Skip to Content
MDPIMDPI

Advanced

SustainabilitySustainability
PDF
  • Article
  • Open Access

27 April 2022

9 Pages

Analysis of the Steps Cycle in the Action of Throwing in Competition in Men’s Elite Handball

,
,
,
and
Facultad de Ciencias de la Salud, Universidad San Jorge, Autov A23 km 29, Villanueva de Gállego, 50830 Zaragoza, Spain
*
Author to whom correspondence should be addressed.
Sustainability2022, 14(9), 5291;https://doi.org/10.3390/su14095291
This article belongs to the Special Issue Development Sustainable with Diet and Physical Activity on Health and Performance
Version Notes
Review Reports
Order Reprints

Abstract

The aim of this article was to analyze the step cycle that precedes the throwing action in elite men’s handball and its relationship with different factors, such as throwing distance, throwing technics, throw speed, whether it occurs in jump or standing, the last step, and efficiency. Twenty-four complete matches were analyzed, with a total of 1013 throws in three international elite men’s handball championships. The results show that the most used step cycle is the one performed with two steps. There is a significant relationship between the step cycle and the throw distance, with two-step throws being the most used from outside 9 m (29.8%, p < 0.001), three-step throws at a distance between 6 and 9 m (35.9%, p < 0.001), and zero- and one-step throws from 6 m (30.5%, p < 0.001). Likewise, the last step with natural footing is the most used (93.7%, p < 0.001) with a complete cycle of steps, followed by false foot with more than three steps (27.3%, p < 0.001), and two feet with zero steps (12.6%, p < 0.001). In conclusion, the skill to take advantage of the dynamic improvement offered by the mastery of the step cycle, adapting to the different situations of the game, could be an essential characteristic of the player to effectively complete the throwing action.

1. Introduction

Handball is an Olympic team sport with wide repercussions around the world. This sport is characterized by intermittent high-intensity actions, the speed of attack–defense changes during the game, and a great variety of offensive and defensive technical actions, as well as complex tactical schemes [1]. This sport is integrated within the cooperation teams sports with common space, understanding cooperation as the use of different technical and tactical means for the achievement of a common purpose, scoring a goal. On the other hand, opposition is the aim of the team in order to prevent the opponents from scoring a goal [2,3]. According to this approach, the observational methodology has been frequently used to analyze the most important performance factors in handball [4,5,6].
In this context, throwing a ball is defined as the most important action for the achievement of scoring a goal in handball, allowing a successful offensive phase [7,8,9]. Furthermore, throwing effectiveness is predetermined by other factors, such as throwing distance, which, in turn, is conditioned by other prior factor, such as the step cycle [6].
Handball-specific throws, in contrast to those from other sports, such as baseball or cricket, are characterized by a previous movement limited to a maximum of three steps, which actually are the most common throws in handball competitions [10,11,12,13]. For some authors, the three-step throwing cycle seems to be the most appropriate because of the high number of preparatory movements needed to coordinate the body segments and apply the most power to the end of the throwing chain. Moreover, these studies have proven better outcomes for the three-step cycle and good reliability over time [14,15].
The studies indicate that, at the professional national levels, the full-step cycle, with three previous steps, is the most used [16,17,18]. However, in the modern international game of handball, the mobility of the defense players is continuously increasing, leading to more open defensive systems, and positioning the attacking players further away from the goal area than in traditional handball defenses. Consequently, they do not give the thrower too much time to prepare the movement [16,19,20]. Therefore, some authors highlight the importance of mastering the technical–tactical resources of handball to succeed in competition [6,21,22,23,24].
Given the substantial changes in rules that enabled the simple practicality of playing with an extra player and an empty goal, the tactical systems have varied greatly in recent years, and offensive players have had to quickly adapt their technical–tactical background to maintain their levels of effectiveness in the game [22]. Therefore, our hypothesis is that the duration of the step cycle prior to the throw will be conditioned by the throwing distance. The aim of this study was to analyze the pre-throw step cycle in elite men’s handball, as well as the relationship with criteria and categories such as efficiency, throw distance, throw type, throwing technics, last supporting foot, and final match result in elite men’s handball competitions.

2. Materials and Methods

The observational methodology allowed us to collect data directly from the participants in competition [25]. Participants were informed of the purpose of the study and signed an informed consent. These matches were videotaped at all times. The recordings and sequencing of shots from each match were analyzed (match analysis) [22]. Observational and descriptive studies (ODS) [22] validated the observational design that combines three dichotomous axes, namely nomothetic (plurality), single point of observation, and multidimensional, which help to separate the basic ways of analyzing observational data [26,27]. The guidelines on ethical issues in human-subject research in the Belmont Report [28], describing basic ethical principles and guidelines, were followed. According to the guidelines, images of public behavior can be used for research without the informed consent of the athletes. The ethical and deontological principles were complied in relation to the people participating in the study, and the handling of the data obtained was in accordance with the ethical principles of the Declaration of Helsinki. This study has the favorable opinion of the Research Ethics Committee of the Autonomous Community of Aragon in its act No. 10/2021.

2.1. Participants

The sample is composed of the men’s national teams of the European Championship 2018, World Championship 2019, and European Championship 2020 that were ranked first-to-fourth finalists (Table 1). These championships were analyzed because they are fully representative of the elite teams in men’s handball. We observed 12 matches, and 24 clashes were analyzed. A total of 174 players were analyzed (mean age, 26.98 ± 5.2 years; body weight, 89.9 ± 7.9 kg; height, 1.91 ± 0.84 m; training experience, 11.8 years; and training work, 20 h per week). All throws from all matches were analyzed.
Table 1. Participants.

2.2. Instruments

An observational method was used to validate the study data [29], and a multidimensional ad hoc observation system [25] was created. The recording instrument was the free and versatile software Lince v.1.0. [30]. This program provides computerized observation procedures that speed up the recording process [31].
The independent variable was the cycle of steps used in each visualized throw, and the dependent variables were throw distance, throwing technics, throw height, throw speed, last foot, and throw result, as listed in Table 2.
Table 2. Definition of throw indicators used in the study [6].

2.3. Procedure

The observation instrument was validated by a panel of experts composed of 3 graduates in physical activity and sport sciences and national coaches with research experience in observational methodology [32].
Two observers were trained thanks to the construction of an observation manual in which the criteria, category, and codes of the observational process were defined [25]. All analyses were carried out over a period of 30 days, using the same tool and in the same space. Data validity was achieved by calculating the degree of concordance or reliability of the observers’ record, using Cohen’s Kappa index [33], which obtained a value of 0.80 for interobserver reliability and 0.89 for intraobserver reliability.

2.4. Statistical Analysis

Data were processed and presented by using the IBM SPSS Statistics version 26.0 (IBM Corp., Armonk, NY, USA). Descriptive analysis was used to calculate the distribution of frequencies and percentages of the different criteria and category. The normality of the distribution of the data was checked by using the Shapiro–Wilk test. Differences between groups (winners and losers) were examined by using the analysis of variance (one-factor ANOVA). To explore these correlations further, the adjusted residuals or z-score test [34] was used with a significance level of p < 0.05 (z ≥ ±3.29).

3. Results

The analysis of variance (one-factor ANOVA) of the normally distributed interval criteria found no significant differences (Table 3) between the means of the different championships with respect to the number of throws (1.890 f; 0.176 sig) and their effectiveness (0.542 f; 0.590 sig).
Table 3. ANOVA and number of throws, with results per team and match.
In our analysis of the step cycle and all study variables with frequency and percentage correlations (Table 4), there was a statistically significant correlation between throws from 7 m with the fly step cycle (90%, p < 0.01), zero step (30.5%, p < 0.001), and one step (54.8%, p < 0.01). Throws from a distance between 6 and 9 m have a statistically significant relationship with cycles of three steps (35.9%, p < 0.001) and more than three steps (54%, p < 0.01). It should be noted that the 9 m throws are correlated with the two-step throws (29.8%, p < 0.001). In the analysis of the correlations of the cycle of steps prior to the throw and the last foot of support, the statistically significant correlation between the throws made from a changed foot and the use of more than three steps (27.3%, p < 0.001) stands out. Equally, correlations were found between throws made with three steps and a natural-foot last support (93.7%, p < 0.001), whereas zero-step throws correlated with shooting with a two-foot throw at the same level (12.6%, p < 0.001).
Table 4. Frequency and percentage of the use of the step cycle and adjusted residuals or z-score between all study criteria.

4. Discussion

This research focused on the context of the game process and specifically analyzed the actions that can lead to success in team sports [22,35,36,37]. The aim of this study was to analyze the influence of the cycle of steps prior to throwing a ball in handball and its effectiveness, as well as the relationship between the variables that characterize the action, in elite men’s handball competitions.
The results show that the use of different step cycles prior to the throwing of the ball is conditioned by the distance of this throwing and the last support foot used. This is due to the wide variety of situations that can occur during the game (fast break shots, outside shots, pivot shots, and winger shots) [6].
Firstly, we found a relationship between the throwing distance and the results. Some studies found that throws from 6 m were in a positive relationship in the success of scoring a goal [38,39]. On the contrary, Antúnez et al. observed a negative relationship from 9 throwing meters [40].
Our results show that the throwing distance determines the use of different step cycles. This may be due to the in-game difficulty of effectively throwing the ball beyond the 9 m line. Interestingly, in this kind of throwing, a technical execution with three steps appears to be too slow, and defenders could easily defend and intercept the opponent’s shots. On the contrary, throwing the ball with zero or one step gives less time for the goalkeepers and defenders to react; this would allow attackers to anticipate their movements and gain an advantage during the game [41]. However, this tactical approach usually results in longer shooting distances. It is worth noting that these results are in agreement with other studies, confirming that, when the distance increases, effectiveness and precision decrease [9,24,42]. Furthermore, the players who most commonly use a single step to throw the ball are those who throw from short distances, where impairments in the neuromuscular throwing chain are less damaging to the performance and the little time to execute the throw seems to be the key factor.
Interestingly, the most common throwing step cycle when shooting between the lines (6–9 m) was with a complete cycle of steps (three steps). This strategy seems to respond to the player’s intention to get as close as possible to the opposing goal, rushing to score a goal and trying to avoid the goalkeeper’s anticipated actions. This result is in accordance with the studies of Gutiérrez-Dávila et al. [43] and Carbonell et al. [41]. These results highlight important aspects to be considered by coaches: (i) throws between lines (6–9 m) are mostly made with a complete cycle of steps (three steps), (ii) throws from beyond the 9 m line are mostly made with two steps, and (iii) throws from the 6 m line are mostly made with zero or one step.
As for limitations of the study, we can conclude that it is necessary to increase the sample size to have greater relevance in the factors analyzed. Moreover, the analysis of contextual variables (championship phase, partial score, match result) could improve the consistency of the analysis model. Moreover, the type of competition includes matches in the final phase and matches in the group phase, in addition others based on the knockout stage that may have influenced the behavior of the teams analyzed.
Finally, there is a lack of studies that analyze the last support performed within the technical execution of the throwing of the ball. Our findings highlight the greater use of the natural foot support for the last step of the throwing, that is, the opposite foot to the throwing arm. The explanation may be twofold, due to the laws of the game that only allow three steps before the throwing of the ball and in order to adopt an optimal throwing position [23]. In this direction, the natural foot support showed to be more effective than the non-natural one in each type of shooting analyzed. Furthermore, in the present study, the relationship between the two-feet throw and the zero-step throw appears to be a consequence of the greater influence of the game with the pivot player in the current handball game [44].

5. Conclusions

The conclusions derived from this study are that the highest percentage of shots in handball are made with two steps prior to the shot, throws from beyond the 9 m line are mostly made with two steps, throws between 6 and 9 m are executed to a greater extent with a previous cycle of three steps, and throws from the 6 m line are mostly made with zero or one step. Moreover, most throws were executed with the full cycle of steps, three steps. It is performed with the last natural support foot.
For all of this, it is important to propose a correct training process for the formation of the handball player, where the dynamic richness offered by mastery of the steps cycle is taken advantage of. The control of the step cycle is an essential characteristic to carry out the throwing action effectively. Coaches should propose exercises that modify the step cycle at all ages. Training throws from 9 m with two steps is the optimal way to increase performance in handball.

Author Contributions

Conceptualization, J.T. and D.L.; methodology, E.M.-P., J.T., D.L. and A.C.; validation, E.M.-P., J.T., D.L. and A.C.; formal analysis, J.T. and D.L.; investigation, J.T. and A.C.; data curation, J.T. and E.M.-P.; writing—original draft preparation, J.T.; writing—review and editing, E.M.-P., A.C., L.A.M.-C. and D.L.; supervision, E.M.-P., J.T., D.L., L.A.M.-C. and A.C.; project administration, D.L. and A.C. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Government of Aragon, Research Group ValorA, under Grant No. S08_20R.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of CEIC Aragón (CEICA) no. 10/2021.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Ibragimov, A.K.; Muxiddinovich, L.A. Individualization of psychological training of qualified handball players. Web Sci. Int. Sci. Res. J. 2021, 2, 234–241. [Google Scholar]
  2. Mancha-Triguero, D.; Baquero, B.; Ibáñez, S.; Antúnez, A. Impact of players’ grouping on the design of handball training tasks. Retos 2022, 43, 62–73. [Google Scholar] [CrossRef] [Scilit]
  3. Mendes, J.C.; Greco, P.J.; Ibáñez, S.J.; Nascimento, J.V. Construcción del modelo de juego en balonmano. Pensar en Movimiento. Revista de Ciencias del Ejercicio y la Salud 2021, 19, 1–25. [Google Scholar] [CrossRef] [Scilit]
  4. Lozano, D.; Camerino, O.; Hileno, R. Análisis del comportamiento táctico ofensivo en momentos críticos de juego en el alto rendimiento en balonmano: Un estudio Mixed Methods. Cuadernos de Psicología del Deporte 2016, 16, 151–160. [Google Scholar]
  5. Travassos, B.; Davids, K.; Araujo, D.; Esteves, P. Performance analysis in team sports: Advances from an Ecological Dynamics approach. Int. J. Perform. Anal. Sport 2013, 13, 89–95. [Google Scholar] [CrossRef] [Scilit]
  6. Tuquet, J.; Lozano, D.; Antunez, A.; Larroy, J.; Mainer-Pardos, E. Determinant Factors for Throwing in Competition in Male Elite Handball. Sustainability 2021, 13, 10913. [Google Scholar] [CrossRef] [Scilit]
  7. Bouagina, R.; Padulo, J.; Fray, A.; Larion, A.; Abidi, H.; Chtara, M.; Souhail Chelly, M.; Khalifa, R. Short-term in-season ballistic training improves power, muscle volume and throwing velocity in junior handball players. A randomized control trial. Biol. Sport 2021, 39, 415–427. [Google Scholar] [CrossRef] [Scilit]
  8. Debanne, T.; Laffaye, G. Predicting the throwing velocity of the ball in handball with anthropometric variables and isotonic tests. J. Sports Sci. 2011, 29, 705–713. [Google Scholar] [CrossRef] [Scilit]
  9. Granados, C.; Izquierdo, M.; Ibanez, J.; Bonnabau, H.; Gorostiaga, E.M. Differences in physical fitness and throwing velocity among elite and amateur female handball players. Int. J. Sports Med. 2007, 28, 860–867. [Google Scholar] [CrossRef] [Scilit]
  10. Chelly, M.S.; Hermassi, S.; Shephard, R.J. Relationships between power and strength of the upper and lower limb muscles and throwing velocity in male handball players. J. Strength Cond. Res. 2010, 24, 1480–1487. [Google Scholar] [CrossRef] [Scilit]
  11. Hermassi, S.; Ghaith, A.; Schwesig, R.; Shephard, R.J.; Souhaiel Chelly, M. Effects of short-term resistance training and tapering on maximal strength, peak power, throwing ball velocity, and sprint performance in handball players. PLoS ONE 2019, 14, e0214827. [Google Scholar]
  12. Rousanoglou, E.N.; Noutsos, K.S.; Bayios, I.A.; Boudolos, K.D. Self-Paced and Temporally Constrained Throwing Performance by Team-Handball Experts and Novices without Foreknowledge of Target Position. J. Sports Sci. Med. 2015, 14, 41–46. [Google Scholar] [PubMed]
  13. Spieszny, M.; Zubik, M. Modification of Strength Training Programs in Handball Players and its Influence on Power During the Competitive Period. J. Hum. Kinet. 2018, 63, 149–160. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  14. Rios, L.J.C.; Cuevas-Aburto, J.; Martinez-Garcia, D.; Ulloa-Diaz, D.; Ramirez, O.A.A.; Martin, I.M.; Ramos, A.G. Reliability of Throwing Velocity during Non-specific and Specific Handball Throwing Tests. Int. J. Sports Med. 2021, 42, 825–832. [Google Scholar] [CrossRef] [Scilit]
  15. Baştiurea, E.; Stan, Z.; Rizescu, C.; Mihăilă, I.; Andronic, F. The Effect of Muscle Strength on the Capacity of Coordination in Handball. Procedia-Soc. Behav. Sci. 2014, 137, 3–10. [Google Scholar] [CrossRef] [Scilit]
  16. Burger, A.; Foretić, N.; Spasić, M.; Rogulj, N.; Papić, V. Handball jump shoot kinematics-differences between croatian elite and professional players. In Proceedings of the 9th International Scientific Conference on Kinesiology, Opatija, Croatia, 13–17 May 2020; Volume 102. [Google Scholar]
  17. Belcic, I.; Rodić, S.; Dukarić, V.; Rupčić, T.; Knjaz, D. Do Blood Lactate Levels Affect the Kinematic Patterns of Jump Shots in Handball? Int. J. Environ. Res. Public Health 2021, 18, 10809. [Google Scholar] [CrossRef] [Scilit]
  18. Akl, A.-R.; Hassan, I.; Hassan, A.; Bishop, P. Relationship between Kinematic Variables of Jump Throwing and Ball Velocity in Elite Handball Players. Appl. Sci. 2019, 9, 3423. [Google Scholar] [CrossRef] [Scilit]
  19. Daza, G.; Andrés, A.; Tarragó, R. Match statistics as predictors of team’s performance in elite competitive handball. Rev. Int. Cienc. Deporte Int. J. Sport Sci. 2017, 13, 149–161. [Google Scholar] [CrossRef] [Scilit]
  20. Foreti, N.; Rogulj, N.; Papi, V. Empirical model for evaluating situational efficiency in top level handball. Int. J. Perform. Anal. Sport 2013, 13, 275–293. [Google Scholar] [CrossRef] [Scilit]
  21. Carbonell, V.; Fontaina, S.; Gonzalez, A. Study of the technical-tactical actions carried out by elite handball goalkeepers against the pivots throws. E-balonmano.com: Revista de Ciencias del Deporte 2018, 14, 1–8. [Google Scholar]
  22. Ávila-Moreno, F.M.; Chirosa-Ríos, L.J.; Ureña-Espá, A.; Lozano-Jarque, D.; Ulloa-Díaz, D. Evaluation of tactical performance in invasion team sports: A systematic review. Int. J. Perform. Anal. Sport 2018, 18, 195–216. [Google Scholar] [CrossRef] [Scilit]
  23. Lozano, D.; Camerino, O.; Hileno, R. Interacción dinámica ofensiva en balonmano de alto rendimiento. Apunts. Educ. Fis. Y Deportes 2016, 125, 90–110. [Google Scholar] [CrossRef] [Scilit]
  24. Zapardiel, J.C.; Suarez, H.V.; Manchado, C.; Rivilla, J.; Van den Tillaar, R. Effect of opposition and effectiveness of throwing from first and second line in male elite handball during competition. Kinesiol. Slov. 2019, 25, 35–44. [Google Scholar]
  25. Anguera, M.T.; Hernández-Mendo, A. Metodología observacional y psicología del deporte: Estado de la cuestión. Rev. Psicol. Deporte 2014, 23, 103–109. [Google Scholar]
  26. Manterola, C.; Otzen, T. Checklist for Reporting Results Using Observational Descriptive Studies as Research Designs: The MInCir Initiative. Int. J. Morphol. 2017, 35, 72–76. [Google Scholar] [CrossRef] [Scilit]
  27. Camerino, O.; Castañer, M. Mixed Methods Research in the Movement Sciences Cases in Sport Physical Education and Dance; Routledge: London, UK, 2012. [Google Scholar]
  28. Emanuel, E.J.; Grady, C.C.; Crouch, R.A.; Lie, R.K.; Miller, F.G.; Wendler, D.D. The Oxford Textbook of Clinical Research Ethics; Oxford University Press: Oxford, UK, 2008. [Google Scholar]
  29. Anguera Argilaga, M.T.; Blanco Villaseñor, Á.; Hernández Mendo, A.; Losada López, J.L. Diseños Observacionales: Ajuste y aplicación en psicología del deporte. Cuad. Psicol. Deporte 2011, 11, 63–76. [Google Scholar]
  30. Gabin, B.; Camerino, O.; Anguera, M.T.; Castañer, M. Lince: Multiplatform Sport Analysis Software. Procedia-Soc. Behav. Sci. 2012, 46, 4692–4694. [Google Scholar] [CrossRef] [Scilit]
  31. Anguera, M.T.; Hernández-Mendo, A. Técnicas de análisis en estudios observacionales en ciencias del deporte. [Data analysis techniques in observational studies in sport sciences]. Cuad. Psicol. Deporte 2015, 15, 13–30. [Google Scholar] [CrossRef] [Scilit]
  32. Villaseñor, A.; Losada, J.; Anguera, M.T. Data analysis techniques in observational designs applied to the environment-behaviour relation1. Medio Ambiente Comport. Hum. 2003, 4, 111–126. [Google Scholar]
  33. Cohen, J. Statistical Power Analysis for the Behavioral Sciences, 2nd ed; Routledge: London, UK, 1988. [Google Scholar]
  34. Allison, P.D.; Liker, J.K. Analyzing sequential categorical data on dyadic interaction: A comment on Gottman. Psychol. Bull. 1982, 91, 393–403. [Google Scholar] [CrossRef]
  35. Castellano, J.; Casamichana, D.; Lago, C. The Use of Match Statistics that Discriminate Between Successful and Unsuccessful Soccer Teams. J. Hum. Kinet. 2012, 31, 139–147. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  36. Drezner, R.; Lamas, L.; Barrera, J.; Dantas, L. Original Article A method for classifying and evaluating the efficiency of offensive playing styles in soccer. J. Phys. Educ. Sport 2020, 20, 1284–1294. [Google Scholar]
  37. Ruano, M.; Peñas, C.; Viaño, J.; González-García, I. Effects of game location, team quality and final outcome on game-related statistics in professional handball close games. Kinesiology 2014, 46, 249–257. [Google Scholar]
  38. Ávila Moreno, F.M. Application of an observational system for analysis of handball shots in the French World Championship 2001. Apunts. Educ. Física Y Deportes 2003, 71, 100–108. [Google Scholar]
  39. Almeida, A.G.; Merlin, M.; Pinto, A.; Torres, R.d.S.; Cunha, S.A. Performance-level indicators of male elite handball teams. Int. J. Perform. Anal. Sport 2020, 20, 1–9. [Google Scholar] [CrossRef] [Scilit]
  40. Antúnez Medina, A.; Ureña Villanueva, F.; Velandrino Nicolás, A.P.; García Parra, M.M. Valoración de la efectividad de interceptación com êxito de la portera de balonmano ante el lanzamiento trás la aplicación de um programa perceptivo-motor. Revista Internacional de Medicina y Ciencias de la Actividad Física y el Deporte 2004, 4, 192–203. [Google Scholar]
  41. Carbonell, V.; Fontaina, S.; Ramírez, A.G. Estudio de las acciones técnico-tácticas realizadas por los porteros de balonmano ante los lanzamientos de pivote. E-Balonmano.Com J. Sports Sci. 2018, 14, 1–8. [Google Scholar]
  42. Rivilla-García, J.; Martínez, I.; Grande, I.; Sampedro-Molinuevo, J. Relation between general throwing tests with a medicine ball and specific tests to evaluate throwing velocity with and without opposition in handball. J. Hum. Sport Exerc. 2011, 6, 414–426. [Google Scholar] [CrossRef] [Scilit]
  43. Gutiérrez-Davila, M.; Ortega, M.; Párraga, J.; Campos, J.; Rojas, F.J. Variabilidad de la secuencia temporal de la cadena cinética en el lanzamiento de balonmano. Revista Internacional de Medicina y Ciencias de la Actividad Física y el Deporte 2011, 11, 455–471. [Google Scholar]
  44. Román Seco, J.d.D. Táctica colectiva grupal en ataque: Los modelos en el balonmano español. [Tactical collective of group in attack: The models spanish handball]. E-Balonmano.com: Revista de Ciencias del Deporte 2009, 4, 23. [Google Scholar]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Article Metrics

Citations

Article Access Statistics

Journal Statistics
Multiple requests from the same IP address are counted as one view.
Sustainable Workplace Mental Well Being for Sustainable SMEs: How?
Previous
Systemic Risk Contributions of Financial Institutions during the Stock Market Crash in China
Next