Temporal effects of final action on the performance of the Portuguese men’s volleyball teams

Open access

Summary

Study aim: The purpose of this study was twofold: (i) to compare total attacks, points in the defense phase and attack efficiency between playing positions; and (ii) to identify the main predictors of overall volleyball teams’ success related to points made during the game.

Material and methods: 282 sets with a total of 33 174 actions and 8 231 points were analyzed. The study included 14 teams participating in the male First Division Portuguese Championship (53 games from the 2016/2017 season and 27 from the first phase of the 2017/2018 season, for a total of 80 matches).

Results: The most important parameters for the overall performance are efficacy of points in defense phase, aces, block points, and attack efficiency. Overall team performance variables statistically significantly predicted the total points of the team, F16,1091 = 39.375, p < 0.001, R2 = 0.366. Considering the comparisons between players’ performances, it was found that the setter had the lowest number of points in the defense phase and total attacks. Opposites had more total attacks and points in the defense phase than the other players (at a small-to-moderate magnitude).

Conclusion: The results revealed the importance of the efficacy of points in the defense phase, namely regarding the service action, block point, and attack efficiency, to improve the possibilities of winning.

If the inline PDF is not rendering correctly, you can download the PDF file here.

  • 1. Afonso J. Esteves F. Araújo R. Thomas L. Mesquita I. (2012) Tactical determinants of setting zone in elite men’s Volleyball. J. Sports Sci. Med. 11: 64-70.

  • 2. Alexandru S.D. Sabin S.I. (2015) Study on the Interpretation of the Results in a Volleyball Game by Using a Specific Program of Statistics. Procedia – Soc. Behav. Sci. 180: 1357–1363. DOI: 10.1016/j.sbspro.2015.02.277.

  • 3. Araújo R.M. Castro J. Marcelino R. Mesquita I.R. (2010) Relationship between the Opponent Block and the Hitter in Elite Male Volleyball. J. Quant. Anal. Sport 6. DOI: 10.2202/1559-0410.1216.

  • 4. Batterham A.M. Hopkins W.G. (2006) Making Meaningful Inferences about Magnitudes. Int. J. Sports Physiol. Perform. 1: 50–57. DOI: 10.1123/ijspp.1.1.50.

  • 5. Castro J. Souza A. Mesquita I. (2011) Attack Efficacy in Volleyball: Elite Male Teams. Percept. Mot. Skills 113: 395-408. DOI: 10.2466/05.25.PMS.113.5.395-408.

  • 6. Cohen J. (1988) Statistical power analysis for the behavioral sciences 2nd Edition.

  • 7. Costa G. Castro H. Evangelista B. Malheiros L. Greco P. Ugrinowitsch H. (2017) Predicting Factors of Zone 4 Attack in Volleyball. Percept. Mot. Skills 124: 621–633. DOI: 10.1177/0031512517697070.

  • 8. Data Project (2014) The statistics and analysis software used by the best teams worldwide. http://www.dataproject.com/US/en/Volleyball.

  • 9. Djamel M. Mohamed S. (2015) Level of decision making in some volleyball skills for secondary stage students. Swedish J. Sci. Res. 2: 23-29.

  • 10. Drikos S Kountouris P Laios A Laios Y (2009) Correlates of Team Performance in Volleyball. Int. J. Perform. Anal. Sport 9: 149-156.

  • 11. Durkovic T. Marelic N. Resetar T. (2008) Influence of the position of players in rotation on differences between winning and loosing teams in volleyball. Int. J. Perform. Anal. Sport 8: 8-15.

  • 12. Eom H.J. Schutz R.W. (1992) Statistical analyses of volleyball team performance. Res. Q. Exerc. Sport 63: 11-18. DOI: 10.1080/02701367.1992.10607551.

  • 13. Hopkins W. Marshall S. Batterham A. Hanin J. (2009) Progressive statistics for studies in sports medicine and exercise science. Med. Sci. Sport Exerc. 41: 3.

  • 14. Klaričić I. Grgantov Z. Jelaska I. (2018) Prediction of efficiency in elite volleyball: multiple regression approach. Acta Kinesiol. 12: 79-85.

  • 15. Laios A. Kountouris P. (2017) Receiving and serving team efficiency in Volleyball in relation to team rotation. Int. J. Perform. Anal. Sport 11: 553-561.

  • 16. Marcelino R. Mesquita I. Afonso J. (2008) The weight of terminal actions in Volleyball. Contributions of the spike serve and block for the teams’ rankings in the World League 2005. Int. J. Perform. Anal. Sport 8: 1-7. DOI: 10.1080/24748668.2008.11868430.

  • 17. Marcelino R. Mesquita I. Palao J.M. Sampaio J. (2009) Home advantage in high-level volleyball varies according to set number. J. Sport Sci. Med. 8: 352–356.

  • 18. Marcelino R. Mesquita I. Sampaio J. (2011) Effects of quality of opposition and match status on technical and tactical performances in elite volleyball. J. Sports Sci. 29: 733-741. DOI: 10.1080/02640414.2011.552516.

  • 19. Marcelino R. Mesquita I. Sampaio J. Moraes J. (2010) Study of performance indicators in male volleyball according to the set results. Rev. Bras. Educ. Física e Esporte 24: 69-78.

  • 20. Millán-Sánchez A. Morante Rábago J.C. Ureña Espa A. (2017) Differences in the success of the attack between outside and opposite hitters in high level men’s volleyball. J. Hum. Sport Exerc. 12: 251-257. DOI: 10.14198/jhse.2017.122.01.

  • 21. Monteiro R. Mesquita I. Marcelino R. (2009) Relationship between the set outcome and the dig and attack efficacy in elite male volleyball game. Int. J. Perform. Anal. Sport 9: 294-305.

  • 22. Palao J.M. Santos J.A. Ureña A. (2004) Effect of team level on skill performance in volleyball. Int. J. Perform. Anal. Sport 4: 50-60.

  • 23. Pena J. Rodriguez-Guerra J. Busca B. Serra N. (2013) Which skills and factors better predict winning and losing in high-level men’s volleyball? J. Strength Cond. Res. 27: 2487-2493.

  • 24. Petroski E.L. Fidelix Y.L. Augusto D. Silva S. Rocha M.A. Oncken P. Viera F.S. (2013) Anthropometric morpholgical and somatotype characteristics of athletes of the Brazilian Men’s Volleyball team: an 11-year descriptive study. Brazilian J. Kinanthropometry Hum. Perform. 184-193.

  • 25. Robinson G. O’Donoghue P. (2007) A weighted kappa statistic for reliability testing in performance analysis of sport. International. J. Perform. Anal. Sport 7: 12-19.

  • 26. Rodriguez-Ruiz D. Quiroga M. Miralles J. Sarmiento S. Saá Y. Garcia-Manso J. (2011). Study of the technical and tactical variables determining set win or loss in top-level European men’s volleyball. Int. J. Perform. Anal. Sport 7: 1-13.

  • 27. Silva M. Lacerda D. João P. (2013) Match analysis of discrimination skills according to the setter attack zone position in high level volleyball. Int. J. Perform. Anal. Sport 13: 367-379.

  • 28. Silva M. Lacerda D. João P.V. (2014) Game-related volleyball skills that influence victory. J. Hum. Kinet. 41: 173-179. DOI: 10.2478/hukin-2014-0045.

  • 29. Silva M. Marcelino R. Lacerda D. João P.V. (2016) Match Analysis in Volleyball : a systematic review. Int. J. Perform. Anal. Sport 5: 35-46.

  • 30. Stutzig N. Zimmermann B. Büsch D. Siebert T. (2017) Analysis of game variables to predict scoring and performance levels in elite men’s volleyball Analysis of game variables to predict scoring and performance levels in elite men’s volleyball. Int. J. Perform. Anal. Sport 15: 816-829. DOI: 10.1080/24748668.2015.11868833.

  • 31. Valhondo Á. Fernández-Echeverría C. González-silva J. Claver F. Moreno M.P. (2018) Variables that predict serve efficacy in elite men’s volleyball with different quality of opposition sets. J. Hum. Kinet. 61: 167-177. DOI: 10.1515/hukin-2017-0119.

  • 32. Zetou E. Moustakidis A. Tsigilis N. Komninakidou A. (2007) Does Effectiveness of Skill in Complex I Predict Win in Men’s Olympic Volleyball Games? J. Quant. Anal. Sport 3. DOI: 10.2202/1559-0410.1076.

Search
Journal information
Impact Factor


CiteScore 2018: 0.38

SCImago Journal Rank (SJR) 2018: 0.144
Source Normalized Impact per Paper (SNIP) 2018: 0.432

Metrics
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 116 116 13
PDF Downloads 63 63 8