High-Performance Handball Player's Time-Motion Analysis by Playing Positions

Is Match Playing Time a Potential Tool for Managing Load in Women's Handball?

ABSTRACT

García-Sánchez, C, Navarro, RM, Nieto-Acevedo, R, and de la Rubia, A. Is match playing time a potential tool for managing load in women's handball? J Strength Cond Res XX(X): 000-000, 2024-The aim of this study was to explore the external load experienced by female handball players according to the time played in official matches (≥40, <40, and ≤20 minutes) and in relation to playing positions (backs, pivots, and wings). Twenty-two female players from the Spanish second Division were monitored across 13 matches. Total distance covered, high-speed running distance (HSR), accelerations, decelerations, and PlayerLoad were collected in absolute and relative values using a local positioning system (WIMU PRO, Realtrack Systems SL, Almería, Spain). One-way ANOVA with partial eta-squared and Cohen's d were used to determine the differences between playing time groups and between playing positions. This study revealed that players with more match playing time had a higher absolute values in all external load variables (p < 0.001; very large effects), except in HSR where only wings showed higher values according to the time played (p < 0.001; very large effects). However, these differences between playing time groups disappear when the external load values were normalized according to the effective playing time (p > 0.05). In relation to playing positions, wings covered more HSR/minutes than the other playing positions regardless of the playing time (p < 0.05; large effects). In addition, backs performed more ACC/minutes than wings in the high playing time group and more than pivots in the low playing time group (p < 0.05, moderate effects). In addition, backs performed more DEC/minutes than wings in the low playing time group (p < 0.05, moderate effects). Therefore, handball coaches should consider the playing time as an effective tool to optimize the weekly load distribution.

Unraveling athletic performance: Transcriptomics and external load monitoring in handball competition

OBJECTIVE

This study aims to comprehend the impact of handball practice on sub-elite athletes by investigating transcriptomic changes that occur during a match. The primary focus encompasses a dual objective: firstly, to identify and characterize these transcriptomic alterations, and secondly, to establish correlations between internal factors (gene expression), and external loads measured through Electronic Performance and Tracking Systems (EPTS variables). Ultimately, this comprehensive analysis seeks to evaluate both acute and chronic responses to exercise within the context of handball training.

METHODS

The study included sixteen elite male athletes from the FC Barcelona handball second team. Blood samples were extracted at three different time points: before the match at baseline levels (T1), immediately upon completion (T2), and 24 hours after completion (T3). Differential gene expression, Gene Ontology Term and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were conducted in two comparisons: Comparison 1 (T1 vs T2) and Comparison 2 (T1 vs T3). Further, the correlation between gene expression levels and training variables (external load) was conducted.

RESULTS

In T1 vs T2, 3717 of the 14632 genes detected were differentially expressed (adjusted p-value < 0.05), and enrichment of terms related to the immune system, mitochondria, and metabolic processes was found. Further, significant linear correlations were obtained between High-Speed running (HSR) and high-intensity variables such as acceleration ACC and deceleration DEC values with amino acids, and inflammatory and oxidative environment-related pathways, both in chronic and acute response.

CONCLUSIONS

This research highlights the effects of external workload on elite athletes during a handball match and throughout the season. The study identifies deregulation in the immune system, mitochondrial functions, and various metabolic pathways during the match. Additionally, it establishes correlations between the external load and pathways associated with amino acids, inflammation, oxidative environment, and regulation. These findings offer insights into the immediate and chronic responses of athletes to physical effort.

Relationship between team ranking and physical fitness in elite male handball players in different playing positions

The aim of this study was to identify the key physical indicators that affect game performance of male team handball athletes in national team handball tournaments and explore them further in relation to playing positions. A total of 150 male handball athletes were tested before a national tournament, using squat, bench press, 30-m sprint, vertical jump, pull-ups and abdominal endurance testing. Correlation analysis was used to examine the potential relationship between fitness level and tournament ranking. The results revealed significant differences in fitness variables among different playing positions (p < 0.05), excepted abdominal endurance and vertical jump (p > 0.05). 1RM squad performance was associated with team rankings (r = 0.289, p < 0.05). For individual playing positions, bench press of backs correlate with rankings (r = 0.354, p < 0.05). For goalkeepers, ranking was significantly positively correlated with 30-m sprinting (r = 0.604, p < 0.05). No other correlations were found (p > 0.05). To conclude, fitness level is to some extent related to team ranking with higher ranked teams having better scores in some of the fitness tests for all playing positions. The key predictors of performance in sport vary from position to position and practitioners need to differentiate between them to organize strength and conditioning training more precisely. More specialized fitness tests are also needed to assess athletes' competition ability.

Improving Balance and Movement Control in Fencing Using IoT and Real-Time Sensorial Feedback

Fencing, a sport emphasizing the equilibrium and movement control of participants, forms the focal point of inquiry in the current study. The research endeavors to assess the efficacy of a novel system designed for real-time monitoring of fencers' balance and movement control, augmented by modules incorporating visual feedback and haptic feedback, to ascertain its potential for performance enhancement. Over a span of five weeks, three distinct groups, each comprising ten fencers, underwent specific training: a control group, a cohort utilizing the system with a visual real-time feedback module, and a cohort using the system with a haptic real-time feedback module. Positive outcomes were observed across all three groups, a typical occurrence following a 5-week training regimen. However, noteworthy advancements were particularly discerned in the second group, reaching approximately 15%. In contrast, the improvements in the remaining two groups were below 5%. Statistical analyses employing the Wilcoxon signed-rank test for repeated measures were applied to assess the significance of the results. Significance was solely ascertained for the second group, underscoring the efficacy of the system integrated with visual real-time feedback in yielding statistically noteworthy performance enhancements.

Worst-case scenario analysis of physical demands in elite men handball players by playing position through big data analytics

The physical demands of intermittent sports require a preparation based, by definition, on high-intensity actions and variable recovery periods. Innovative local positioning systems make it possible to track players during matches and collect their distance, speed, and acceleration data. The purpose of this study was to describe the worst-case scenarios of high-performance handball players within 5-minute periods and per playing position. The sample was composed of 180 players (27 goalkeepers, 44 wings, 56 backs, 23 centre backs and 30 line players) belonging to the first eight highest ranked teams participating in the European Men's Handball Championship held in January 2022. They were followed during the 28 matches they played through a local positioning system worn on their upper bodies. Total and high-speed distance covered (m), pace (m/min), player load (a.u.) and high-intensity accelerations and decelerations (n) were recorded for the twelve 5-min periods of each match. Data on full-time player average and peak demands were included in the analysis according to each playing position. A systematic three-phase analysis process was designed: 1) information capture of match activities and context through sensor networks, the LPS system, and WebScraping techniques; 2) information processing based on big data analytics; 3) extraction of results based on a descriptive analytics approach. The descriptive cross-sectional study of worst-case scenarios revealed an ~17% increment in total distance covered and pace, with a distinct ~51% spike in high-intensity actions. Significant differences between playing positions were found, with effect sizes ranging from moderate to very large (0.7-5.1). Line players, in particular, showed a lower running pace peak (~10 m/min) and wings ran longer distances at high speed (> 4.4 m/s) than the rest of the field players (~76 m). The worst-case scenario assessment of handball player locomotion demands will help handball coaches and physical trainers to design tasks that replicate these crucial match moments, thus improving performance based on a position-specific approach.

Analysis of contextualized intensity in Men's elite handball using graph-based deep learning

Manual annotation of data in invasion games is a costly task which poses a natural limit on sample sizes and the level of granularity used in match and performance analyses. To overcome this challenge, this work introduces FAUPA-ML, a Framework for Automatic Upscaled Performance Analysis with Machine Learning, which leverages graph neural networks to scale domain-specific expert knowledge to large data sets. Networks were trained using position data of match phases (counter/position attacks), annotated manually by domain experts in 10 matches. The best network was applied to contextualize N = 539 matches of elite handball (2019/20-2021/22 German Men's Handball Bundesliga) with 86% balanced accuracy. Distance covered, speed, metabolic power, and metabolic work were calculated for attackers and defenders and differences between counters and position attacks across seasons analyzed with an ANOVA. Results showed that counter attacks are shorter, less frequent and more intense than position attacks and that attacking is more intense than defending. Findings show that FAUPA-ML generates accurate replications of expert knowledge that can be used to gain insights in performance analysis previously deemed infeasible. Future studies can use FAUPA-ML for large-scale, contextualized analyses that investigate influences of team strength, score-line, or team tactics on performance.

A deep dive into the use of local positioning system in professional handball: Automatic detection of players' orientation, position and game phases to analyse specific physical demands

The objective of this study is to automate and analyse the quantification of external load during an elite men's handball match. This study was carried out using data from a local positioning system and inertial measurement units. The literature review leads us to assume that physical demands are different depending on position, player specialty and phases of the game. In order to do this analysis, raw data was used from professional competitors of a Spanish club during National and European competition matches. First, a game phase algorithm was designed to automate phase recognition. Then, a descriptive evaluation of the means and standard deviation was performed with the following variables: total distance, total time, total Accel'Rate, the percentages of distance and time per speed and displacement direction. A Kruskal Wallis test was applied to normalized distance and normalized Accel'Rate. Defensive play showed the highest values on covered distance (930.6 ± 395.0 m). However, normalized distance showed significant differences (p<0.05) across all phases with defensive play (558.8 ± 53.9 m/10min) lower than offensive play (870.3 ± 145.7 m/10min), offensive transition (1671.3 ± 242.0 m/10min) or defensive transition (1604.5 ± 242.0 m/10min). Regarding position, wing players covered the most distance (2925.8 ± 998.8 m) at the second highest intensity (911.4 ± 63.3 m/10min) after offensive back players (1105.0 ± 84.9 m/10min). Significant difference in normalized requirements were found between each playing position: goalkeepers, wings, versatile backs, versatile line players, offensive backs and defensive backs (p<0.05), so a separation between offensive or defensive specialists is plausible and necessary. In conclusion, as physical demands differ for each game phase, activity profile among players is modulated by their playing position and their specialty (offense, defense or none). This study may help to create individual training programs according to precise on-court demands.

Metabolic power in the men's European handball championship 2020

PURPOSE

To ascertain the typical metabolic power characteristics of elite handball players of different positions, and whether changes occur within matches.

METHODS

414 elite male handball players were included. During all 65 matches of the EURO 2020, local positioning system data were collected, yielding 1853 datasets. Field players were categorised into six positional groups: centre backs (CB), left/right wings (LW/RW), left/right backs (LB/RB) and pivots (P). Metabolic power, total energy expenditure, high-power energy, and the equivalent distance index were calculated. We used linear mixed models with players as random and positions as fixed effects models. Intensity models adjusted for time-dependency by incorporating the duration of play.

RESULTS

LW/RW spent most time on the court, expanded most total energy, and most relative energy per kg body weight in the high-intensity categories. CB played at the highest mean metabolic power (7.85 W/kg; CI_95% [7.67, 8.03]). Playing intensity decreased by 2.5% (0.2 kJ/kg/s; CI_95% [0.17, 0.23]) per 10 min played.

CONCLUSION

Positional differences in metabolic power parameters exist. In general, wing players had the highest volume and CB the highest intensity of match-play. Analysis of metabolic intensity in handball should take position and players' time on the court into account.

Analysis of Motion Characteristics and Metabolic Power in Elite Male Handball Players

While handball is characterized by repeated sprints and changes of direction, traditional player load models do not consider accelerations and decelerations. The aim of this study was to analyze the differences between metabolic power and speed zones for player load assessment with regard to the player role. Position data from 330 male individuals during 77 games from the 2019/20 German Men's Handball-Bundesliga (HBL) were analyzed, resulting in 2233 individual observations. Players were categorized into wings, backs and pivots. Distance covered in different speed zones, metabolic power, metabolic work, equivalent distance (metabolic work divided by energy cost of running), time spend running, energy spend running, and time over 10 and 20 W were calculated. A 2-by-3 mixed ANOVA was calculated to investigate differences and interactions between groups and player load models. Results showed that total distance was longest in wings (3568 ± 1459 m in 42 ± 17 min), followed by backs (2462 ± 1145 m in 29 ± 14 min), and pivots (2445 ± 1052 m in 30 ± 13 min). Equivalent distance was greatest in wings (4072.50 ± 1644.83 m), followed by backs (2765.23 ± 1252.44 m), and pivots (2697.98 ± 1153.16 m). Distance covered and equivalent distance showed moderate to large interaction effects between wings and backs (p < .01, ES = 0.73) and between wings and pivots (p < .01, ES = 0.86) and a small interaction effect between backs and pivots (p < .01, ES = 0.22). The results underline the need for individualized management of training loads and the potential of using information about locomotive accelerations and decelerations to obtain more precise descriptions of player load during handball game performance at the highest level of competition. Future studies should investigate the influence of physical performance on smaller match sequences, like ball possession phases.

Physical match demands of four LIQUI-MOLY Handball-Bundesliga teams from 2019-2022: effects of season, team, match outcome, playing position, and halftime

Introduction

Due to the development in team handball, there is a need to optimize the physical capacities of team handball players for which knowledge of the physical match demands is essential. The aim of this study was to investigate the physical match demands of four LIQUI-MOLY Handball-Bundesliga (HBL) teams across three seasons with respect to the effects of season, team, match outcome, playing position, and halftime.

Methods

A fixed installed local positioning system (Kinexon) was used, collecting 2D positional and 3D inertial measurement unit data at 20 and 100 Hz, respectively. The physical match demands were operationalized by basic (e.g., distance, speed, and acceleration) and more advanced variables (e.g., jumps, throws, impacts, acceleration load, and metabolic power). A total of 347 matches (213 with an additional ball tracking) were analyzed from four teams (one top, two middle, and one lower ranked) during three consecutive seasons (2019-2022). One-way ANOVAs were calculated to estimate differences between more than two groups (e.g., season, team, match outcome, playing position). Mean differences between halftimes were estimated using Yuen's test for paired samples.

Results

Large effects were detected for the season (0.6≤ξ^≤0.86), team (0.56≤ξ^≤0.72), and playing position (0.64≤ξ^≤0.98). Medium effects were found for match outcome (ξ^≤0.36) and halftime (ξ^≤0.47).

Conclusion

For the first time, we provide a comprehensive analysis of physical match demands in handball players competing in the LIQUI-MOLY Handball-Bundesliga. We found that physical match demands differ on that top-level with up to large effect sizes concerning the season, team, match outcome, playing position, and halftime. Our outcomes can help practitioners and researchers to develop team and player profiles as well as to optimize talent identification, training, regeneration, prevention, and rehabilitation procedures.

Physical Demands during Official Competitions in Elite Handball: A Systematic Review

An understanding of physical demands during official competitions is essential to achieving the highest performance in handball. The aim of this systematic review was to summarise the available scientific evidence associated with physical demands during official competitions in elite handball according to playing positions, competition level and gender. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, 17 studies were selected after a systematic search and selection process of three digital databases: PubMed, Web of Science and Sport Discus. The quality of the selected studies was evaluated using the Strengthening the Reporting of Observational Studies in Epidemiology checklist; the average score was 18.47 points. The sample consisted of 1175 handball players, of whom 1042 were men (88.68%) and 133 were women (11.32%). The results show that an elite handball player covered on average 3664.4 ± 1121.6 m during a match. The average running pace was 84.8 ± 17.2 m∙min-1. The total distance covered was largely greater in national competitions (4506.7 ± 647.9 m) compared with international competitions (2190.3 ± 1950.5 m) (effect size (ES) = 1.2); however, the running pace did not present any significant difference between the international or national level (ES = 0.06). In regard to gender, the total distance covered was moderately greater in female competitions (4549.1 ± 758.6 m) compared with male competitions (3332.6 ± 1257.7 m) (ES = 0.9), and the running pace was largely greater in female competitions (110.5 ± 7.2 m∙min-1) compared with male competitions (78.4 ± 19.7 m∙min-1) (ES = 1.6). In relation to playing position, backs and wings covered a moderately greater total distance (ES = 0.7 and 0.6) and slightly more meters per minute (ES = 0.4 and 0.2) than pivots. Moreover, the technical activity profile differed between playing positions. Backs performed moderately more throws than pivots and wings (ES = 1.2 and 0.9), pivots exhibited largely more body contact than backs and wings, and wings performed moderately more fast breaks (6.7 ± 3.0) than backs (2.2 ± 2.3) (ES = 1.8). Therefore, this research study provides practical applications for handball coaches and strength and conditioning professionals with respect to designing and implementing more individualised training programmes to maximise performance and reduce injury risk.

Position-Specific Comparison of the Player Loads and High-Intensity Events During Match in Male and Female Handball Players

Amaç: Kısa süreli yüksek şiddetli aktiviteler içeren hentbolda fiziksel ve fizyolojik özellikler ile atış hızı parametrelerinde cinsiyet farkı açıkça gösterilmiştir. Bu tür performans parametreleri dışında branşa ait gerçek zamanlı maç verisi elde etmek metodolojik kısıtlılıklar içermektedir. Ancak, son dönemde giyilebilir teknolojilerle kapalı alan takım sporlarında oyuncu yükünü daha detaylı incelemek mümkündür. Bu çalışmanın amacı hentbolda maç sırasında oyuncu yükünü kadın ve erkek oyuncularda pozisyonlara göre karşılaştırmaktır.Yöntem: Çalışmaya hazırlık turnuvasına katılan 2 erkek ve 2 kadın toplam 4 Türkiye Hentbol Süper Lig takımından 42 saha oyuncusu (20 kadın ve 22 erkek) gönüllü olarak katılmıştır. Kaleciler ve toplam oyun süresi 10 dakikanın altında kalan saha oyuncuları analize dahil edilmemiştir. Müsabaka öncesi kişiye tanımlanmış İnersiyal Ölçüm Ünitesi (IMU) sensörleri (OptimEye S5, Catapult Sports, Avustralya) firmanın özel yeleği ile üst gövde arkasına sabitlenmiş ve kalp atım hızı monitörizasyonu için göğüs bandı (Polar T31 Coded, Finlandiya) takılmıştır. Toplanan verilerde sporcu değişimi (yedek bankında geçen süre) ve oyun duraksamaları (aktif oyun süresi) firmanın yazılımıyla (OpenField, Catapult Sports, Avustralya) işaretlenerek filtrelenmiştir.Bulgular: Her iki cinsiyet için aktif oyun süreleri benzer olmasına rağmen oyuncu yükü ve kalp atım hızı yanıtları arasında anlamlı fark bulunmuştur. Kadın hentbolcularda toplam oyuncu yükü ve ortalama oyuncu yükü erkeklere göre daha yüksek iken erkek hentbolcularda pik oyuncu yükü istatistiksel olarak daha yüksek bulunmuştur (265.50±93.06 PL total, 255.80±81.59 PL total; 8.30±1.27 PL/dak, 8.07±1.64 PL/dak). Benzer olarak oyuncu yükü yoğunluk bölgelerinde erkekler kadınlara göre düşük seviye bölgelerde daha az, yüksek seviye bölgelerde daha çok oyuncu yükü eforu göstermiştir. İç yük yanıtları kadın hentbolcuların kalp atım hızı tükenme parametresinde erkeklere göre anlamlı yüksek bulunmuştur.Sonuç: Bu araştırma bulguları hentbol branşındaki çoğu anahtar performans belirteçlerindeki cinsiyet farkının maç sırasında oyuncu yükünde de literatürle uyumlu olarak anlamlı farklılıklar olduğunu göstermiştir. Ancak, daha yüksek sayıda maçın dahil edildiği ve rekabetin daha yüksek olduğu lig düzeyindeki maçlardan toplanacak verilere ihtiyaç duyulmaktadır. 

Contextualizing Physical Data in Professional Handball: Using Local Positioning Systems to Automatically Define Defensive Organizations

In handball, the way the team organizes itself in defense can greatly impact the player's activity and displacement during the play, therefore impacting the match demands. This paper aims (1) to develop an automatic tool to detect and classify the defensive organization of the team based on the local positioning system data and check its classification quality, and (2) to quantify the match demands per defensive organization, i.e., defining a somehow cost of specific defensive organizations. For this study, LPS positional data (X and Y location) of players from a team in the Spanish League were analyzed during 25 games. The algorithm quantified the physical demands of the game (distance stand, walk, jog, run and sprint) broken down by player role and by specific defensive organizations, which were automatically detected from the raw data. Results show that the different attacking and defending phases of a game can be automatically detected with high accuracy, the defensive organization can be classified between 1-5, 0-6, 2-4, and 3-3. Interestingly, due to the highly adaptive nature of handball, differences were found between what was the intended defensive organization at a start of a phase and the actual organization that can be observed during the full defensive phase, which consequently impacts the physical demands of the game. From there, quantifying for each player role the cost of each specific defensive organization is the first step into optimizing the use of the players in the team and their recovery time, but also at the team level, it allows to balance the cost (i.e., physical demand) and the benefit (i.e., the outcome of the defensive phase) of each type of defensive organization.

Characteristics of the level of psychomotor abilities of female handball players

BACKGROUND

Handball is a high-intensity game, during which players run, change directions with or without the ball, interact with the opponent and make different decisions in both offensive and defensive actions. Players' performance may depend on a number of factors, including explosive force, power, speed and agility. Players' results may be significantly influenced by their, psychomotor abilities. This article presents an analysis of selected psychomotor abilities of female handball players at different level of competition.

METHODS

Test2Drive computer tests were used. The following four tests were used to measure psychomotor abilities: the Simple Reaction Time Test (SIRT), the Choice Reaction Time Test (CHORT), the Hand-Eye Coordination Test and the Spatial Anticipation Test (SPANT). The study covered a group of 118 female handball players (average age 19.6 ± 3.16), playing in the PGNiG Polish Women's Superliga, the Polish 1st Handball League and 2nd the Polish 2nd Handball League, in the playing positions: goalkeepers, centre players, pivot players and wing players. The study also included analyses of the players' body composition and aerobic capacity through the use of the multistage 20-m shuttle run test. In addition, the players' psychomotor abilities were analysed depending on the level of competition and playing position.

RESULTS

The analysis of the reaction time and movement time showed statistically significant differences between the results obtained by the female handball players on different levels of competition. Moreover the female players from the Polish Women's Superliga exhibited the fastest reaction times according to the SIRT, the CHORT and the SPANT. Additionally, on the basis of the linear Pearson correlation coefficient, a statistically significant relationship was determined between the players' psychomotor abilities (movement time in the SIRT, the CHORT and the SPANT) and elements of their body composition or aerobic capacity.

CONCLUSIONS

The analysis showed that the higher the level of competition (leagues), the shorter the female handball players' reaction times. The study also revealed that the players' body mass index and percentage of fat content reassociated with movement times, while their aerobic capacity (measured in the multistage 20-m shuttle run test) had a significant influence on their reaction times. This study shows that reaction time it's one of ability which should be consider to develop in training of female handball players.

Throwing performance by playing positions of male handball players during the European Championship 2020

The aim of this study was to analyze the throwing velocity and effectiveness of elite male handball players during the European Championship 2020. A local positioning system was used for the first time in a European Championship to collect 6568 throw events from 337 players of 24 national teams during 65 matches. ANOVA (F = 80.8, p < 0.01, η²  = 0.058) revealed that back players throws were significantly faster (24.3-26.5 m/s) than the rest of the players (22.2-22.5 m/s). Similarly, throws made from the central zone showed the highest speed values of 28.0 m/s (F = 43.2, p < 0.01, η²  = 0.050). In regard to the goal hit zone, higher speeds were shown for throws in side zones (24.9-26.8 m/s) compared to central zones (23.0-23.8 m/s) (F = 49.0, p < 0.01, η²  = 0.063). Effectiveness was higher in wing players (62%-64%) than the rest (45%-56%) (F = 30.9, p < 0.01, η²  = 0.023). Interestingly, the two higher velocity categories (>22 m/s) showed similar effectiveness (~60%), which were higher than the preceding slower category of 17-22 m/s (39.7%) (F = 175.1, p < 0.01, η²  = 0.074). Regarding court zones, throws from first-line zones (48%-60%), were more effective than from second line (38%-43%) (F = 13.1, p < 0.01, η²  = 0.016). With respect to the goal hit zone, effectiveness was higher in side (72%-77%) than in central zones (58%-64%) (F = 523.2, p < 0.01, η²  = 0.418). Coaches should improve the throwing velocity of players but also train at submaximal velocities (effective velocity) to save energy and reduce the potential risk of injury. Finally, training should be specialized according to the performance shown by players from different throwing zones, rather than from playing positions.

Time-Motion Analysis by Playing Positions of Male Handball Players during the European Championship 2020

The aim of this study was to analyze time-motion characteristics of elite male handball players during the last European Championship 2020. A total of 414 players from 24 national teams were analyzed during 65 matches using a local positioning system (LPS) for the first time in a European Championship. Players (n = 1865) covered significantly (p < 0.001; ES = 0.48) more total distance in offense (1217.48 ± 699.33 m) and in all locomotion categories (p < 0.001) than in defense (900.96 ± 538.95 m), with a similar average total time on court (13.40 ± 8.19 min in offense and 13.27 ± 8.59 min; p > 0.05). The running pace was significantly higher in offense 96.53 ± 22.57 m/min than in defense 82.72 ± 43.28 m/min (p < 0.001; ES = 0.47). By playing positions, the Left Wing players covered significantly (p < 0.001) higher distances (2547.14 ± 1309.52) and showed longer playing time (32.08 ± 17.01). Center Back was the playing position that showed the highest global running pace (98.34 m/min). Players with higher running pace in offense (p < 0.001) were Left Backs (105.95 ± 25.20) and the Center Backs in defense (95.76 ± 48.90). There were no significant differences between winners and losers or between top ranked and lower ranked teams in terms of time played, distance covered, and running pace. Specific physical conditioning is necessary to maximize performance and minimize fatigue when performing in long tournaments.

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.