Bayesian Analysis of Skills Importance in World Champions Men’s Volleyball across Ages

Open access

Abstract

In volleyball, due to the sequential structure of the game, each outcome results from events that follow consistent consecutive patterns: pass–set–attack–outcome, serve–outcome and block–dig–set–counter attack–outcome. There are three possible outcomes: point won, point lost, and rally continuation. With the aim of quantifying the importance of volleyball skills, data of world champions of the male International Volleyball Federation tournaments for three age categories (Youth, Juniors and Men) were used to construct a transition matrix between subsequent moves and skills within the game. A Dirichlet-Multinomial Bayesian model was used to estimate the transition probabilities between the subsequent moves along with the marginal probability of success of each skill in the complex. The prior distribution of each transition probabilities between moves/skills was elicited to incorporate experts' opinion. For the final evaluation of the skills a simple Monte Carlo scheme was applied to obtain a random sample from the posterior distribution. The findings of the study indicate that the relative importance of volleyball skills is robust across world champions of different age categories. Slight variations are observed on specific skills. A new index (Quantile Mid-range Ratio) is proposed for highlighting skills that are valuable for team’s gameplay.

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

  • Afonso J. & Mesquita I. (2007). Pilot study on attack tempo in women's volleyball. Portuguese Journal of Sports Science 7 (1) pp. 21-84.

  • Albert I. Donnet S. Guihenneuc-Joyaaux C. Low-Choy S. Mengersen K. & Rousseau J. (2012). Combining Experts opinion in Prior Elicitation. Bayesian Analysis 7 (3) pp. 503-532.

  • Alfonso J. Esteves F. Araujo R. Thomas L. & Mesquita I. (2012). Tactical determinants of setting zone in elite men's volleyball. Journal of Sport Sciences and Medicine (11) pp. 64-79.

  • Altman D. G. (1991). Practical Statistics for Medical Research. London: Chapman & Hall.

  • Araujo R. Mesquita I. & Marcelino R. (2009). Relationship between block constraits and set outcome in elite male volleyball. International Journal of Performance Analysis in Sport9 (3) pp. 306-313.

  • Barzouka K. Nikolaidou M. E. Malousaris G. & Bergeles N. (2006). Perfomance Excellence of male Setters and attackers in Complex 1 and 2 on Volleyball teams in the 2004 Olympic games. International Journal of Volleyball Research9 (1).

  • Costa G. C. Caetano R. J. Ferreira N. N. Alfonso J. & Costa P. (2011). Determinants of attacking tactics in youth male elite Volleyball. International Journal of Performance Analysis in Sport11 (1) pp. 96-104.

  • Data Project. (2000). Data Volley. 2.1.9.2.1.9. Salerno Italy.

  • Drikos S. & Tsoukos A. (2018 July 06). Data benchmarking through a longitudinal study in high-level men's volleyball. International Journal of Performance Analysis in Sport 18 (3) pp. 470-480.

  • Drikos S. & Vagenas G. (2011). Multivariate assessment of selected performance indicators in relation to the type and result of a typical set in Men's Elite Volleyball. International Journal of Performance Analysis in Sport (11) pp. 85-95.

  • Florence L. Fellingham G. Vehrs P. & Mortensen N. (2008). Skill Evaluation in Women's Volleyball. Journal of Quantitative Analysis in Sports4 (2).

  • Garcia de Alcaraz A. Ortega E. & Palao J. M. (2015). Effect of age group on male volleyball players' technical-tactical performance profile for the spike. International Journal of Performance Analysis in Sport15 (2) pp. 668-686.

  • Garcia-de-Alcaraz A. Valades D. & Palao J. M. (2017). Evolution of Game's Demands From Young to Elite Players in Men's Volleyball. International Journal of Sports Physiology and Performance12 (6) pp. 788-795.

  • Kountouris P. Drikos S. Aggelonidis I. Laios A. & Kyprianou M. (2015). Evidence for Differences in Men's and Women's Volleyball Games Based on Skillls Effectiveness in Four Consecutive Olympic Tournaments. Comprehensive Psychology 4 (9).

  • Marcelino R. Mesquita I. & Sampaio J. (2009). Home advantage and set outcome in high level volleyball. Journal of Sport Sciences (26) pp. S66-S67.

  • Milian-Sanchez A. Rabago M. Hernadez M. A. Femia Marzo P. & Urena A. (2015 August). Participation in terminal actions according to the role of the player and his location on the court in top level men's volleyball. International Journal of Performance Analysis in Sport pp. 609-619.

  • Miskin M. Fellingham G. & Florence L. (2010). Skill Importance in Women's Volleyball. Journal of Quantitative Analysis in Sports6 (2).

  • Nikolaidis P. Alfonso J. Busko K. Ingebrigtsen J. Chtourou H. & Martin J. (2015). Positional differences of physical trait and physiological characteristics in female volleyball players - The role of age. Kinesiology (47) pp. 75-81.

  • Palao J. M. Santos J. A. & Urena A. (2004). Effect of the setter's position on the Block in Volleyball. International Journal of Volleyball Research 6 (1) pp. 29-32.

  • Pena J. Rodriguez - Guerra J. Busca B. & Serra N. (2012 December). Which skills and factors better predict winning and losing in high level men's volleyball. The Journal of Strength and Conditioning Research27 (9).

  • Rocha C. & Barbanti V. (2006). An analysis of confrontation in the first sequence of game actions in Brazilian Volleyball. Journal of Human Movement Studies (50) pp. 259-272.

  • Silva M. Lacerda D. & Joao P. V. (2014 August). Match analysis of discrimination skills according to the setter defence zone position in high level Volleyball. International Journal of Performance Analysis in Sport14 (2) pp. 463-472.

  • Stutzig N. Zimmermann B. Busch D. & Siebert T. (2015). Analysis of game variables to predict scoring and performance levels in elite men's volleyball. International Journal of Performance Analysis in Sport (15) pp. 816-829.

  • Zetou E. Moustakidis A. Tsigilis N. & Komninakidou A. (2007). Does effectiveness of skill Complex 1 predict win in Men's Olympic Volleyball Games? Journal of Quantitative Analysis in Sports3 (4).

  • Zetou E. Tsigilis N. Moustakidis A. & Komninakidou A. (2006 6). Playing characteristics of men's Olympic Volleyball teams in complex II. International Journal of Performance Analysis in Sport6 (1) pp. 172-177.

Search
Journal information
Impact Factor


CiteScore 2018: 0.71

SCImago Journal Rank (SJR) 2018: 0.355
Source Normalized Impact per Paper (SNIP) 2018: 0.462

Metrics
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 113 113 34
PDF Downloads 94 94 32