Current Developments in Handball Game Analysis

Main Article Content

Nilgün Vurgun
Murat Bilge
Serdar Eler
Nebahat Eler
Aydın Şentürk

Keywords

Game analysis, tournament analysis, finalist analysis, longitudinal analysis

Abstract

The most important expectation of the trainers was the correct evaluation of the game analysis and the reflection of its effects on the trainings. Because of handball’s complex nature, interpreting numerical data with objective field facts requires expertise. The aim of this study was to evaluate the numerical results under three different titles (longitudinal-success–tournament analysis) and with different research problems. As a longitudinal analysis, match parameters of the same generation (WU17-WU19 European Championships) in underage categories held two years apart were compared. As a success analysis, all the matches played by the 2020 MECh (Mens’ European Championship) champion (Spain) and finalist (Croatia) in the tournament were analyzed. It has been set up which parameters determine success. As a tournament analysis, the leadership of European teams in handball was analyzed after the evaluations between the European teams and others in the 2019 WWCh (Womens’ World Championship) tournament. According to the property of the research problem, t-test, Kruskall Wallis H-test, Pearson correlation and the eta square statistics were used. Research results based on numerical data has tried to be done current contributions to game analysis in handball. As a result, this study has been designed to show that the results of match analysis in handball are not just numbers. It is aimed to evaluate the results under four different titles and with different research problems and to transfer them on the practice. With these three topics; longitudinal analysis, success analysis and tournament analysis, it would also be appropriate to complement the notational analysis with different variables that are predominantly characterized by actions such as different parameters’ efficiency. In order to model the game process effectively, it is necessary to obtain more data about the actions of the teams during the match and the strategies used in different competitions.

Abstract 221 | PDF Downloads 247

References

1. Bilge, M. (2012). Game analysis of Olympic, World and European Championships in men’s Handball. Journal of Human Kinetics, 35, 109–118.
2. Wagner H., Finkenzeller T., Würth S., von Duvillard S.P. (2014). Individual and team performance in team-handball: a review. J. Sports Sci. Med.,13(4), 808-16
3. Passos, P., Araújo, D., Volossovitch, A. (2017). Performance analysis in team sports. Taylor & Francis, sf: 200-217.Bilge, 2019)
4. Gutiérrez, O., Ruiz, J. L. (2013). Game performance in the World Championship ofhandball 2011. Journal of Human Kinetics, 36, 137–147. doi:10.2478/hukin-2013–0014
5. Lago, C., Gómez, M. A., Viaño, J., González-García, I., Fernández, M. (2013). Home advantage in elite handball: The impact of the quality of opposition on team performance. International Journal of Performance Analysis in Sport, 13, 724–733.
6. Ohnjec, K., Vuleta, D., Milanovic, D., Gruic, I. (2008). Performance indicators of teams at the 2003 world handball championship for women in Croatia. Kinesiology, 40(1), 69–79.
7. Srhoj, V., Rogulj, N., Padovan, M., Katic, R. (2001). Influence of the attack end conduction on match result in handball. Collegium Antropologicum, 25(2), 611–617.
8. Vuleta, D., Milanovic, D., Grunic, I., Ohnjec, K. (2007). Influence of the goals scored in the different time periods of the game on the final outcome of matches of the 2003 Men’s World Handball Championships, Portugal. EHF Periodical [Internet]. http://home.eurohandball.com/ehf_files/Publikation/ WP Vuleta-Influence of the goals scored on final outcomes.pdf
9. Foretic´, N., Rogulj, N., Papic´, V. (2013). Empirical model for evaluating situational efficiency in top level handball. International Journal of Performance Analysis in Sport, 13, 275–293.
10. Rogulj, N., Srhoj, V., Srhoj, L. (2004). The contribution of collective attack tactics in differentiating handball score efficiency. Collegium Antropologicum, 28(2), 739–746.
11. Lozano, D., Camerino, O. (2012). Effectiveness of offensive systems in hand ball. Apunts. Educación Física y Deportes, 108, 70–81. Rogulj et al, 2004).
12. Chelly, M. S., Hermassi, S., Aouadi, R., et al. (2011). Match analysis of elite adolescent team handball players. J Strength Cond Res, 25, 2410-7.
13. Povoas, S. C., Seabra, A. F., Ascensao, A. A., et al. (2012). Physical and physiological demands of elite team handball. J Strength Cond Res, 26, 3365-75.
14. Bilge, M. (2017). Qualitative Analysis of EHF Women’s Championship 2017 Macedonia, 31.07-06.08.2017.SKOPJE. http://home.eurohandball.com/ehf_files/specificHBI/ECh_Analyses/2017/MKD/3/Trend%20Analysis_W17%20ECh%20MKD.pdf
15. Bilge, M. (2019). Qualitative Analysis of EHF Women’s 19 Championship 2019 LTU, 15-21.07 2019.KLAIPEDA.
http://home.eurohandball.com/ehf_files/specificHBI/ECh_Analyses/2019/LTU/3/QUALITATIVE%20ANALYSIS%20OF%202019%20W19%20EURO%20CHAMPIONSHIP%20LTU.pdf
16. Duyan, M., Ilkim, M., & Çelik, T. (2022). The Effect of Social Appearance Anxiety on Psychological Well-Being: A Study on Women Doing Regular Pilates Activities. Pakistan Journal of Medical & Health Sciences, 16(02), 797-797.
17. Souhail, H., Castagna, C., Mohamed, et al. (2010). Direct validity of the yo-yo intermittent recovery test in young team handball players. J Strength Cond Res, 24, 465-70
18. Michalsik, L. B., Aagaard, P., Madsen, K. (2013). Locomotion characteristics and match-induced impairments in physical performance in male elite team handball players. Int J Sports Med, 34, 590-599.
19. Hulka, K., Cuberek, R., Svoboda, Z. 2014. Time-motion analysis of basketball players: a reliability assessment of Video Manual Motion Tracker 1.0 software. J Sports Sci, 32, 53-9.
20. Del Coso, J., Munoz-Fernandez, V. E., Munoz, G., et al. (2012). Effects of a caffeine-containing energy drink on simulated soccer performance. PLoS One, 7, e31380.Barbero et al., 2017).
21. Barbero, J.C., Vera, J. G., González, J. C. et al. (2014). Physical and physiological demands of
22. elite team handball players. International Journal of Performance Analysis in Sport, 14,921-933.
23. Alex Pascual1, Roger Font2,3, Xavier Pascual4, and Carlos Lago-Peñas. Evolution of match performance parameters in elite men’s handball 2012–2022. International Journal of Sports Science & Coaching, 1–5
24. Karaca, Y., & Ilkim, M. (2021). Investigation of the attitudes distance education of the faculty of sport science students in the Covid-19 period. Turkish Online Journal of Distance Education, 22(4), 114-129.
25. Valentin, Lf. Longitudinal Study On The Effectiveness Of The Game Actions In Men’s Handball Top Competitions (1998-2016 Kinesiologia Slovenica, 24, 2, 36–43 (2018),
26. Meletakos P and Bayios I. General trends in European men’s handball: a longitudinal study. Int J Perform Anal Sport 2010; 10: 221–228.
27. Gómez, M. A.; Lago, C.; Viaño, J.; González, I. Effects of game location, team quality and final outcome on game-related statistics in professional handball close games. Kinesiology 2014, 46(2), 249–257.
28. Calin R. The analysis of the efficiency of using fast breaks in female handball during the WorldChampionship in China, 2009. Sci Movement Health, 2010; 2; 594-599
29. Yiannakos A, Sileloglou P, Gerodimos V, Triantafillou P, Armatas V, Kellis S. Analysis and comparison of fast break in top level handball matches. Int J Perform Anal Sport, 2005; 5: 3: 62-72
30. Ding YJ. The statistical analysis of the technique and tactics of the women handball tournaments of the World Championship and the Beijing Olympic Games. Fujian Sport Sci Technol, 2011; 01:17-19 Schmidt, R. A., Lange, C. Young, D. E. (1990). Optimizing summary knowledge of results for skill learning. Human Movement Science, 9, 325–348.