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PERFORMANCE COEFFICIENT OF THE MASTER VOLLEYBALL SKILLS/Coeficiente de rendimiento de las acciones de juego del voleibol master.

INTRODUCTION

The performance of the volleyball skills were much researched in volleyball literature (Palao and collaborators, 2016; Silva and collaborators, 2016). But the volleyball studies were about the professional volleyball (Marques Junior, 2013) and the young volleyball (Arruda and Marques Junior, 2015).

The volleyball studies about the skills determined the serve, the block and the attack how the most important skills for the team win the match (Marques Junior, 2015; Oliveira and collaborators, 2016). Then, the volleyball skills practiced point during the match were the best skills for the volleyball team get the victory (Drikos and collaborators, 2009; Silva, Lacerda and Joao, 2014).

The reception, the set and the defense the volleyball literature informed about these skills (Sanchez and collaborators, 2015). The volleyball research determined the relation between the reception, the set and the attack (Costa and collaborators, 2017a; Rocha and Barbanti, 2004). The good reception causes a good set and the attack has more successful. Others volleyball skills with a relation during the match were determined by volleyball literature, a good block is important for the success in the defense (Mesquita and collaborators, 2013).

Performance coefficient was developed by Coleman (2002) with the objective of determine the performance of the volleyball skills. Coleman (2002) practiced the following classification of the performance coefficient for the volleyball skills: 2,50 or more is an excellent performance of an international level volleyball team, 2,30 to 2,49 is a low performance of an international level volleyball team, 2,20 to 2,29 is a good performance of a club level volleyball team, 2 to 2,19 is a medium performance of a club level volleyball team and 1,99 or less is a bad performance of a club level volleyball team.

However, volleyball literature did not determine the performance coefficient of the male master volleyball of the category 35 years or more during the sets (Marcelino and collaborators, 2009, 2010; Marques Junior and Arruda, 2015). Only a study about the male master volleyball studied the performance coefficient of a volleyball team during the 2nd shift of the Carioca Championship of 2016 (Marques Junior, 2017). Therefore, the volleyball literature needs more research about this theme.

What is the value of the performance coefficient of the male master volleyball skills of the category 35 years or more?

The volleyball research did not have information about these results (Costa and collaborators, 2017; Peiro and collaborators, 2016), only the study of Marques Junior (2017).

The objective of the study was to determine the performance coefficient of the master volleyball skills.

MATERIALS AND METHODS

The study was composed by 15 matches of the male master volleyball of the category 35 years or more during the Carioca Championship of 2016 (n = 9 matches) and of 2017 (n = 6 matches). The study had 15 matches during the 1st set, 15 matches during the 2nd set and 4 matches during the 3rd sets--total of 34 sets.

The matches of the master volleyball were filmed with the camera Sony[R] handycam, model DCR-SX20 on the tripod Mirage[R].

After the data collect, the researcher practiced the match analysis with a scout prepared in the Excel[R] of Marques Junior and Arruda (2017) with the objective of determines the performance coefficient. The materials used during the match analysis were the following: a Compaq Presario CQ43 notebook was used with the scout, an Acer Aspire 4320 notebook was used to pass the image of the matches to the Philips 42 LCD television for this instrument reproduce the image of the matches. The figure illustrates these explanations.

The master volleyball is practiced with two sets of 25 points or two points of difference for the winner. When each team wins one set, the tie break (3rd set) is practiced with a set of 15 points or two points of difference for the winner.

The data were collected with the camera in gymnasium, at a distance of 2 meters (m) and a height of 2 m. All the matches were filmed in the Canto Rio gymnasium, club in Niteroi, Rio de Janeiro, Brazil. The researcher positioned back of the court for filmed the match. Then, only a master volleyball team was analyzed with the scout prepared in the Excel[R].

The researcher practiced the match analysis at a distance of 1 m from the television. The scout prepared in the Excel[R] was standardized for collect the data of the matches with the norms of Marques Junior and Arruda (2015).

The classification of the performance coefficient of the skills for the male master volleyball of the category 35 years or more was as follows: 0 to 1 is a low performance, 1,1 to 2 is a medium performance and 2,1 to 3 or more is a high performance (Marques Junior, 2017). The results were expressed as mean and standard deviation, minimum and maximum, confidence interval of 95%. The effect size (ES) of Hedges and Olkin (1985) was calculated in the Excel[R]. The classification of the ES was based in Cano-Corres, Sanchez-Alvarez and Fuentes-Arderiu (2012), the classification was as follows: 0,20 or less is very small the effect, 0,21 to 0,49 is small the effect, 0,50 to 0,79 is medium the effect and 0,80 or more is great the effect.

The researcher verified the performance coefficient of the skills during the sets of all the 15 matches. Then, the normality of the data was assessed by the Shapiro Wilk test (n = 50, p p[less than or equal to]0.05) and/or with the Kolmogorov Smirnov test (n>50, p[less than or equal to]0.05), but was observed the normality of the data through of the histogram.

In case of data normal, the difference between the performance coefficient of the skills in each set was analyzed using one way Anova, with accepted results with significance level of p[less than or equal to]0,05. The Tukey post hoc was used to identify the difference of the performance coefficient of the skills in each set, with accepted results with significance level of p[less than or equal to]0.05. In case of data not normal, the difference between the performance coefficient of the skills in each set was analyzed using Kruskal Wallis Anova, with accepted results with significance level of p[less than or equal to]0,05. The Dunn post hoc was used to identify the difference of the performance coefficient of the skills in each set, with accepted results with significance level of p[less than or equal to]0.05. After the calculation of the Anova, the new statistic of Cumming (2014) was performed for the significance p to be more precise.

The same statistical models of the sets were applied in the court zone.

The study verified the relation between skills through correlation. In case of data normal, Pearson correlation (r) was used, with accepted results with significance level of p[less than or equal to]0,05. In case of data not normal, Spearman correlation (R) was used, with accepted results with significance level of p[less than or equal to]0,05. The variables studied by the correlations were as follows: serve versus block, block versus defense, reception versus set and set versus attack.

All these statistical treatments were performed according to the procedures of the GraphPad Prism, version 5.0. The histogram, the bar graph and the correlation graph were elaborated according to the procedures of the GraphPad Prism, version 5.0. The bar graph with value of the mean was elaborate in the Excel[R].

RESULTS

The data of the performance coefficient (PC) of the skills of each set were presented in table 1.

The Kolmogorov Smirnov test detected data not normal of the performance coefficient of the 1st and 2nd set of all skills. The Shapiro Wilk test detected data not normal of the performance coefficient of the 3rd set of all skills. The histogram illustrates the data not normal of some skills.

Kruskal Wallis Anova did not identify statistical difference of the performance coefficient of all skills during each set. The results were as follows: serve [H (2) = 2.51, p = 0.28], reception [H (2) = 4.94, p = 0.08], set [H (2) = 0.03, p = 0.98], attack [H (2) = 1.71, p = 0.42], block [H (2) = 1.81, p = 0.40] and defense [H (2) = 3.01, p = 0.22]. The figure 3 illustrates the results.
           1 set  2 set  3 set

Serve      1.91   1.73   1.87
Block      1.74   1.66   1.86
Defense    1.57   1.41   1.33

           1 set  2 set  3 set

Reception  2.29   2.39   2.65
Set        2.16   2 12   2.07
Attack     2.37   2.24   2.13

Figure 3 - Result of the performance coefficient of the skills of each
set.

Note: Table made from bar graph.


After of the calculation of the Kruskal Wallis Anova, the researcher practiced the new statistic of Cumming (2014) with the data of each set. The new statistic did not identify statistical difference of the performance coefficient of the serve, of the reception and of the set because the mean did not had the p less or equal the 0.05 and overlap of the confidence interval of 95% was not 0.50 or less (Cumming and Finch, 2005; Cumming, Fidler and Vaux, 2007). The table 2 shows the results of the skills of each set.

Therefore, new statistic detects statistical difference when the p and the confidence interval of 95% (is the overlap) have difference.

The table 3 shows the performance coefficient (PC) of the skills of all the 15 matches or 34 sets.

The figure 4 shows in ascending order the performance of the skills of the match.
        Defense  Block  Serve  Set   Attack  Reception

Serie1   1,48    1,72    1,82  2,13   2,29      2,37

Figure 4 - Performance coefficient of the 15 matches (n = 34 sets) of
the male master volleyball of the category 35 years or more.

Note: Table made from bar graph.


The Kolmogorov Smirnov test detected data not normal of the performance coefficient of the skills of the correlation. The histogram illustrates the data not normal of the skills.

The researcher verified the relation between the skills through of the Spearman correlation (R). The table 4 shows the results.

The figure 6 shows the correlation graphics.

The researcher determined the performance coefficient of the skill in each court zone. The volleyball is composed of six zones and the figure 7 illustrates the zones.

The data of the performance coefficient (PC) of the serve of each court zone were presented in table 5.

The Kolmogorov Smirnov test detected data not normal of the performance coefficient of the serve in each court zone that the volleyball player practiced the skill. The histogram illustrates the data not normal of the serve.

Kruskal Wallis Anova did not identify statistical difference of the performance coefficient of the serve of each court zone that the volleyball player practiced the skill, H (2) = 2.45, p = 0.29. The figure 9 illustrates the results.
       zone 1  zone 5  zone 6

Serve   1,77    1,85    1,89

Figure 9 - Performance coefficient of the serve of each court zone (15
matches or 34 sets).

Note: Table made from bar graph.

       zone 2  zone 3  zone 4

Block   1,68    1,75    1,71

Figure 11 - Performance coefficient of the block of each court zone (15
matches or 34 sets).

Note: Table made from bar graph.


The new statistic did not identify statistical difference of the performance coefficient of the serve of each court zone. The table 6 shows the results.

The data of the performance coefficient (PC) of the block of each court zone were presented in table 7.

The Kolmogorov Smirnov test detected data not normal of the performance coefficient of the block in each court zone that the volleyball player practiced the skill. The histogram illustrates the data not normal of the block.

Kruskal Wallis Anova did not identify statistical difference of the performance coefficient of the block of each court zone that the volleyball player practiced the skill, H (2) = 1.45, p = 0.48. The figure 11 illustrates the results.

The new statistic did not identify statistical difference of the performance coefficient of the block of each court zone. The table 8 shows the results.

The data of the performance coefficient (PC) of the defense of each court zone were presented in table 9.
         zone 1  zone 5  zone 6  zone 2  zone 3  zone 4

Defense   1.35    1.20    1.64    1.47    1.76    1.36

Figure 13 - Performance coefficient of the defense of each court zone
(15 matches or 34 sets).

Note: Table made from bar graph.


The Kolmogorov Smirnov test detected data not normal of the performance coefficient of the defense in each court zone that the volleyball player practiced the skill. The histogram illustrates the data not normal of the defense.

Kruskal Wallis Anova identified statistical difference of the performance coefficient of the defense of each court zone that the volleyball player practiced the skill, H (5) = 15.88, p = 0.007. The post hoc Dunn detected statistical difference (p[less than or equal to]0.05) between the zone 5 (mean = 1.20) versus the zone 3 (mean = 1.76)--difference in rank sum = -63.77. The figure 13 illustrates the results.

The new statistic detected statistical difference in a comparison of the defense, zone 5 (back zone) versus the zone 3 (front zone). The table 10 shows the results.

The figure 14 illustrates the results with statistical difference of the defense, zone 5 (back zone) versus the zone 3 (front zone).

Therefore, the significance p and new statistic detected statistical difference during the defense of the zone 5 (back zone) versus the zone 3 (front zone). Then, the study detected only statistical difference in one comparison.

The data of the performance coefficient (PC) of the set of each court zone were presented in table 11.

The Kolmogorov Smirnov test detected data not normal of the performance coefficient of the set in each court zone that the volleyball player practiced the skill. The histogram illustrates the data not normal of the set.

Kruskal Wallis Anova identified statistical difference of the performance coefficient of the set of each court zone that the volleyball player practiced the skill, H (5) = 37.89, p = 0.0001. The post hoc Dunn detected statistical difference (p[less than or equal to]0.05) of the following comparisons: zone 2 (mean = 2.21) versus zone 1 (mean = 1.80) - difference in rank sum = 59.04, zone 5 (mean = 1.96) - difference in rank sum = 47.38 and zone 4 (1.94) - difference in rank sum = 54.55. Zone 3 (mean = 2.34) versus zone 1 - difference in rank sum = 65.70, zone 5 - difference in rank sum = 54.04 and zone 4 - difference in rank sum = 61.21. The figure 16 illustrates the results.
     zone 1  zone 5  zone 6  zone 2  zone 3  zone 4

Set   1.80    1.96    2.06    2.21    2.34    1.94

Figure 16 - Performance coefficient of the set of each court zone (15
matches or 34 sets).

Note: Table made from bar graph.

        zone 1  zone 5  zone 6  zone 2  zone 3  zone 4

Attack   2.24    1.71    1.75    2.25    2.45    2.32

Figure 19 - Performance coefficient of the attack of each court zone
(15 matches or 34 sets).

Note: Table made from bar graph.


The new statistic detected statistical difference in the following comparisons of the set: zone 1 (back zone) versus the zone 2 (front zone), zone 5 (back zone) versus the zone 2 (front zone), zone 6 (back zone) versus the zone 3 (front zone) and zone 2 (front zone) versus the zone 3 (front zone). The table 12 shows the results.

The figure 17 illustrates the results with statistical difference of the set.

Therefore, the significance p and the new statistic detected statistical difference of the set of each court zone only in two comparisons, zone 1 versus the zone 2 and zone 5 versus the zone 2. Then, the study detected only statistical difference in two comparisons.

The data of the performance coefficient (PC) of the attack of each court zone were presented in table 13.

The Kolmogorov Smirnov test detected data not normal of the performance coefficient of the attack in each court zone that the volleyball player practiced the skill. The histogram illustrates the data not normal of the attack.

Kruskal Wallis Anova identified statistical difference of the performance coefficient of the attack of each court zone that the volleyball player practiced the skill, H (5) = 14.87, p = 0.01. The post hoc Dunn detected statistical difference (p[less than or equal to]0.05) between the zone 6 (mean = 1.75) versus the zone 3 (mean = 2.45) - difference in rank sum = -68.75. The figure 19 illustrates the results.

The new statistic detected statistical difference in the following comparisons of the attack: zone 1 (back zone) versus the zone 6 (back zone), zone 5 (back zone) versus the zone 3 (front zone), zone 6 (back zone) versus the zone 2 (front zone), zone 6 (back zone) versus the zone 3 (front zone) and zone 6 versus the zone 4 (front zone). The table 14 shows the results.

The figure 20 illustrates the results with statistical difference of the attack.
           zone 1  zone 5  zone 6  zone 2  zone 3  zone 4

Reception   2,39    2,31    2,37     3      2,83    2,53

Figure 22 - Performance coefficient of the reception of each court zone
(15 matches or 34 sets).

Note: Table made from bar graph.


Therefore, the significance p and new statistic detected statistical difference during the attack of the zone 6 (back zone) versus the zone 3 (front zone). Then, the study detected only statistical difference in one comparison.

The data of the performance coefficient (PC) of the reception of each court zone were presented in table 15.

The Kolmogorov Smirnov test detected data not normal of the performance coefficient of the reception in each court zone that the volleyball player practiced the skill. The histogram illustrates the data not normal of the reception.

Kruskal Wallis Anova did not identify statistical difference of the performance coefficient of the reception of each court zone that the volleyball player practiced the skill, H (5) = 9.44, p = 0.09. The figure 22 illustrates the results.

The new statistic did not identify statistical difference of the performance coefficient of the reception of each court zone. The table 16 shows the results.

DISCUSSION

The male master volleyball of the category 35 years or more had the reception and the attack with high performance coefficient during the three sets--see table 1. Then, the skills were the best techniques practiced by players. The study had similar result of the article of Marques Junior (2017) about the male master volleyball, the best skill were the attack and the reception. The second best skill was the set, the result was with high (1st and 2nd set) and medium (3rd set) performance coefficient. Only article about the male master volleyball of the category 35 year or more detected the same result (Marques Junior, 2017).

However, the best skills (attack, reception and set) of the male master volleyball of the category 35 years or more had similar result during the sets because the significance p and the new statistic did not identify statistical difference. Other result, of the effect size--see table 1, evidenced very small or small effect of the performance coefficient of the reception, of the set and of the attack during the sets. These results confirmed similar performance coefficient of these three skills (attack, reception and set) during the sets.

Coleman (2002) informed about the performance coefficient of the serve, of the block and of the defense this study was with a bad performance because the result was 1.87 to less--see table 1. However, the result of the performance coefficient of 1.1 to 2 of the male master volleyball of the category 35 years or more was classified with medium (Marques Junior, 2017).

The worst skills of the male master volleyball were the serve, the block and the defense. These results confirmed the relation between these skills (Mesquita and collaborators, 2013). A bad serve causes a bad block because the opponenfs attack is good. Then, the bad block causes a bad defense because the attack is very strong. However, the relation between the skills had only a statistical difference (serve x block, p = 0.003), but the R was of 0.18, this result was very low second Gaya (2008). The other results did not have statistical difference and this study did not show the relation between the volleyball skills. Maybe it is the statistic model because the studies about this theme use the chi-square (Costa and collaborators, 2017a; Costa and collaborators, 2016).

The worst skills of all matches (15 matches) or of all sets (34 sets) were the defense (performance coefficient or PC of 1.48 [+ or -] 1.02), the block (1.72 [+ or -] 0.91) and the serve (1.82 [+ or -] 0.61)--see table 3 and figure 4. The classification of the performance coefficient of these skills was medium. Then, the coach needs to train more the serve, the block and the defense.

The performance of the court zone was studied. The serve (see table 5 and figure 9) and the block (see table 7 and figure 11) had similar performance of the skill in each court zone. But the defense, back zone (zone 1, 5 and 6) had worse performance than the front zone (zone 2, 3 and 4). The results were similar to the volleyball studies (Marques Junior and Arruda, 2015; Palao and Ibarra, 2015). However, zone 1 (PC of 1.35 [+ or -] 1) and zone 5 (PC of 1.20 [+ or -]1.06) (back zone) had worse performance of the defense. Perhaps this defense problem of the zone 1 and 5 can be through of the use of three players in zone 1 or 5 when the attack is of the zone 4 or 2 (Marques Junior, 2017b). The France men's volleyball team was champion of the World League of 2017 with three volleyball players in zone 1 or 5 during the defense when the attack was of the zone 4 or 2.

The best skills of all matches (15 matches) or of all sets (34 sets) were the set (PC of 2.13 [+ or -] 0.68), the attack (2.29 [+ or -] 1.15) and the reception (2.37 [+ or -] 0.67)--see table 3 and figure 4. The classification of the performance coefficient of these skills was high. Then, the coach needs to train do maintenance training for the set, the attack and the reception.

The study detected the best set of the zone 2 (PC of 2.21 [+ or -] 0.87) and of the zone 3 (PC of 2.34 [+ or -] 0.57). The zone 2 and 3 is in front zone and this zone facilitates the set. The study detected statistical difference (p[less than or equal to]0.05 and new statistic) only in two comparisons of the front zone versus the back zone (zone 2 versus the zone 1 and 5). This result was found in other studies, the zone 2 and 3 had the best set (Marques Junior and Arruda, 2015; Marques Junior, 2017). Therefore, the coach needs to prescribe more training in the other court zones.

The best performance of the attack was practiced in front zone (zone 2, 3 and 4) and in only back zone (zone 1)--see table 13 and figure 13. These results were similar to the only study about the master volleyball (Marques Junior, 2017). However, the medium performance of the attack was in the back zone 5 and 6, the master volleyball player needs of more training in these zones.

The reception was the best skill of the master volleyball because the performance coefficient was high in all court zones. However, the reception was worse in the zone 5 (PC of 2.31 [+ or -] 0.69), so the players needs of more training in this zone.

The study had limitations because the researcher did not use sophisticated technology for match analysis of the volleyball skills (Marques Junior, 2010).

CONCLUSION

The match analysis of the skills of the male master volleyball (category 35 year or more) determined the worst skill (serve, block and defense) and the best skill (reception, set and attack). Then, these results are important for the coach prescribe the training.

In conclusion, match analysis is an important "tool" for the master volleyball.

REFERENCES

1 Arruda, D.; Marques Junior, N. Estudos dos fundamentos de jovens jogadoras do voleibol feminino. Rev Bras Prescr Fisio Exerc. Vol. 9. Num. 56. p. 730-51. 2015.

2 Cano-Corres, R.; Sanchez-Alvarez, J.; Fuentes-Arderiu, X. The effect size: beyond statistical significance. J Int Feder Clin Chem Lab Med. Vol. 23. Num. 1. p. 1-5. 2012.

3 Coleman, J. Scouting opponents and evaluating team performance. In. Shondell D.; Reynaud, C. (Eds.). The volleyball coaching bible. Champaign: Human Kinetics. 2002. p. 321-346.

4 Costa, G.; Maia, M.; Capuzzo, J.; Evangelista, B.; Freire, A.; Nora, F.; Campos, M.; Ugrinowitsch, H. Offensive structuring in men's high-level volleyball: analysis of the attack zone. Rev Bras Cineantropom Desempenho Hum. Vol. 18. Num. 5. p. 611-619. 2016.

5 Costa, G.; Castro, H.; Evangelista, B.; Malheiros, L.; Greco, P.; Ugrinowitsch, H. Predicting factors of zone 4 attack in volleyball. Percept Motor Skill. Vol. 124. Num. 3. p. 621-633. 2017a.

6 Costa, G.; Evangelista, B.; Maia, M.; Ceccato, J.; Freire, A.; Milistetd, M.; Moraes, J.; Ugrinowitsch, H. Volleyball: analysis of attack performed from the backcourt on men's Brazilian volleyball Superleague (Brazilian Championship). Rev Bras Cineantropom Desempenho Hum. Vol. 19. Num. 2. p. 233-241. 2017.

7 Cumming, G. The new statistics: why and how. Psychol Sci. Vol. 25. Num. 1. p. 7-29. 2014.

8 Cumming, G.; Finch, S. Inference by eye: confidence intervals and how to read pictures of data. Am Psychol. Vol. 60. Num. 2. p. 170-80. 2005.

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10 Drikos, S.; Kountouris, P.; Laios, A.; Laios, Y. Correlates of team peformance in volleyball. Int J Perf Analysis Sport. Vol. 9. Num. 2. p. 149-156. 2009.

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12 Hedges, L.; Olkin, I. Statistical methods for meta-analysis. New York: Academic Press. 1985.

13 Marcelino, R.; Mesquita, I.; Sampaio, J.; Anguera, A. Ventaja de jugar em casa em voleibol de alto rendimento. Rev Psicol Dep. Vol. 18. Num. 2. p. 181-196. 2009.

14 Marcelino, R.; Mesquita, I.; Sampaio, J.; Moraes, J. Estudo dos indicadores de rendimento em voleibol em funcao do resultado do set. Rev Bras Educ Fis Esp. Vol. 24. Num. 1. p. 69-78. 2010.

15 Marques Junior, N. Coaching peripheral vision training for soccer athletes. Phys Educ. Vol. 67. Num. 2. p. 74-89. 2010.

16 Marques Junior, N. Evidencias cientificas sobre os fundamentos do voleibol: importancia desse conteudo para prescrever o treino. Rev Bras Prescr Fisio Exerc. Vol. 7. Num. 37. p. 78-97. 2013.

17 Marques Junior, N. Fundamentos que fazem ponto durante o jogo de voleibol: um estudo de correlacao. Rev Observatorio Dep. Vol. 1. Num. 3. p. 134-145. 2015.

18 Marques Junior, N. Estudo no voleibol master: analise da performance dos fundamentos e do desempenho fisico durante o jogo. Rev Observatorio Dep. Vol. 3. Num. 1. p. 7-95. 2017.

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20 Marques Junior, N.; Arruda, D. Coeficiente de performance dos fundamentos do voleibol de uma equipe feminina sub 15: um estudo no campeonato do Parana de 2015. Rev Observatorio Dep. Vol. 1. Num. 4. p. 253-280. 2015.

21 Marques Junior, N.; Arruda, D. Analise do jogo de voleibol com novo scout elaborado no Excel[R]. Rev Bras Prescr Fisio Exerc. Vol. 11. Num. 68. p. 525-541. 2017.

22 Mesquita, I.; Palao, J.; Marcelino, R.; Afonso, J. Performance analysis in indoor volleyball and beach volleyball. In. McGarry, T.; O' Donoghue, P.; Sampaio, J. (Eds.). Handbook of sports performance analysis. London: Routledge. 2013. p. 367-379.

23 Oliveira, A.; Valladares, N.; Vaz, L.; Joao, V. Evaluation of scoring skills and non-scoring skills in the Brazilian Super league women's volleyball. Monten J Sports Sci Med. Vol. 5. Num. 2. p. 25-31. 2016.

24 Palao, J.; Ibarra, M. Defense efficacy in practice and competition. A case study in women's volleyball. Central Eur J Sports Sci Med. Vol. 12. Num. 4. p. 25-34. 2015.

25 Palao, J.; Alcaraz, A.; Hernandez, E.; Ortega, E. A case study of applying collective technical-tactical performance goals in elite men's volleyball team. Int J Appl Sports Sci. Vol. 28. Num. 2. p. 68-78. 2016.

26 Peiro, I.; Parra, M.; Leon, J.; Fradua, L.; Benitez, J.; Urena, A. Relationship between middle hitter and setter's position and its influence on the attack zone in elite men's volleyball. Int J Perf Analysis Sport. Vol. 16. Num. 2. p. 523-538. 2016.

27 Rocha, C.; Barbanti, V. Uma analise dos fatores que influenciam o ataque no voleibol masculino de alto nivel. Rev Bras Educ Fis Esp. Vol. 18. Num. 4. p. 303-314. 2004.

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Nelson Kautzner Marques Junior (1)

(1) Castelo Branco University, Rio de Janeiro-RJ, Brazil

E-mail:

kautzner123456789junior@gmail.com

Recebido para publicacao 24/11/2017

Aceito em 01/01/2018
Table 1 - Performance of the skills in each set--minimum and maximum
(min and max), confidence interval of 95% (IC 95%), effect size (ES)
and classification.

  Skills           1st set                      2nd set

           1.91 [+ or -] 0.47 (medium)  1.73 [+ or -] 0.73 (medium)
Serve      0 and 3,5 (min and max)      0 and 4
           1.82 to 2 (IC 95%)           1.59 to 1.86
           2.29 [+ or -] 0.47 (high)    2.39 [+ or -] 0.60 (high)
Reception  0 and 3                      0 and 3
           2.14 to 2.43                 2.29 to 2.50
           2.16 [+ or -] 0.63 (high)    2.12 [+ or -] 0.70 (high)
Set        0 and 3                      0 and 3
           2.05 to 2.26                 2 to 2.24
           2.37 [+ or -] 1.11 (high)    2.24 [+ or -] 1.18 (high)
Attack     0 and 4                      0 and 4
           2.20 to 2.54                 2.07 to 2.42
           1.74 [+ or -] 0.92 (medium)  1.66 [+ or -] 0.91 (medium)
Block      0 and 4                      0 and 4
           1.62 to 1.86                 1.53 to 1.79
           1.57 [+ or -] 1.01 (medium)  1.41 [+ or -] 1.05 (medium)
Defense    0 and 3                      0 and 3
           1.42 to 1.73                 1.25 to 1.57

  Skills           3rd set                ES and Classification

           1.87 [+ or -] 0.55 (medium)  1st and 2nd set = 0,17 (very
                                        small)
Serve      0 and 3                      1st and 3rd set = 0,04 (very
                                        small)
           1.82 to 2                    2nd and 3rd set = 0,13 (very
                                        small)
           2.65 [+ or -] 0.48 (high)    1st and 2nd set = 0,10 (very
                                        small)
Reception  0 and 3                      1st and 3rd set = 0,34 (small)
           2.44 to 2.86                 2nd and 3rd set = 0,25 (small)
           2.07 [+ or -] 0.48 (medium)  1st and 2nd set = 0,04 (very
                                        small)
Set        0 and 3                      1st and 3rd set = 0,09 (very
                                        small)
           1.71 to 2.43                 2nd and 3rd set = 0,05 (very
                                        small)
           2.13 [+ or -] 1.16 (high)    1st and 2nd set = 0,12 (very
                                        small)
Attack     0 and 4                      1st and 3rd set = 0,22 (small)
           1.68 to 2.57                 2nd and 3rd set = 0,10 (very
                                        small)
           1.86 [+ or -] 0.85 (medium)  1st and 2nd set = 0,08 (very
                                        small)
Block      0 and 4                      1st and 3rd set = 0,11 (very
                                        small)
           1.60 to 2.13                 2nd and 3rd set = 0,19 (very
                                        small)
           1.33 [+ or -] 0.88 (medium)  1st and 2nd set = 0,15 (very
                                        small)
Defense    0 and 3                      1st and 3rd set = 0,23 (small)
           1.03 to 1.64                 2nd and 3rd set = 0,08 (very
                                        small)

Legend: Classification of the PC: 0 to 1 (low), 1,1 to 2 (medium) and
2,1 to 3 or more (high).

Table 2 - Results of the new statistic of the skills of each set.

       Serve       Overlap   p        Reception      Overlap   p

1st set x 2nd set   1.28    0.29  1st set x 2nd set    1.70   0.65
1st set x 3rd set   0.52    0.71  1st set x 3rd set    1      0.42
2nd set x 3rd set   0.73    0.79  2nd set x 3rd set    1      0.59

       Attack      Overlap   p          Block        Overlap   p

1st set x 2nd set   1.43    0.85  1st set x 2nd set    1.77   0.73
1st set x 3rd set   0.49    0.77  1st set x 3rd set    0.73   0.84
2nd set x 3rd set   0.80    0.93  2nd set x 3rd set    0.73   0.69

       Set         Overlap   p

1st set x 2nd set   1.70    0.65
1st set x 3rd set   0.57    0.80
2nd set x 3rd set   0.57    0.80

     Defense       Overlap   p

1st set x 2nd set   1.82    0.78
1st set x 3rd set   0.87    0.75
2nd set x 3rd set   0.87    0.87

Legend: n = 10 or more: Overlap of 0,50 or less (*) and p
[less than or equal to]0,05 (*) (statistical difference).

Table 3 - Performance of the skills of the match.

Skills             Match                    IC 95%

Serve      1.82 [+ or -] 0.61 (medium)  1.74 to 1.90
Reception  2.37 [+ or -] 0.67 (high)    2.29 to 2.45
Set        2.13 [+ or -] 0.68 (high)    2.06 to 2.21
Attack     2.29 [+ or -] 1.15 (high)    2.17 to 2.41
Block      1.72 [+ or -] 0.91 (medium)  1.63 to 1.80
Defense    1.48 [+ or -] 1.02 (medium)  1.37 to 1.58


Legend: Classification of the PC: 0 to 1 (low), 1,1 to 2 (medium) and
2,1 to 3 or more (high).

Table 4 - R Spearman of the skills.

     Variable            R           P            IC 95%

serve x block     0.18 (very low)  0.003 (*)   0.05 to 0.31
block x defense   0.03             0.45       -0.06 to 0.14
reception x set  -0.04             0.47       -0.16 to 0.08
set x attack     -0.04             0.41       -0.15 to 0.06

Legend: p[less than or equal to]0.05* (statistical difference).

Table 5 - Performance of the serve in each court zone - PC, minimum and
maximum (min and max), confidence interval of 95% (IC 95%), effect size
(ES) and classification.

Skill             Zone 1                       Zone 5

       1.77 [+ or -] 0.63 (medium)  1.85 [+ or -] 0.63 (medium)
Serve  0 and 3,5 (min and max)      0 and 4
       1.66 to 1.88 (IC 95%)        1.70 to 2

Skill             Zone 6                   ES and Classification

       1.89 [+ or -] 0.56 (medium)  zone 1 and zone 2 = 0.08 (very
                                    small)
Serve  0 and 3                      zone 1 and zone 5 = 0.12 (very
                                    small)
       1.74 to 2.05                 zone 5 and zone 6 = 0.04 (very
                                    small)

Legend: Classification of the PC: 0 to 1 (low), 1.1 to 2 (medium) and
2.1 to 3 or more (high).

Table 6 - Results of the new statistic of the serve of each court zone.

      Serve      Overlap    p

zone 1 x zone 5    1.22   0.27
zone 1 x zone 6    1.30   0.32
zone 5 x zone 6    1.83   1

Legend: n = 10 or more: Overlap of 0.50 or less (*) and p<0.05 (*)
(statistical diference).

Table 7 - Performance of the block in each court zone.

Skill             Zone 2                       Zone 3

       1.68 [+ or -] 0.86 (medium)  1.75 [+ or -] 1 (medium)
Block  0 and 4 (min and max)        0 and 4
       1.55 to 1.81 (IC 95%)        1.58 to 1.92

Skill             Zone 4               ES and Classification

       1.71 [+ or -] 0.92 (medium)  zone 2 and zone 3 = 0.07 (very
                                    small)
Block  0 and 4                      zone 2 and zone 4 = 0.03 (very
                                    small)
       1.57 to 1.86                 zone 3 and zone 4 = 0.04 (very
                                    small)

Legend: Classification of the PC: 0 to 1 (low), 1.1 to 2 (medium) and
2.1 to 3 or more (high).

Table 8 - Results of the new statistic of the block of each court zone.

     Block       Overlap    p

zone 2 x zone 3    1.44   0.43
zone 2 x zone 4    1.37   0.37
zone 3 x zone 4    1.78   1

Legend: n = 10 or more: Overlap of 0.50 or less (*) and p
[less than or equal to]0.05 (*) (statistical diference).

Table 9 - Performance of the defense in each court zone.

      Zone              Defense              Min and Max     IC 95%

1 (back zone)   1.35 [+ or -] 1 (medium)        0 and 3   1.13 to 1.56

5 (back zone)   1.20 [+ or -] 1.06 (medium)     0 and 3   0.95 to 1.14

6 (back zone)   1.64 [+ or -] 1 (medium)        0 and 3   1.43 to 1.84

2 (front zone)  1.47 [+ or -] 1 (medium)        0 and 3   1.15 to 2.02

3 (front zone)  1.76 [+ or -] 0.98 (medium)     0 and 3   1.51 to 2.02
4 (front zone)  1.36 [+ or -] 0.98 (medium)     0 and 3   1.04 to 1.67

      Zone         ES and Classification

                zone 1 and zone 2 = 0.12 (very small)
                zone 1 and zone 3 = 0.41 (small)
1 (back zone)   zone 1 and zone 4 = 0.01 (very small)
                zone 1 and zone 5 = 0.15 (very small)
                zone 1 and 6 = 0.29 (very small)
                zone 5 and zone 2 = 0.27 (small)
5 (back zone)   zone 5 and zone 3 = 0.55 (medium)
                zone 5 and zone 4 = 0.16 (very small)
                zone 5 and zone 6 = 0.44 (small)
                zone 6 and zone 2 = 0.17 (very small)
6 (back zone)   zone 6 and zone 3 = 0.12 (very small)
                zone 6 and zone 4 = 0.24 (small)
2 (front zone)  zone 2 and zone 3 = 0.29 (small)
                zone 2 and zone 4 = 0.11 (very small)
3 (front zone)  zone 3 and zone 4 = 0.39 (small)
4 (front zone)  -

Legend: Classification of the PC: 0 to 1 (low), 1.1 to 2 (medium) and
2.1 to 3 or more (high).

Table 10 - Results of the new statistic of the defense of each court
zone.

     Defense     Overlap      p

zone 1 x zone 2   1.57      0.57
zone 1 x zone 3   0.09 (*)  0.11
zone 1 x zone 4   1.82      1
zone 1 x zone 5   1.55      0.52
zone 1 x zone 6   0.57      0.04 (*)
zone 5 x zone 2   1.27      0.30
zone 5 x zone 3  -0.05 (*)  0.004 (*)
zone 5 x zone 4   1.64      0.61
zone 5 x zone 6   1.17      0.11
zone 6 x zone 2   1.23      0.28
zone 6 x zone 3   1.57      0.54
zone 6 x zone 4   0.86      0.11
zone 2 x zone 3   0.95      0.14
zone 2 x zone 4   1.65      0.65
zone 3 x zone 4   0.61      0.05 (*)

Legend: n = 10 or more: Overlap of 0.50 or less (*) and p
[less than or equal to]0.05 (*) (statistical difference).

Table 11 - Performance of the set in each court zone.

     Zone                Set                 Min and Max     IC 95%

1 (back zone)   1.80 [+ or -] 0.64 (medium)    0 and 3    1.63 to 1.98

5 (back zone)   1.96 [+ or -] 0.52 (medium)    0 and 3    1.77 to 2.16

6 (back zone)   2.06 [+ or -] 0.50 (medium)    0 and 3    1.77 to 2.16

2 (front zone)  2.21 [+ or -] 0.87 (high)      0 and 3    2.02 to 2.40
3 (front zone)  2.34 [+ or -] 0.57 (high)      0 and 3    2.19 to 2.49
4 (front zone)  1.94 [+ or -] 0.16 (medium)  1,5 and 2    1.88 to 2

     Zone          ES and Classification

                zone 1 and zone 2 = 0.41 (small)
                zone 1 and zone 3 = 0.53 (medium)
1 (back zone)   zone 1 and zone 4 = 0.14 (very small)
                zone 1 and zone 5 = 0.16 (very small)
                zone 1 and 6 = 0.26 (small)
                zone 5 and zone 2 = 0.25 (small)
5 (back zone)   zone 5 and zone 3 = 0.38 (small)
                zone 5 and zone 4 = 0.02 (very small)
                zone 5 and zone 6 = 0.10 (very small)
                zone 6 and zone 2 = 0.15 (very small)
6 (back zone)   zone 6 and zone 3 = 0.28 (small)
                zone 6 and zone 4 = 0.12 (very small)
                zone 2 and zone 3 = 0.13 (very small)
2 (front zone)  zone 2 and zone 4 = 0.27 (small)
3 (front zone)  zone 3 and zone 4 = 0.40 (small)
4 (front zone)  -

Legend: Classification of the PC: 0 to 1 (low), 1.1 to 2 (medium) and
2.1 to 3 or more (high).

Table 12 - Results of the new statistic of the set of each court zone.

      Set        Overlap      p

zone 1 x zone 2   0,22 (*)  0,02 (*)
zone 1 x zone 3  -1.09      0.001 (*)
zone 1 x zone 4   1.18      0.40
zone 1 x zone 5   1.36      0.41
zone 1 x zone 6   0.57      0.05 (*)
zone 5 x zone 2   0,14 (*)  0,05 (*)
zone 5 x zone 3  -0.60      0.001 (*)
zone 5 x zone 4   0.01 (*)  1
zone 5 x zone 6   1.24      0.28
zone 6 x zone 2   0.60      0.10
zone 6 x zone 3  -0,20 (*)  0,004 (*)
zone 6 x zone 4   0.01 (*)  0.19
zone 2 x zone 3   0,18 (*)  0.01 (*)
zone 2 x zone 4   0.01 (*)  0.51
zone 3 x zone 4  -3.07      0.001 (*)

Legend: n = 10 or more: Overlap of 0,50 or less (*) and p
[less than or equal to]0,05 (*) (statistical difference).

Table 13 - Performance of the attack in each court zone.

     Zone                 Attack             Min and Max     IC 95%

1 (back zone)   2.24 [+ or -] 0.84 (high)       0 and 4   1.90 to 2.57

5 (back zone)   1.71 [+ or -] 1.06 (medium)     0 and 4   1.09 to 2.33

6 (back zone)   1.75 [+ or -] 1.19 (medium)     0 and 4   1.37 to 2.13

                                                0 and 4   2.03 to 2.46
2 (front zone)  2.25 [+ or -] 1.15 (high)
3 (front zone)  2.45 [+ or -] 1.01 (high)       0 and 4   2.24 to 2.66
4 (front zone)  2.32 [+ or -] 1.21 (high)       0 and 4   2.10 to 2.54

     Zone            ES and Classification
                zone 1 and zone 2 = 0.01 (very small)
                zone 1 and zone 3 = 0.21 (small)
1 (back zone)   zone 1 and zone 4 = 0.08 (very small)
                zone 1 and zone 5 = 0.51 (medium)
                zone 1 and 6 = 0.48 (very small)
                zone 5 and zone 2 = 0.53 (medium)
5 (back zone)   zone 5 and zone 3 = 0.73 (medium)
                zone 5 and zone 4 = 0.60 (medium)
                zone 5 and zone 6 = 0.04 (very small)
                zone 6 and zone 2 = 0.49 (medium)
6 (back zone)   zone 6 and zone 3 = 0.69 (medium)
                zone 6 and zone 4 = 0.56 (medium)
                zone 2 and zone 3 = 0.20 (very small)
2 (front zone)  zone 2 and zone 4 = 0.07 (very small)
3 (front zone)  zone 3 and zone 4 = 0.13 (very small)
4 (front zone)  -

Legend: Classification of the PC: 0 to 1 (low), 1.1 to 2 (medium) and
2.1 to 3 or more (high).

Table 14 - Results of the new statistic of the attack of each court
zone.

     Attack      Overlap     p

zone 1 x zone 2   1.54      1
zone 1 x zone 3   1.24      0.34
zone 1 x zone 4   1.64      0.68
zone 1 x zone 5   0.88      0.08
zone 1 x zone 6   0.42 (*)  0.03 (*)
zone 5 x zone 2   0.71      0.08
zone 5 x zone 3   0.22 (*)  0.01 (*)
zone 5 x zone 4   0.53      0.07
zone 5 x zone 6   1.58      1
zone 6 x zone 2   0.05 (*)  0.008 (*)
zone 6 x zone 3  -0.47 (*)  0.001 (*)
zone 6 x zone 4  -0.17 (*)  0.005 (*)
zone 2 x zone 3   1.02      0.17
zone 2 x zone 4   1.50      0.48
zone 3 x zone 4   1.51      0.49

Legend: n = 10 or more: Overlap of 0,50 or less (*) and p
[less than or equal to]0,05 (*) (statistical difference).

Table 15 - Performance of the reception in each court zone.

     Zone               Reception          Min and Max     IC 95%

1 (back zone)   2.39 [+ or -] 0.66 (high)     0 and 3   2.24 to 2.53

5 (back zone)   2.31 [+ or -] 0.06 (high)     0 and 3   2.16 to 2.46

6 (back zone)   2.37 [+ or -] 0.65 (high)     0 and 3   2.23 to 2.51

2 (front zone)  3 (high)                      3 and 3   3 to 3
3 (front zone)  2.83 [+ or -] 0.40 (high)     2 and 3   2.40 to 3.26
4 (front zone)  2.53 [+ or -] 0.87 (high)     0 and 3   2 to 3.06

     Zone            ES and Classification

                zone 1 and zone 2 = 0.60 (medium)
                zone 1 and zone 3 = 0.43 (small)
1 (back zone)   zone 1 and zone 4 = 0.14 (very small)
                zone 1 and zone 5 = 0.08 (very small)
                zone 1 and zone 6 = 0.02 (very small)
                zone 5 and zone 2 = 0.68 (medium)
5 (back zone)   zone 5 and zone 3 = 0.51 (medium)
                zone 5 and zone 4 = 0.22 (small)
                zone 5 and zone 6 = 0.06 (very small)
                zone 6 and zone 2 = 0.62 (medium)
6 (back zone)   zone 6 and zone 3 = 0.45 (small)
                zone 6 and zone 4 = 0.16 (very small)
                zone 2 and zone 3 = 0.14 (very small)
2 (front zone)  zone 2 and zone 4 = 0.43 (small)
3 (front zone)  zone 3 and zone 4 = 0.28 (small)
4 (front zone)  -

Legend: Classification of the PC: 0 to 1 (low), 1.1 to 2 (medium) and
2.1 to 3 or more (high).

Table 16 - Results of the new statistic of the reception of each court
zone.

   Reception     Overlap     p

zone 1 x zone 2  -7,10      0,08
zone 1 x zone 3   0,55      0,11
zone 1 x zone 4   0,86      0,59
zone 1 x zone 5   1,23      0,27
zone 1 x zone 6   1,24      0,28
zone 5 x zone 2  -9,01      0,04 (*)
zone 5 x zone 3   0,17      0,04 (*)
zone 5 x zone 4   0,83      0,28
zone 5 x zone 6   2         1
zone 6 x zone 2  -8,75      0,04 (*)
zone 6 x zone 3   0,55      0,11
zone 6 x zone 4   0,85      0,28
zone 2 x zone 3   0.01 (*)  0,43
zone 2 x zone 4  -0,07 (*)  0,31
zone 3 x zone 4   1,34      0,40

Legend: n = 10 or more: Overlap of 0,50 or less (*) and p
[less than or equal to]0,05 (*) (statistical difference).
COPYRIGHT 2018 Instituto Brasileiro de Pesquisa e Ensino em Fisiologia do Exercicio. IBPEFEX
No portion of this article can be reproduced without the express written permission from the copyright holder.
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Author:Marques, Nelson Kautzner, Jr.
Publication:Revista Brasileira de Prescricao e Fisiologia do Exercicio
Date:Nov 1, 2018
Words:8169
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