The aim of this review is to provide the first comprehensive analysis of the various technical and physical on-court demands in elite male handball with respect to playing positions. While low-intensity activities such as standing still and walking represent the greater proportion of playing time (up to ~70 %), handball can be considered an intense activity for all players, especially because of the large number of repeated high-intensity actions occurring throughout the game (e.g., jumps, sprints, changes of direction, duels, contacts). Additionally, the substantial number of body contacts likely increases neuromuscular load, both during and following games. However, the average running pace (53 ± 7 to 90 ± 9 m·min(-1)) during handball games tends to be lower than in the majority of other team sports, while blood lactate and heart rate responses tend to be similar and slightly lower, respectively. Behind these team-average data, the substantial variations in technical and physiological demands between the different positions have been overlooked in the literature. Whether physical fatigue actually occurs during games is still unclear since, in the majority of studies, games were not examined under actual competitive situations. We contend that, in practice, appropriate player rotations may allow players to maintain an optimal physical performance level or, at least, limit a possible drop in physical/playing efficiency. Future research should essentially focus on the technical and physiological responses during games in relation to specific collective systems of play and individual playing roles. The occurrence of player position-specific fatigue should also be better examined when considering individual playing time and rotation strategies.

Monitoring workload is critical for elite training and competition, as well as preventing potential sports injuries. The assessment of external load in team sports has been provided with new technologies that help coaches to individualize training and optimize their team’s playing system. In this study we characterized the physical demands of an elite handball team during an entire sports season. Novel data are reported for each playing position of this highly strenuous body-contact team sport. Sixteen world top players (5 wings, 2 centre backs, 6 backs, 3 line players) were equipped with a local positioning system (WIMU PRO) during fourteen official Spanish first league matches. Playing time, total distance covered at different running speeds, and acceleration variables were monitored. During a handball match, wings cover the greater distance by high-speed running (> 5.0 m·s -1 ): 410.3 ± 193.2 m, and by sprint (> 6.7 m·s -1 ): 98.0 ± 75.4 m. Centre backs perform the following playing position that supports the highest speed intensities during the matches: high-speed running: 243.2 ± 130.2 m; sprint: 62.0 ± 54.2 m. Centre backs also register the largest number of high-intensity decelerations (n = 142.7 ± 59.5) compared to wings (n = 112.9 ± 56.0), backs (n = 105.2 ± 49.2) and line players: 99.6 ± 28.9). This study provides helpful information for professional coaches and their technical staff to optimize training load and individualize the physical demands of their elite male handball players depending on each playing position.

The use of CMJ as a predictor of handball-specific jumping ability is questioned given the dissociation between CMJ and jump-shot flying time. These results also show that transiently affected flight time may not affect scoring efficiency, which questions the importance of jumping ability for success in wing players.

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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.

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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.

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.