were observed (standardized mean difference: 0.86-1.95), except for jogging and walking exercises (p > 0.05). The overall percentage error was 16.29%. The intraclass correlation coefficient for distance measurements was 0.91, indicating good reliability. Tasks involving rapid acceleration and directional changes, such as the spider run, exhibited larger errors (mean bias: 4.13 m, effect size: 1.03). While the UWB system demonstrated acceptable accuracy for steady movements, it showed notable discrepancies during high-speed, tennis-specific activities. Overestimation due to arm movement and hip rotation suggests caution when applying arm-mounted UWB devices in training and competitive settings.

Performance in professional soccer players: normative data and benchmarks from official matches for metabolic power and high-intensity activities

BACKGROUND

The opportunity to compare data among players using normative data and benchmarks may represent a helpful tool for coaches to assess the players' physical performance easily and quickly. This study aimed to create normative data and benchmarks that can be exploited to compare professional soccer players' physical capacity competing in the Premier Division Championship (series A).

METHODS

Match data from six professional soccer teams competing in the Premier Division championship (Serie A and Italy Cup matches) were collected during the entire season. Players (N.=112) were divided based on the role positioning as follows: forwards and wingers (FW), midfielders (MF), side-backs (SB), and center-backs (CB). All the teams analyzed competed with a 4-3-3 formation, and only players who played for the entire match (85-95 minutes) were considered. The video analysis system STATS SportVU was used to collect the data during official matches. Average metabolic power (AP) was considered to estimate the energy cost. The number of power events (PE), distance (m) covered at more than 25 W/kg (D25), and finally, the distance covered at v>25 km/h (VHS) were considered as high-intensity assessments. Standardized T-scores (scaled from 0 to 100) were calculated for each role and variable.

RESULTS

T-score data was used to create performance bands combined with qualitative description (ranging from extremely poor to excellent), and a traffic light system approach was implemented to simplify the data's interpretation.

CONCLUSIONS

The results could be used to compare different athletes' performance quickly and effectively, to detect symptoms of overtraining, and to give helpful insights to coaches on what the training should be focused on.

Measurement Properties of Wearable Kinematic-Based Data Collection Systems to Evaluate Ball Kicking in Soccer: A Systematic Review with Evidence Gap Map

Kinematic assessment of ball kicking may require significant human effort (e.g., traditional vision-based tracking systems). Wearables offer a potential solution to reduce processing time. This systematic review collated measurement properties (validity, reliability, and/or accuracy) of wearable kinematic-based technology systems used to evaluate soccer kicking. Seven databases were searched for studies published on or before April 2024. The protocol was previously published and followed the PRISMA 2020 statement. The data items included any validity, reliability, and/or accuracy measurements extracted from the selected articles. Twelve articles (1011 participants) were included in the qualitative synthesis, showing generally (92%) moderate methodological quality. The authors claimed validity (e.g., concurrent) in seven of the eight studies found on the topic, reliability in two of three, and accuracy (event detection) in three of three studies. The synthesis method indicated moderate evidence for the concurrent validity of the MPU-9150/ICM-20649 InvenSense and PlayerMaker™ devices. However, limited to no evidence was identified across studies when considering wearable devices/systems, measurement properties, and specific outcome variables. To conclude, there is a knowledge base that may support the implementation of wearables to assess ball kicking in soccer practice, while future research should further evaluate the measurement properties to attempt to reach a strong evidence level.

Influence of Substitutions and Roles on Kinematic Variables in Professional Soccer Players

In soccer, roles and substitutions can make it unclear how different physical capacities decrease over time and impact performance. This investigation aimed to analyze kinematic parameters and their changes over game time, and provide information to effectively prescribe training programs. Data from four professional teams were analyzed, and all the teams competed in the Italian First Division (Serie A). Average metabolic power and high-intensity activities associated with critical moments in the match were considered in the comparisons. The video analysis system STATS SportVU collected the data during official matches. Players were assigned to a specific group according to their time played, categorized as follows: 0-15', 15-30', 30-45', 45-60', 60-75', 75-90', and > 90 min. Different roles, including forwards and wingers (FW), midfielders (MF), center-backs (CB), and side-backs (SB) were also considered. Significant differences (p<0.05) were found in different roles and within roles at different times played. The results highlighted how MF performance decreased over time, whereas CB was unaffected by time. SB spent more time at very high velocity than other roles, independently from the time played. These findings provide valuable information about the physical demands of official soccer matches and could be used to review training prescriptions.

Contextualised physical metrics: The physical demands vary with phase of play during elite soccer match play

The physical demands of elite soccer match play have traditionally been measured using aggregated whole-match metrics. However, match play is increasingly considered as distinct phases of play, although the influence of phase of play on match physical demands remains largely unknown. This study compared physical intensity, acceleration and deceleration demands, between phases of play and according to playing position. The duration of each match from a major European league (n = 1083) was divided into one of five reciprocal phases (for the in-/out-of-possession team) using event and tracking data: build-up/high-block, progression/mid-block, chance creation/low-block, fast attack/fast defence, or attacking transition/defensive transition. Player tracking data were used to calculate physical intensity as the rate of distance covered (m⋅min-1) in total and within five speed categories, and the proportion of time spent accelerating and decelerating (>2 m s-2) during each phase of play. Rate of distance covered in total differed markedly with phase of play; fast attack 35%-53% greater, and fast defence 33%-50% greater, than other in-/out-of-possession phases respectively, and these effects were amplified for the rate of distance covered at higher speeds (e.g., sprinting ≥4-fold differences between phases). Match phase also affected the proportion of time spent accelerating and decelerating (highest for fast attack and chance creation, respectively), especially when in-possession for forwards and when out-of-possession for defenders (p < 0.001). Phase of play had a large effect on the physical intensity of match play, particularly rates of distance covered at higher speeds, as well as the acceleration and deceleration demands, and in a position specific manner.

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

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

The Relationship Between Playing Formations, Team Ranking, and Physical Performance in the Serie A Soccer League

The influence of playing formations and team ranking on the physical performance of professional soccer players is an open question that needs to be explored. The present study aimed to investigate the impact of these factors on the physical exertion of Serie A soccer players. We analyzed match data from 375 players, categorizing teams based on their final ranking and comparing performance across different playing formations. The Kruskal-Wallis test and the Dunn test with Bonferroni adjustment revealed that high-ranking (HR) teams exhibited a higher percentage of high-intensity (HI) accelerations compared to mid-ranking teams, suggesting the critical role of HI efforts in achieving favorable match outcomes. Moreover, the 4-3-3 playing formation was associated with greater acceleration demands than other formations, particularly in HR teams. Our study also established benchmarks for various performance metrics, enabling coaches to assess player performance and identify potential signs of overtraining. These findings contribute to a deeper understanding of the physical demands in soccer and offer practical implications for coaches and players in optimizing training and performance strategies.

Agreement and Sensitivity of the Acceleration-Velocity Profile Derived via Local Positioning System

Sprint performance is commonly assessed via discrete sprint tests and analyzed through kinematic estimates modeled using a mono-exponential equation, including estimated maximal sprinting speed (MSS), relative acceleration (TAU), maximum acceleration (MAC), and relative propulsive maximal power (PMAX). The acceleration-velocity profile (AVP) provides a simple summary of short sprint performance using two parameters: MSS and MAC, which are useful for simplifying descriptions of sprint performance, comparison between athletes and groups of athletes, and estimating changes in performance over time or due to training intervention. However, discrete testing poses logistical challenges and defines an athlete's AVP exclusively from the performance achieved in an isolated testing environment. Recently, an in situ AVP (velocity-acceleration method) was proposed to estimate kinematic parameters from velocity and acceleration data obtained via global or local positioning systems (GPS/LPS) over multiple training sessions, plausibly improving the time efficiency of sprint monitoring and increasing the sample size that defines the athlete's AVP. However, the validity and sensitivity of estimates derived from the velocity-acceleration method in relation to changes in criterion scores remain elusive. To assess the concurrent validity and sensitivity of kinematic measures from the velocity-acceleration method, 31 elite youth basketball athletes (23 males and 8 females) completed two maximal effort 30 m sprint trials. Performance was simultaneously measured by a laser gun and an LPS (Kinexon), with kinematic parameters estimated using the time-velocity and velocity-acceleration methods. Agreement (%Bias) between laser gun and LPS-derived estimates was within the practically significant magnitude (±5%), while confidence intervals for the percentage mean absolute difference (%MAD) overlapped practical significance for TAU, MAC, and PMAX using the velocity-acceleration method. Only the MSS parameter showed a sensitivity (%MDC95) within practical significance (<5%), with all other parameters showing unsatisfactory sensitivity (>10%) for both the time-velocity and velocity-acceleration methods. Thus, sports practitioners may be confident in the concurrent validity and sensitivity of MSS estimates derived in situ using the velocity-acceleration method, while caution should be applied when using this method to infer an athlete's maximal acceleration capabilities.

Evolution of passing network in the Soccer World Cups 2010-2022

This study investigates the evolution of passing networks (PN) at both team and player levels in the FIFA World Cups (WC) from 2010 to 2022. Analyzing 256 matches (7328 player observations) using a multiple-camera tracking system across four WCs, we considered six playing positions: goalkeeper (n = 521), central defender (n = 1192), fullback (n = 1223), midfielder (n = 2039), winger (n = 1320), and central forward (n = 1033). We used 17 network metrics and considered contextual variables such as team formation, and team ranking. Linear mixed-effect models analyzed differences in team and player PN parameters by year and team strength. Results showed a shift from possession-play to direct-play from the 2010 to 2018 WCs, with possession-play returning in 2022. Specifically, high- and low-quality teams significantly decreased their density, average degree (AD), modularity, and average path length in 2018 (p < 0.05). High-quality teams showed increased density, AD, and average weighted degree in 2022 (p < 0.05). Midfielders and central forwards exhibited significantly lower centrality parameters, whereas central defenders and goalkeepers showed increased centrality parameters (p < 0.05). This study highlights the evolutionary trends of passing relationships from a network analysis perspective over twelve years, providing insights into the changing dynamics of team interactions and positional prominence in elite soccer.

Effect of Data-Processing Methods on Acceleration Summary Metrics of GNSS Devices in Elite Australian Football

This study aimed to measure the differences in commonly used summary acceleration metrics during elite Australian football games under three different data processing protocols (raw, custom-processed, manufacturer-processed). Estimates of distance, speed and acceleration were collected with a 10-Hz GNSS tracking technology device from fourteen matches of 38 elite Australian football players from one team. Raw and manufacturer-processed data were exported from respective proprietary software and two common summary acceleration metrics (number of efforts and distance within medium/high-intensity zone) were calculated for the three processing methods. To estimate the effect of the three different data processing methods on the summary metrics, linear mixed models were used. The main findings demonstrated that there were substantial differences between the three processing methods; the manufacturer-processed acceleration data had the lowest reported distance (up to 184 times lower) and efforts (up to 89 times lower), followed by the custom-processed distance (up to 3.3 times lower) and efforts (up to 4.3 times lower), where raw data had the highest reported distance and efforts. The results indicated that different processing methods changed the metric output and in turn alters the quantification of the demands of a sport (volume, intensity and frequency of the metrics). Coaches, practitioners and researchers need to understand that various processing methods alter the summary metrics of acceleration data. By being informed about how these metrics are affected by processing methods, they can better interpret the data available and effectively tailor their training programs to match the demands of competition.

Playing position and match location affect the number of high-intensity efforts more than the quality of the opposition in elite football players

This study aimed to examine the impact of playing position (PP), match location (ML), and opposition standard (OS) on team and individual acceleration (ACC) and deceleration (DEC) efforts. Fifty professional football players were monitored across 24 English Premier Development League matches during the 2020/21 season. High-intensity ACC and DEC thresholds were set at > +3 m · s-2 and < -3 m · s-2, respectively. Players were divided into five PPs: centre backs (CB; n = 68), full-backs (FB; n = 24), centre midfielders (CM; n = 54), wide midfielders (WM; n = 15), centre forwards (CF; n = 27). Opposition standard was categorised as Top (1st-4th), Middle (5th-9th), and Bottom (9th-13th) based on final league ranking of the study season. Each match location was classified as Home or Away. One way analysis of variance (ANOVA) and a multivariate ANOVA analysed the independent effect of PP, ML and OS on ACC and DEC efforts, and the interaction of all contextual factors, respectively. Acceleration efforts were affected by PP and ML. FB performed 22% more ACC than WM. All players performed 6% more ACC actions during home matches compared to away fixtures. DEC efforts were only affected by PP, with FB and CM executing 26% and 32% greater DEC efforts than CB, respectively. When playing against top or middle teams at home, CB, CM, and CF tended to perform more high-intensity actions than when playing away. In contrast, when playing against top teams at home, FB and WM performed fewer high-intensity actions than when playing away. Playing position and ML affected ACC and DEC actions but not OS.

Analyzing the impact of non-participation in the FIFA World Cup Qatar 2022 on LaLiga players' physical performance

Background

Monitoring external load demands in soccer is crucial for optimizing performance and reducing injury risk. However, events like the FIFA World Cup Qatar 2022 and unexpected interruptions can disrupt load management strategies. Understanding the impact of such events on player performance is essential for effective training and recovery strategies.

Objective

This study retrospectively assessed the impact of the FIFA World Cup Qatar 2022 on the physical performance of LaLiga elite soccer players who were not part of the tournament. The aim was to analyze various external load parameters and determine the direction of their changes post-tournament.

Methods

Data from 239 LaLiga players who were not selected for the World Cup were analyzed. External load parameters from 8 matches before and after the tournament were compared. Statistical analyses, including repeated measures ANOVA, were conducted to evaluate changes in performance metrics.

Results

Minutes played and total distance covered showed no significant changes post-tournament. However, maximal speed decreased significantly (p < 0.001; η2p = 0.117). High-speed running parameters improved significantly (p < 0.05), except for HSRRelCount (p = 0.074; η2p = 0.013). Sprint-related variables demonstrated significant enhancements, except for SprintAbsAvgDuration, SprintMaxAvgDuration, and Sprints >85% Vel Max. Acceleration metrics showed significant improvements in Accel_HighIntensityAccAbsCount (p = 0.024; η2p = 0.021), while Accel_Accelerations showed no significant changes. Deceleration metrics remained unchanged, but Accel_HighIntensityDecAbsCount and Accel_HighIntensityDecAbsDistance increased significantly post-tournament (p = 0.002; η2p = 0.040, p = 0.001; η2p = 0.044, respectively).

Conclusion

Non-participant LaLiga players demonstrated enhanced performance in most external load metrics after the FIFA World Cup Qatar 2022. These findings highlight the importance of effective load management during periods of competition interruption and suggest strategies to optimize performance and reduce injury risk. Further research should consider holistic performance metrics and internal load parameters to provide comprehensive insights into player response to mid-season tournaments.

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

OBJECTIVES

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

DESIGN

Repeated measures.

METHODS

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

RESULTS

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

CONCLUSIONS

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

In which rounds were the most rotations of key players made, and how did this affect physical activity? Analysis of the eight best teams of the 2018 FIFA world cup Russia

BACKGROUND

Team management, especially player selection, rotation, and availability, are critical issues when dealing with the high demands of modern training and gameplay. As such, research continuously seeks ways to improve these actions or implement new ideas to gain a competitive advantage through the rotation of players in the starting line-up. The current study aimed to examine the rounds of the 2018 FIFA World Cup Russia in which the most rotations of key players were made and how this affected physical activity.

METHODS

The sample consisted of 110 players from the top eight teams in the 2018 World Cup Russia who played entire matches for up to 90 min in seven consecutive games. All players were divided into key players (KPs, n = 58) and non-key players (NKPs, n = 52). The analysis used data collected by an advanced motion analysis system known as STATS®, with physical activity variables analyzed, including total distance covered (TDC), distance covered with high intensity over 20 km/h (HIR), and the number of sprints undertaken. In statistical analysis, differences between categories and consecutive matches were calculated using the Kruskal-Wallis H test, and if a significant effect size was found, a multiple comparisons p values test was performed.

RESULTS

The best teams at the 2018 FIFA World Cup Russia used the most KP rotations with NKPs in the third match of the group stage. In addition, this was even more visible among more successful teams than less successful teams. The rotation strategy among the best eight teams allowed them to maintain the physical activity of KPs and NKPs in all rounds of the tournament.

CONCLUSIONS

Coaches and coaching staff should incorporate squad rotation that includes a large group of players in their team management to improve their success. Team management expertise in player rotation during matches played over congested schedules at top tournaments maintains high levels of physical activity indicators (TDC, HIR, and sprints).

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.

In professional football the decline in high-intensity running activities from first to second half is more pronounced in players with a fast muscle typology

Muscle typology is heterogeneous among national level football (soccer) players, but positional differences remain unclear. Furthermore, fast typology (FT) individuals fatigue more than slow typology (ST) individuals in lab conditions. Therefore, we investigated if muscle typology is different between playing positions and if the decay in high-intensity activities from the first to the second half is larger in FT football players than in ST players. We estimated muscle typology in 147 male professional football players by measuring soleus and gastrocnemius muscle carnosine via proton magnetic resonance spectroscopy. Players were classified as ST, intermediate typology (IT) or FT and categorized as goalkeeper, center back, full back, midfielder, winger or forward. Across four seasons in-game distances covered in multiple running speed, acceleration and deceleration zones were collected during the first and second half. We found no differences in muscle typology between positions (p = 0.412). FT players covered 10.9% more high acceleration distance (>3 m.s-2 ) in the first half than ST players (p = 0.021) and high acceleration distance decay was larger for FT players (-12.4%) than ST (-7.7%; p = 0.006) and IT players (-7.3%; p = 0.010). Moreover, the decline in distance covered in several high-intensity zones tended to be larger in FT players (-11.2% high-intensity >15 km.h-1 ; -12.7% high deceleration <-3 m.s-2 ; -11.5% medium acceleration 2-3 m.s-2 ) than in ST players (-7.1% high-intensity; -8.1% high deceleration; -8.1% medium acceleration; 0.05 < p < 0.1). In conclusion, possessing a particular muscle typology is not required to play any football position at the national level. However, there are indications that FT players might fatigue more toward the end of the game compared to ST players.

Challenges and considerations in determining the quality of electronic performance & tracking systems for team sports

Electronic performance & tracking systems (EPTS) are commonly used to track the location and velocity of athletes in many team sports. A range of associated applications using the derived data exist, such as assessment of athlete characteristics, informing training design, assisting match adjudication and providing fan insights for broadcast. Consequently the quality of such systems is of importance to a range of stakeholders. The influence of both systematic and methodological factors such as hardware, software settings, sample rate and filtering on this resulting quality is non-trivial. Highlighting these allows for the user to understand their strengths and limitations in various decision-making processes, as well as identify areas for research and development. In this paper, a number of challenges and considerations relating to the determination of EPTS validity for team sport are outlined and discussed. The aim of this paper is to draw attention of these factors to both researchers and practitioners looking to inform their decision-making in the EPTS area. Addressing some of the posited considerations in future work may represent best practice; others may require further investigation, have multiple potential solutions or currently be intractable.

Using Microtechnology and the Fourier Transform for the Analysis of Effective Activity Time in Professional Soccer

ABSTRACT

Oliva-Lozano, JM, Chmura, P, Granero-Gil, P, and Muyor, JM. Using microtechnology and the Fourier Transform for the analysis of effective activity time in professional soccer. J Strength Cond Res 37(12): 2491-2495, 2023-This study aimed to investigate the use of the fast Fourier transform (FFT) for the analysis of effective activity time in professional soccer by (a) exploring the relationship between this variable and standard external load parameters and (b) analyzing the effective activity time during official professional soccer matches. Twenty-six male players participated in the study. Each player was categorized as midfielder, central defender, full-back, wide-midfielder, or forward. Tracking systems based on inertial sensors (4 3D accelerometers, 3 3D gyroscopes, and 1 magnetometer), and global positioning systems technology were used to collect external load measures for 35 matches. Each match was analyzed considering 15-minute periods to explore the evolution of effective activity time during the matches. The extra time from each match was also included. Fast Fourier transform duration may be a representative variable of effective activity time, given the strong positive correlation with the external load variables ( p < 0.001). The linear regression analysis showed that the variables that significantly contributed to the model ( R2 = 0.97) were the total of steps and the distance covered. The mean effective activity time in soccer match play was ∼48.69 minutes. This time significantly changed depending on factors such as the period of the match ( F = 239.05; p < 0.001; ηp 2 = 0.60) or playing position ( F = 16.99; p < 0.001; ηp 2 = 0.06). The greatest effective activity time was observed for all playing positions in the 0'-15' period. However, the 60'-75' period showed the lowest effective activity times compared with the rest of the 15-minute periods for all positions except for forwards (75'-90'). From a practical standpoint, sports performance practitioners may consider these results to improve the individualization of training and match demands. Also, a more accurate indicator of exercise intensity may be obtained (e.g., multiplying the rating of perceived exertion by the effective activity time).

Interchangeability of optical tracking technologies: potential overestimation of the sprint running load demands in the English Premier League

PURPOSE

The purpose of this study was to assess the agreement between match-derived running load outputs; total distance (TD), high-speed running (HSR) and sprint distance (SPR) obtained by two optical tracking systems.

METHODS

Data were collected from 31 elite footballers from the first team and under-21 squads of an English Premier League (EPL) football club across three competitive matches. One EPL game (game 2) and one under-21 Premier League game (game 3) were played at the team's home stadium and one EPL game (game 1) at an away venue. All matches were tracked concomitantly using eight colour cameras sampling at 10 Hz (PROZONE®) and six high-definition motion cameras sampling at 25 Hz (TRACAB®).

RESULTS

TD displayed a perfect (r = 0.99) correlation while HSR and SPR displayed very large (r = 0.81 and r = 0.73) correlations between TRACAB® and PROZONE®. Mean biases were 5% for TD, -3% for HSR and 61% for SPR. Between games, mean biases for TD were 6% for game 1, and 5% for game 2 and game 3. For HSR, 9% for game 1, -5% for game 2 and 6% for game 3 and for SPR, 31% for game 1, 71% for game 2 and 84% for game 3.

CONCLUSION

TD and HSR can be interchanged between PROZONE® and TRACAB®, to allow accurate interpretation between the two optical systems. PROZONE® overestimated SPR compared to the TRACAB®, with the magnitude of difference considered meaningful, altering interpretation of historical match outputs, sprint volume trends in the EPL and forecasts of the modern game.

Exploring the interplay between metabolic power and equivalent distance in training games and official matches in soccer: a machine learning approach

Introduction: This study aimed to explore the interplay between metabolic power (MP) and equivalent distance (ED) and their respective roles in training games (TGs) and official soccer matches. Furthermore, the secondary objective was to investigate the connection between external training load (ETL), determined by the interplay of metabolic power and equivalent distance, and internal training load (ITL) assessed through HR-based methods, serving as a measure of criterion validity. Methods: Twenty-one elite professional male soccer players participated in the study. Players were monitored during 11 months of full training and overall official matches. The study used a dataset of 4269 training games and 380 official matches split into training and test sets. In terms of machine learning methods, the study applied several techniques, including K-Nearest Neighbors, Decision Tree, Random Forest, and Support-Vector Machine classifiers. The dataset was divided into two subsets: a training set used for model training and a test set used for evaluation. Results: Based on metabolic power and equivalent distance, the study successfully employed four machine learning methods to accurately distinguish between the two types of soccer activities: TGs and official matches. The area under the curve (AUC) values ranged from 0.90 to 0.96, demonstrating high discriminatory power, with accuracy levels ranging from 0.89 to 0.98. Furthermore, the significant correlations observed between Edwards' training load (TL) and TL calculated from metabolic power metrics confirm the validity of these variables in assessing external training load in soccer. The correlation coefficients (r values) ranged from 0.59 to 0.87, all reaching statistical significance at p < 0.001. Discussion: These results underscore the critical importance of investigating the interaction between metabolic power and equivalent distance in soccer. While the overall intensity may appear similar between TGs and official matches, it is evident that underlying factors contributing to this intensity differ significantly. This highlights the necessity for more comprehensive analyses of the specific elements influencing physical effort during these activities. By addressing this fundamental aspect, this study contributes valuable insights to the field of sports science, aiding in the development of tailored training programs and strategies that can optimize player performance and reduce the risk of injuries in elite soccer.

The influence of ball in/out of play and possession in elite soccer: Towards a more valid measure of physical intensity during competitive match-play

The physical demands of soccer match-play have typically been assessed using a low-resolution whole match approach ignoring whether the ball is in or out of play (BIP/BOP) and during these periods which team has possession. This study investigated the effect of fundamental match structure variables (BIP/BOP, in/out of possession) on the physical demands, and especially intensity, of elite match-play. For 1083 matches from a major European league, whole match duration, and player physical tracking data, were divided into BIP/BOP, and in/out of possession periods throughout the match, using on-ball event data. These distinct phases were used to derive absolute (m) and rate (m·min-1) of distance covered in total and within six speed categories during BIP/BOP and in/out possession. The rate of distance covered, an index of physical intensity, was >2-fold greater during BIP vs BOP. Whole match total distance covered was confounded by BIP time and poorly associated with physical intensity during BIP (r = 0.36). Whole match rates of distance covered substantially underestimated those during BIP, particularly for higher running speeds (∼-62%). Ball possession markedly effected physical intensity, with the rates of distance covered running (+31%), at high-speed (+30%) and in total (+7%) greater out than in possession. Whole match physical metrics underestimated the physical intensity during BIP, and thus the rate(s) of distance covered during BIP are recommended for accurate measurement of physical intensity in elite soccer. The greater demands of being out of possession support a possession-based tactical approach to minimise fatigue and its negative consequences.

Metabolic power and energy expenditure in the German Bundesliga

The aims of the study were to analyze metabolic power (MP) and MP derived parameters for different positions in the German Soccer Bundesliga and to evaluate if classification of high-intensity is more suited using the metabolic power approach instead of using traditional speed-based methods. 1,345 video match analysis (25 Hz) datasets from 380 players in 96 matches of the German first Bundesliga were gathered by an automatic player tracking system. Displacement (speed, acceleration, distance) and energetic (MP, energy expenditure) variables were determined. Intensity was classified utilizing conventional thresholds. Metabolic and running profiles were compared among six positional groups and between the halves of the match respectively (one-way ANOVA). Further, time spent, distance covered and energy expended at high speed (>15.5 km h-1) and high acceleration (>2 m s-2) were compared to those at high MP (>20 W kg-1) (one-way ANOVA) for evaluating if metabolic power is more suited to describe intensity in team sports. Main findings are that central-attacking midfielders (CAM) and central midfielders (CM) expended more energy (CAM: 59.8 ± 4.2 kJ kg-1; CM: 59.6 ± 3.6 kJ kg-1) and covered more distance (CAM: 11,494 ± 765 m; CM: 11,445 ± 638 m) than all other positions (p < 0.001). In the whole group of players, less time (t) and less energy were expended (EE) in high speed (t: 302 ± 84 s; EE: 10.1 ± 2.9 kJ kg-1) and at high acceleration zones (t: 147 ± 24 s; EE: 5.5 ± 1.2 kJ kg-1) when compared to high MP zone (t: 617 ± 141 s; EE: 20.0 ± 4.4 kJ kg-1) (p < 0.001). Furthermore, players covered more distance at high MP (2,464 ± 597 m) than at high speed (1,638 ± 458 m) and much less at high acceleration (359 ± 67 m) (p < 0.001). The higher activity profiles of CAM and CM compared to the other positions indicate the need for higher developed physiological performance in players of these positions. High intensity activities should be interpreted differently when using MP and displacement parameters as indicators of high intensity in soccer.

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.

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

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

Contact times in professional football before and during the SARS-CoV-2 pandemic: Tracking data from the German Bundesliga

The global SARS-CoV-2 pandemic led to a lockdown in team sports in March 2020. Because the risk of virus transmission seems to correlate with the duration of close contacts, data on contact times are necessary to assess the risk of virus transmission in sports. In this study, an optical tracking system was used to determine contact times between players of the two highest men's professional football leagues in Germany in the 2019-20 season and in the first half of the 2020-21 season. Contacts between players were defined as being within a two-metre radius during matches and were differentiated as either match-specific or non-match-specific. In total, 918 matches with 197,087 contacts were analysed. The mean overall contact time of one-to-one situations of 36 s (SD: ± 66) before the lockdown was reduced to 30 s after the lockdown (SD: ± 60) (p < 0.0001). In professional football, contacts between two players infrequently occur within a two-metre radius, averaging less than 35 s. Only 36 player pair contacts lasted for more than 15 min (0.00018%). The mean accumulated contact time per player with all others was 10.6 ± 6.9 min per match, with a decrease from 11.6 ± 7.0 min before the lockdown to 10.0 ± 6.6 min (p < 0.0001) after lockdown in the season 2019-20. The SARS-CoV-2 pandemic has resulted in a reduction in match-specific contacts of 25%. It seems questionable if such short contacts in open-air sports may lead to considerable virus transmission.

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).

Gaussian mixture modeling of acceleration-derived signal for monitoring external physical load of tennis player

Introduction: With the widespread use of wearable sensors, various methods to evaluate external physical loads using acceleration signals measured by inertial sensors in sporting activities have been proposed. Acceleration-derived external physical loads have been evaluated as a simple indicator, such as the mean or cumulative values of the target interval. However, such a conventional simplified indicator may not adequately represent the features of the external physical load in sporting activities involving various movement intensities. Therefore, we propose a method to evaluate the external physical load of tennis player based on the histogram of acceleration-derived signal obtained from wearable inertial sensors. Methods: Twenty-eight matches of 14 male collegiate players and 55 matches of 55 male middle-aged players wore sportswear-type wearable sensors during official tennis matches. The norm of the three-dimensional acceleration signal measured using the wearable sensor was smoothed, and the rest period (less than 0.3 G of at least 5 s) was excluded. Because the histogram of the processed acceleration signal showed a bimodal distribution, for example, high- and low-intensity peaks, a Gaussian mixture model was fitted to the histogram, and the model parameters were obtained to characterize the bimodal distribution of the acceleration signal for each player. Results: Among the obtained Gaussian mixture model parameters, the linear discrimination analysis revealed that the mean and standard deviation of the high-intensity side acceleration value accurately classified collegiate and middle-aged players with 93% accuracy; however, the conventional method (only the overall mean) showed less accurate classification results (63%). Conclusion: The mean and standard deviation of the high-intensity side extracted by the Gaussian mixture modeling is found to be the effective parameter representing the external physical load of tennis players. The histogram-based feature extraction of the acceleration-derived signal that exhibit multimodal distribution may provide a novel insight into monitoring external physical load in other sporting activities.

Evaluating the influence of a constraint manipulation on technical, tactical and physical athlete behaviour

Evaluating practice design is an important component of supporting skill acquisition and improving team-sport performance. Constraint manipulations, including creating a numerical advantage or disadvantage during training, may be implemented by coaches to influence aspects of player or team behaviour. This study presents methods to evaluate the interaction between technical, tactical and physical behaviours of professional Australian Football players during numerical advantage and disadvantage conditions within a small-sided game. During each repetition of the game, team behaviour was manually annotated to determine: repetition duration, disposal speed, total disposals, efficiency, and disposal type. Global Positioning System devices were used to quantify tactical (surface area) and physical (velocity and high intensity running) variables. A rule association and classification tree analysis were undertaken. The top five rules for each constraint manipulation had confidence levels between 73.3% and 100%, which identified the most frequent behaviour interactions. Specifically, four advantage rules involved high surface area and medium high intensity running indicating the attacking team's frequent movement solution within this constraint. The classification tree included three behaviour metrics: surface area, velocity 1SD and repetition duration, and identified two unique movement solutions for each constraint manipulation. These results may inform if player behaviour is achieving the desired outcomes of a constraint manipulation, which could help practitioners determine the efficacy of a training task. Further, critical constraint values provided by the models may guide practitioners in their ongoing constraint manipulations to facilitate skill acquisition. Sport practitioners can adapt these methods to evaluate constraint manipulations and inform practice design.

Integrating physical and tactical factors in football using positional data: a systematic review

Background

Positional data have been used to capture physical and tactical factors in football, however current research is now looking to apply spatiotemporal parameters from an integrative perspective. Thus, the aim of this article was to systematically review the published articles that integrate physical and tactical variables in football using positional data.

Methods and Materials

Following the Preferred Reporting Item for Systematic Reviews and Meta-analyses (PRISMA), a systematic search of relevant English-language articles was performed from earliest record to August 2021. The methodological quality of the studies was evaluated using the modified Downs and Black Quality Index (observational and cross-sectional studies) and the Physiotherapy Evidence Database (PEDro) scale (intervention studies).

Results

The literature search returned 982 articles (WoS = 495; PubMed = 232 and SportDiscus = 255). After screening, 26 full-text articles met the inclusion criteria and data extraction was conducted. All studies considered the integration of physical and tactical variables in football using positional data (n = 26). Other dimensions were also reported, such as psychophysiological and technical factors, however the results of these approaches were not the focus of the analysis (n = 5). Quasi-experimental approaches considered training sets (n = 20) and match contexts (n = 6). One study analysed both training and play insights. Small sided-games (SSG) were the most common training task formats in the reviewed studies, with only three articles addressing medium-sided (MSG) (n = 1) and large-sided games (LSG) (n = 2), respectively.

Conclusions

Among the current systematic review, the physical data can be integrated by player's movement speed. Positional datasets can be computed by spatial movement, complex indexes, playing areas, intra-team and inter-team dyads. Futures researches should consider applying positional data in women's football environments and explore the representativeness of the MSG and LSG.

Metabolic Power in Team and Racquet Sports: A Systematic Review with Best-Evidence Synthesis

Background

In intermittent team and racquet sports, metabolic loads are rarely investigated as they are difficult to examine, e.g., by portable metabolic carts and lactate measures. However, determining the instantaneous metabolic power of intermittent running from acceleration and speed data is possible. Recently, this potential has gained more interest in research and practice due to the development of player tracking technologies that allow easy access to the required data. The aim of this review was to systematically investigate the validity and point out the evidence of this new approach for estimating metabolic loads in intermittent sports. To provide an in-depth understanding of this approach and its validity, the fundamental aspects of the underlying concept were also considered.

Methods

PubMed®, Cochrane Library, Web of Science™, and BISp-surf databases were included in the search conducted on March 1, 2021. Studies assessing physiological and methodological validation as well as conceptual studies of the metabolic power approach in intermittent sports players without diseases or injuries were deemed eligible. The quality assessment was implemented using a modified 12-item version of the Downs and Black checklist. Additionally, a best-evidence synthesis of the validation studies was performed to clarify the direction and strength of the evidence.

Results

Of 947 studies that were identified, 31 met the eligibility criteria of which 7 were physiological, 13 methodological validation, and 11 conceptual studies. Gold standards for validating the metabolic power approach were predominantly oxygen uptake with 6 and traditional running speed analysis with 8 studies for physiological and methodological validation, respectively. The best-evidence synthesis showed conflicting to strong and moderate to strong evidence for physiological and methodological validity of the approach, respectively. The conceptual studies revealed several modifications regarding the approach that need to be considered. Otherwise, incorrect implementation can occur.

Conclusions

Evidence of the physiological validity of the metabolic power approach ranged from conflicting to strong. However, this should be treated with caution as the validation studies were often partially implemented incorrectly as shown by the underlying concept studies. Moreover, strong evidence indicated that the approach is valid from a methodological perspective. Future studies must consider what the metabolic power approach can and cannot actually display.

A lack of research exists in studies concerning children, females, and team and racquet sports besides soccer and the application of more profound physiological approaches for the validation and assessment of metabolic power estimated by acceleration and speed data is needed.

Previous physiological validation studies are outdated as there have been adaptations concerning the metabolic power approach for estimating metabolic loads over recent years, and methodological validation studies revealing its superiority over the traditional running speed approach.

Distinction between walking and running, different terrains, as well as aerobic and anaerobic energy supply should be considered when assessing metabolic power in team and racquet sports.

Validation of deep learning-based markerless 3D pose estimation

Deep learning-based approaches to markerless 3D pose estimation are being adopted by researchers in psychology and neuroscience at an unprecedented rate. Yet many of these tools remain unvalidated. Here, we report on the validation of one increasingly popular tool (DeepLabCut) against simultaneous measurements obtained from a reference measurement system (Fastrak) with well-known performance characteristics. Our results confirm close (mm range) agreement between the two, indicating that under specific circumstances deep learning-based approaches can match more traditional motion tracking methods. Although more work needs to be done to determine their specific performance characteristics and limitations, this study should help build confidence within the research community using these new tools.

Predicting the in-game status in soccer with machine learning using spatiotemporal player tracking data

An important structuring feature of a soccer match is the in-game status, whether a match is interrupted or in play. This is necessary to calculate performance indicators relative to the effective playing time or to find standard situations, ball actions, and other tactical structures in spatiotemporal data. Our study explores the extent to which the in-game status can be determined using time-continuous player positions. Therefore, to determine the in-game status we tested four established machine learning methods: logistic regression, decision trees, random forests, and AdaBoost. The models were trained and evaluated using spatiotemporal data and manually annotated in-game status of 102 matches in the German Bundesliga. Results show up to 92% accuracy in predicting the in-game status in previously unknown matches on frame level. The best performing method, AdaBoost, shows 81% precision for detecting stoppages (longer than 2 s). The absolute time shift error at the start was ≤ 2 s for 77% and 81% at the end for all correctly predicted stoppages. The mean error of the in-game total distance covered per player per match using the AdaBoost in-game status prediction was − 102 ± 273 m, which is 1.3% of the mean value of this performance indicator (7939 m). Conclusively, the prediction quality of our model is high enough to provide merit for performance diagnostics when teams have access to player positions (e.g., from GPS/LPM systems) but no human-annotated in-game status and/or ball position data, such as in amateur or youth soccer.

Float like a Butterfly: Comparison between Off and On-Ice Torso Kinematics during the Butterfly Stance in Ice Hockey Goalkeepers

In ice hockey, the butterfly style/stance is a technique distinguished by the goalkeepers (goalie) dropping to their knees to block attempts to score. Although this goalie style has been around for many years, comparisons between on and off-ice attire has not been undertaken. Therefore, this preliminary study compared differences in torso acceleration and energy expenditure by way of the Metabolic Equivalent of Task (MET) during off-ice and on-ice butterfly stances/saves. Seven participants each performed 8 on-ice butterfly saves/stances whilst wearing full hockey attire followed by 8 off-ice butterfly stances without wearing full hockey attire whilst torso acceleration was collected. The off-ice movement significantly increased vertical torso acceleration (p < 0.01, d > 0.90) with increased MET, compared to on-ice motion. Despite no significant difference in anteroposterior and mediolateral torso kinematics, vector magnitudes were significantly greater (p < 0.01, d > 0.90) when the stance was performed off-ice. The increased vertical acceleration observed when goalies performed the movement off-ice could be due to a failure to maintain adequate posture without the support of the external load. The results of this study may help inform off-ice training interventions for ice hockey goalkeeping.

High metabolic load distance in professional soccer according to competitive level and playing positions

Background

High metabolic load distance provides global information about the soccer players' total high-intensity activities. Thus, this study aimed to examine the Spanish professional soccer players' high metabolic load distance profile, comparing competitive level and playing positions.

Methods

A total of 18,131 individual match observations were collected from outfield players competing during the 2018/2019 and 2019/20 seasons in the First and Second Spanish Professional Soccer Leagues (LaLiga™). High Metabolic Load Distance (HMLD; distance covered with a power consumption above 25.5 W·kg^-1 and accelerations or decelerations (e.g., accelerating from 2 to 4 m·s^-2 for 1 s) were included), and HMLD per minute (HMLD_min) were analyzed by the ChryonHego^® video-tracking system. Players were classified according to their playing position as follows: Central Backs (CB), Full Backs (FB), Center Midfields (CM), Wide Midfields (WM), and Forwards (FW).

Results

No differences between competitive levels were found in any variable when all players were analyzed conjointly except for HMLD_min overall and during the second half. However, when playing positions were considered, differences between competitive levels were observed in all positions, mainly in HMLD and HMLD during the first-half variables. In addition, several differences between playing positions were observed, with CB presenting the lowest values in all variables compared to their counterparts in both competitive levels, whereas CM in First Division and WM in Second Division showed the highest values in the HMLD variables.

Discussion

The findings are of interest to analyze the HMLD in professional soccer players, enabling the adaptation and individualization of training in this population according to the competitive level and specific playing position of each player.

VALIDATION AND RELIABILITY BETWEEN EXTERNAL LOAD ANALYSIS DEVICES FOR SOCCER PLAYERS

ABSTRACT Objective: To test the reliability between two instruments with different analysis mechanisms, either by GPS (model GPSPORTS®) or by video analysis (InStat For Players®), relating the results of total distance covered and distance at high speed ≥ 20km/h (Very High-Intensity Running Distance, VHIR) during official soccer matches. Study Design: This is a methodological study. Data from 35 male professional soccer athletes from all tactical positions were included. Age 29.2 (± 4.8 years) and body fat 9.9 (± 1.7%), excluding goalkeepers (102 individual analyzes) were collected in official matches. In the data analysis, descriptive statistics procedures were used to characterize the sample and the intraclass correlation coefficient (ICC) was used to verify the agreement on the stability and internal consistency of the tests with 95% confidence intervals (CI). Results: The ICC in the case of the total distance traveled variable was significant 0,914 (0,876; 0,941) and indicated a very high agreement, with the linear correlation coefficient indicating a strong positive correlation (p <0.001). The ICC for the VHIR variable was not significant, although the linear correlation coefficient indicates a strong positive correlation (p <0.001). Clinical Relevance Statment: This study reveals that there is good agreement in the comparison of two systems designed to analyze the movement demands of each professional soccer athlete in relation to the total distance covered. Level of Evidence I; Methodological Study - Investigation of a diagnostic test.

Techniques to derive and clean acceleration and deceleration data of athlete tracking technologies in team sports: A scoping review

The application of acceleration and deceleration data as a measure of an athlete's physical performance is common practice in team sports. Acceleration and deceleration are monitored with athlete tracking technologies during training and games to quantify training load, prevent injury and enhance performance. However, inconsistencies exist throughout the literature in the reported methodological procedures used to quantify acceleration and deceleration. The object of this review was to systematically map and provide a summary of the methodological procedures being used on acceleration and deceleration data obtained from athlete tracking technologies in team sports and describe the applications of the data. Systematic searches of multiple databases were undertaken. To be included, studies must have investigated full body acceleration and/or deceleration data of athlete tracking technologies. The search identified 276 eligible studies. Most studies (60%) did not provide information on how the data was derived and what sequence of steps were taken to clean the data. Acceleration and deceleration data were commonly applied to quantify and describe movement demands using effort metrics. This scoping review identified research gaps in the methodological procedures and deriving and cleaning techniques that warrant future research focussing on their effect on acceleration and deceleration data.

Physical Performance Indicators and Team Success in the German Soccer League

The aims of this study were (1) to determine the match running performance required by different teams based on their final ranking position and (2) to analyze the association between match running performance variables and team success at the end of the season. A total of 1,224 match observations from professional soccer teams competing during two consecutive seasons in the German Bundesliga were analyzed. In addition, the final league ranking position and the total of points obtained by each team at the end of the season were registered for the analysis of the association between team success and match running performance. The main findings were that high ranked teams covered the greatest total distance with ball possession, sprinting distance with ball possession, and completed the greatest number of sprinting actions with ball possession and maximal velocity. Moreover, total distance covered with possession of the ball and maximal velocity were the most important variables to predict the total of points obtained at the end of the season. Specifically, the relative contribution of total distance covered with ball possession to the total of points obtained was greater than maximal velocity. Training programs for professional soccer players should be focused on improving the sprint capacity and running with possession of the ball (e.g., transitional tasks and small-sided games). Moreover, this has implications for injury prevention, physical, psychological, and technical-tactical training since today’s soccer requires players to engage in repeated high-intensity actions, reach maximum speeds above 9 m/s, and develop technical-tactical coordination when running with the ball.

Transfering Targeted Maximum Likelihood Estimation for Causal Inference into Sports Science

Although causal inference has shown great value in estimating effect sizes in, for instance, physics, medical studies, and economics, it is rarely used in sports science. Targeted Maximum Likelihood Estimation (TMLE) is a modern method for performing causal inference. TMLE is forgiving in the misspecification of the causal model and improves the estimation of effect sizes using machine-learning methods. We demonstrate the advantage of TMLE in sports science by comparing the calculated effect size with a Generalized Linear Model (GLM). In this study, we introduce TMLE and provide a roadmap for making causal inference and apply the roadmap along with the methods mentioned above in a simulation study and case study investigating the influence of substitutions on the physical performance of the entire soccer team (i.e., the effect size of substitutions on the total physical performance). We construct a causal model, a misspecified causal model, a simulation dataset, and an observed tracking dataset of individual players from 302 elite soccer matches. The simulation dataset results show that TMLE outperforms GLM in estimating the effect size of the substitutions on the total physical performance. Furthermore, TMLE is most robust against model misspecification in both the simulation and the tracking dataset. However, independent of the method used in the tracking dataset, it was found that substitutes increase the physical performance of the entire soccer team.

Reliability of spatial-temporal metrics used to assess collective behaviours in football: An in-silico experiment

The purpose of this study was to investigate the reliability of spatial-temporal measurements applied within collective behaviour research in football. In-silico experiments were conducted introducing positional errors (0.5, 2 and 4 m) representative of commercial tracking systems to match data from the 2020 European Championship qualifiers. Ratios of the natural variance ("signal") of spatial-temporal metrics obtained throughout sections of each game relative to the variance created by positional errors ("noise") were taken to calculate reliability. The effects of error magnitude and time of analysis (1, 5 and 15 mins; length of attack: <10, 10-20, >20 s) were assessed and compared using Cohen's f² effect size. Error magnitude was found to exert greater influence on reliability (f² = 0.15 to 0.81) compared with both standard time of analysis (f² = 0.03 to 0.08) and length of attacks (f² = 0.15 to 0.32). the results demonstrate that technologies generating positional errors of 0.5 m or less should be expected to produce spatial-temporal metrics with high reliability. However, technologies that generate errors of 2 m or greater may produce unreliable values, particularly when analyses are conducted over discrete events such as attacks, which although critical, are often short in duration.

Validation of a LiDAR-based player tracking system during football-specific tasks

Tracking players’ movements in sports is important to monitor and optimise exercise volume, avoid injuries, and enhance game performance. A new LiDAR-based system (Sportlight®) purports to provide accurate velocity and acceleration metrics derived from player movements. This study examined the validity of the LiDAR-based system against a 3D motion analysis system. Two competitive football players (age: 18 years, height: 1.74 ± 0.01 m, mass: 66.5 ± 7.8 kg; playing experience at this level: 3 years) completed nine trials each of six sport-specific movements, consisting of straight-line sprints, cuts, and curved runs. Trials were recorded concurrently by a four-unit LiDAR system and a 64-camera 3D motion analysis system. Instantaneous velocity and acceleration, and time spent within key performance indicator bands (defined by velocity and acceleration thresholds) were compared between systems. Agreement between the systems was evaluated by root mean square error. Differences in time spent within each key performance indicator band between systems were assessed with t tests and standardised effect sizes. Velocity root mean square error values ranged from 0.04 to 0.14 m·s−1 across all movements and acceleration root mean square error values ranged from 0.16 to 0.7 m·s−2. Differences between systems for time spent within each key performance indicator band were mostly trivial. These results show that the LiDAR-based system can provide valid measures of velocity and acceleration in football-specific tasks, thus providing accurate tracking of players and calculation of relevant key performance indicators.

Drone-Based Position Detection in Sports-Validation and Applications

Radio and video-based electronic performance and tracking systems (EPTS) for position detection are widely used in a variety of sports. In this paper, the authors introduce an innovative approach to video-based tracking that uses a single camera attached to a drone to capture an area of interest from a bird’s eye view. This pilot validation study showcases several applications of this novel approach for the analysis of game and racket sports. To this end, the authors compared positional data retrieved from video footage recorded using a drone with positional data obtained from established radio-based systems in three different setups: a tennis match during training with the drone hovering at a height of 27 m, a small-sided soccer game with the drone at a height of 50 m, and an Ultimate Frisbee match with the drone at a height of 85 m. For each type of playing surface, clay (tennis) and grass (soccer and Ultimate), the drone-based system demonstrated acceptable static accuracy with root mean square errors of 0.02 m (clay) and 0.15 m (grass). The total distance measured using the drone-based system showed an absolute difference of 2.78% in Ultimate and 2.36% in soccer, when compared to an established GPS system and an absolute difference of 2.68% in tennis, when compared to a state-of-the-art LPS. The overall ICC value for consistency was 0.998. Further applications of a drone-based EPTS and the collected positional data in the context of performance analysis are discussed. Based on the findings of this pilot validation study, we conclude that drone-based position detection could serve as a promising alternative to existing EPTS but would benefit from further comparisons in dynamic settings and across different sports.

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.

Comparative Analysis of Optoelectronic Accuracy in the Laboratory Setting Versus Clinical Operative Environment: A Systematic Review

STUDY DESIGN

Systematic review.

OBJECTIVES

The optoelectronic camera source and data interpolation process serve as the foundation for navigational integrity in robotic-assisted surgical platforms. The current systematic review serves to provide a basis for the numerical disparity observed when comparing the intrinsic accuracy of optoelectronic cameras versus accuracy in the laboratory setting and clinical operative environments.

METHODS

Review of the PubMed and Cochrane Library research databases was performed. The exhaustive literature compilation obtained was then vetted to reduce redundancies and categorized into topics of intrinsic accuracy, registration accuracy, musculoskeletal kinematic platforms, and clinical operative platforms.

RESULTS

A total of 465 references were vetted and 137 comprise the basis for the current analysis. Regardless of application, the common denominators affecting overall optoelectronic accuracy are intrinsic accuracy, registration accuracy, and application accuracy. Intrinsic accuracy equaled or was less than 0.1 mm translation and 0.1 degrees rotation per fiducial. Controlled laboratory platforms reported 0.1 to 0.5 mm translation and 0.1 to 1.0 degrees rotation per array. Accuracy in robotic-assisted spinal surgery reported 1.5 to 6.0 mm translation and 1.5 to 5.0 degrees rotation when comparing planned to final implant position.

CONCLUSIONS

Navigational integrity and maintenance of fidelity of optoelectronic data is the cornerstone of robotic-assisted spinal surgery. Transitioning from controlled laboratory to clinical operative environments requires an increased number of steps in the optoelectronic kinematic chain and error potential. Diligence in planning, fiducial positioning, system registration and intra-operative workflow have the potential to improve accuracy and decrease disparity between planned and final implant position.

Effects of Chronological Age, Relative Age, and Maturation Status on Accumulated Training Load and Perceived Exertion in Young Sub-Elite Football Players

The aims of this study were 1) to analyze the influence of chronological age, relative age, and biological maturation on accumulated training load and perceived exertion in young sub-elite football players and 2) to understand the interaction effects amongst age grouping, maturation status, and birth quartiles on accumulated training load and perceived exertion in this target population. A 6-week period (18 training sessions and 324 observation cases) concerning 60 young male sub-elite football players grouped into relative age (Q1 to Q4), age group (U15, U17, and U19), and maturation status (Pre-peak height velocity (PHV), Mid-PHV, and Post-PHV) was established. External training load data were collected using 18 Hz global positioning system technology (GPS), heart-rate measures by a 1 Hz short-range telemetry system, and perceived exertion with total quality recovery (TQR) and rating of perceived exertion (RPE). U17 players and U15 players were 2.35 (95% CI: 1.25–4.51) and 1.60 (95% CI: 0.19–4.33) times more likely to pertain to Q1 and Q3, respectively. A negative magnitude for odds ratio was found in all four quartile comparisons within maturation status (95% CI: 6.72–0.64), except for Mid-PHV on Q2 (95% CI: 0.19–4.33). Between- and within-subject analysis reported significant differences in all variables on age group comparison measures (F = 0.439 to 26.636, p = 0.000 to 0.019, η2 = 0.003–0.037), except for dynamic stress load (DSL). Between-subject analysis on maturity status comparison demonstrated significant differences for all training load measures (F = 6.593 to 14.424, p = 0.000 to 0.037, η2 = 0.020–0.092). Interaction effects were found for age group x maturity band x relative age (Λ Pillai’s = 0.391, Λ Wilk’s = 0.609, F = 11.385, p = 0.000, η2 = 0.391) and maturity band x relative age (Λ Pillai’s = 0.252, Λ Wilk’s = 0.769, F = 0.955, p = 0.004, η2 = 0.112). Current research has confirmed the effects of chronological age, relative age, and biological maturation on accumulated training load. Perceived exertion does not seem to show any differences concerning age group or maturity status. Evidence should be helpful for professionals to optimize the training process and young football players’ performance.

Return to match running performance after a hamstring injury in elite football: a single-centre retrospective cohort study

Objectives

To determine the number of matches to return to pre-injury match running performance after sustaining an acute hamstring injury.

Methods

In this retrospective cohort study, the injuries of the players of the first, Under21, Under19, Under18 and Under17 teams of a professional football club in the period 2017-2020 were analysed. Acute hamstring injuries with a minimal absence from training or match play of 7 days were included. For running performance, we assessed the following variables: maximal velocity (km/hour), total distance, high-intensity distance (17.5-22.5 km/hour) and sprint distance (>22.5 km/hour). We calculated the average and 95% CI for these variables during the last five matches before the injury. The primary outcome was the number of matches to reach maximal velocity within the 95% CI of the player's individual pre-injury performance. Secondary outcome scores included the duration (in days and matches) to reach the other running performance variables.

Results

18 hamstring injuries in 15 players were included. 15 out of 18 injuries (83%) showed a return to pre-injury maximal velocity in the second match after return to play. The median number of matches to return to pre-injury maximal velocity was 2 (IQR 1-2). In the first match after return to play, pre-injury total distance was reached in 100% of the injuries, pre-injury sprint distance was reached in 94% of the injuries and pre-injury high-intensity distance was reached in 89% of the injuries.

Conclusion

Following an acute hamstring injury in elite football, pre-injury match running performance is reached in the first or second match.