ࡱ> egdv9 kbjbj&Ul4448lBXn(NAAAAAAA$C EAA2B222A2A22D4Vt;@;L V.KB^4/; ;B0B;0F1F;2Title: Discriminant Analysis of the Sets Won and the Sets Lost in A1 Italian Volleyball Running Title: Discriminant Analysis of Sets in Volleyball Discriminant Analysis of the Sets Won and the Sets Lost in A1 Italian Volleyball League Nenad Mareli1, Tomica Reaetar and Vladimir Jankovi1 1Faculty of Kinesiology, University of Zagreb Abstract: It is commonly known that training program efectivnes depends on quantity of scientific informations especialy ones related with specific equotation, learning and training methods, training content choice, training loads dosage and finally on knowledge about realization of tehnical - tactical elements in competition. Reasons of succesfull or unsuccesfull match result depends on chain of factors, but the mesurable part is related with indicators of situation efficiency of tehnical tactical elements or game phases during the matches. The sample consisting of 76 sets, obtained from 20 matches played in Italian mens A1 league, was employed in this study to determine, on the basis of five situational play-specific parameters, the differences between the sets won and the sets lost. To determine these differences, the discriminant analysis was used. The canonical discriminant function significantly differentiated between the sets won and the sets lost, at the level of significance p<0.00. The discriminant function was defined by the highest projection of the variable spike in the phase of attack, and by somewhat lower projections of the variables spike in the phase of counterattack, serve reception, block and serve. Key words: volleyball, statistical analysis, situational parameters INTRODUCTION The monitoring of play in team sports and its analysis are based on the evaluation of effects of situational parameters on the basis of volleyball records, notes made during the game (Cox, R.H., 1974.; Strahonja A. 1972), on the basis of video recordings (Eom and Schuttz, 1992) computer programs (Fellingham et al., 1994; Fontani et al., 2001) or various analyses of players efficiency during the game (Frhner, 1995). Uniformity of play elements evaluation methods has, for a long time, been a shortcoming of research conducted in volleyball. For instance, about twenty years ago a questionnaire was circulated among the coaches in the same league. The results showed that as many as 17 different variables have been used to evaluate the efficacy of actions executed by volleyball players (Jankovi & Mareli 1995). Statistical data collected during the matches played by top volleyball teams are frequently unavailable; they are also frequently statistically incomplete to employ inferential statistics such as regression analysis, discriminant analysis, etc. (It was possible to write this paper because one of the authors  V. Jankovi has coached one of the analyzed volleyball teams.) It is of great help in investigations employing multivariate methods that a uniform computer program (Datavolley) is now predominantly used in Europe by many national teams, and thus also by statisticians, to monitor volleyball games. The latest significant changes of volleyball rules (e.g. each mistake made by one team is a point for the opposing team) assign a different role to certain play elements in terms of winning a point. These changes open a new and unexplored space and they represent a big challenge for kinesiological research into team-specific characteristics of play. It is interesting to remind ourselves of some similar studies carried out during the old system of point counting; in these studies multivariate methods were employed. Eom and Schutz (1992) attempted to extract, from among the selected technical-tactical components, the best predictor or a group of predictors that determine the success of a team. The comparison of the technical-tactical elements attack and counterattack has shown that setting and spiking in the phase of attack, upon the serve reception and in the phase of the warded-off ball (the so-called counterattack) mustnt be treated in the same way. The study has shown that the differences between the matches won and the matches lost are more expressed in those technical-tactical elements that are executed while organizing a counterattack: block, court defense, setting and spike. Finally, the discriminant analysis has shown that BLOCK and SPIKE are the most important elements for determining the success of a team. On the sample of 149 sets Mareli (1994) carried out the regression analysis of the correlation between five phases of play with victory or defeat in a volleyball game. On the basis of the results of the matrix of intercorrelations it can be concluded that the highest presented value (.71) of the variables SPIK4 and SERV2 explains the importance of spike in the phase of attack and in the phase of counterattack. Additionally, the author concluded that the obtained correlation implied that a team that executed the defensive elements particularly well, among which the efficiency of counterattack was dominant, also had the biggest chances for success in a match. On the basis of the analysis of volleyball matches, several years later (Mareli, 1998) the same author researched the characteristics of team play of international volleyball for juniors. Mareli concluded that the analysis of differences between 8 phases of play in volleyball had shown, on the basis of the sets won and the sets lost, that the variables SPIKE IN THE PHASE OF ATTACK and SETTING IN THE PHASE OF COUNTERATTACK had the highest projection on the discriminant function, whereas the variables BLOCK, COURT DEFENSE, SETTING IN THE PHASE OF ATTACK and SPIKE IN THE PHASE OF COUNTERATTACK had a small projection. MATERIALS AND METHODS Sample of subject Volleyball sets presented the basis of investigation for this study that was carried out on the sample of 76 sets obtained from 20 matches played by the teams Brescial-Montichiari, Modena, Zetaline-Padova, Sisley-Treviso, Cosmogas-Forli, Del Monte-Ferrara, Maxicono-Parma, Piaggio-Roma, Tnt Alpitour-Cuneo, Lube-Macerata, Iveco-Palermo and Vallever-Ravenna in Italian mens A1 league in the season of 1999/2000. The teams monitored were the members of the best volleyball league in the world and they consisted of players of the best national selections in the world. Sample of variables The data were collected by means of a specialized computer recording system, the software Datavolley Rel. 5.0 of the firm DATAPROJECT. The follow-up of the matches is based on evaluating the efficiency of situational parameters of play, that is, of the phases: 1) SERVE (SERVE), 2) SERVE RECEPTION (RECEPT), 3) SPIKE IN THE PHASE OF ATTACK (SMATT), 4) BLOCK (BLOCK) and 5) SPIKE IN THE PHASE OF COUNTERATTACK (SMCATT), Zhang, 2000. The quality of executing each phase was evaluated on an ordinal 5-degree scale (Table 1) The first two degrees denote negative realization, for example, an error and an action that bring advantage to the opponent, the third degree on the scale denotes the execution in which an action is continued without advantage for a team, whereas the last two degrees either bring advantage after such actions or they end in winning a point. This procedure is standardized and used by some of the best national selections at all big international and national competitions. ------------------ Table 1 here ------------------ The phases of setting were not analyzed in this paper. One of the reasons why this has not been done is that the standardized way of monitoring (software DATAPROJECT) evaluates the phase of setting exclusively through the realization of the spike after a perfect pass of the ball to the setter. Other situations in the game are not recorded so that this phase of play was omitted from further analysis due to insufficient data. The sample of the criterion variable is the result, defined on a binary basis, of each individual set in the match (victory defeat). The frequencies of volleyball phases were used to collect the necessary data. Further, although each phase was ranked on the 5-degree scale, the collected frequencies were put in the formula: evaluation of a certain volleyball play phase on the 5-degree scale = (No. of fr error. x 1 ) + (No. of fr.negative realization x 2 ) + (No. of fr. Neutral x 3 ) + (No. of fr. Positive x 4 ) + (No. of fr. Ideal or a point x 5 ) total number of frequencies (error + negative realization + neutral + positive + ideal or a point). Data processing methods Such a calculation produces values on ordinal scale for each of the five phases of play. These values can be further used for statistical analysis. In compliance with the aim of the research, the data were processed by means of descriptive statistics. The basic statistical parameters of indicators were determined arithmetic means (X), minimum (Min), maximum (Max), summa (Sum), and standard deviations (SD) for each sample. The significance of differences between the groups was tested by means of a canonical discriminant analysis. RESULTS AND DISCUSSION The data obtained by descriptive statistics (Table 2, Figure 1) make it interesting to emphasize that the differences are evident between the sets won and the sets lost in the variables SPIKE IN THE PHASE OF ATTACK (sets won 3.99 vs. sets lost 3.66), SPIKE IN THE PHASE OF COUNTERATTACK (sets won 3.92 vs. sets lost 3.57) and in the variable BLOCK (sets won 2.84 vs. sets lost 2.56). The reason, most probably, lies in the fact that the largest number of points in a set is scored in these variables. ------------------ Table 2 here ------------------ The results of the eigenvalue, of canonical correlation, of the chi-square test, as well as the number of degrees of freedom and the level of significance of the discriminant function are presented in Table 3. The obtained results make it possible to conclude that the discriminant function significantly discriminates the sets won from the sets lost at the level of significance 0.00 (p<0.00), with a relatively high canonical correlation (.58). It may be concluded that the five volleyball phases differentiate well between the sets won and the sets lost. ----------------- Table 3 here ----------------- Table 4 displays the correlation between the variables with the discriminant function, as well as the results of centroids of the sets won and the sets lost on the discriminant function. The sets lost are to be found on the negative pole of the discriminant function, whereas the sets won are to be found on its positive pole. The structure of the discriminant function is also bipolar. The positive pole is defined by all variables, whereas no variable was to be found on the negative pole. The discriminant function is defined by the highest projection of the variable SPIKE IN THE PHASE OF ATTACK (SMATT) and by a somewhat lower projection of the variable SPIKE IN THE PHASE OF COUNTERATTACK (SMCATT) and SERVE RECEPTION (RECEPT), whereas the variables BLOCK and SERVE had the lowest projections. In one of the previous research studies9 it was found that spike in the phase of attack and setting in the phase of counterattack significantly affected either the victory or the defeat in a set. By employing discriminant analysis Cox, (1974) found that the monitored sequential skill events were: spike, block, serve reception, dig, serve and setting. The author concluded that the contribution of the first two skills listed to the anticipation of the teams success was larger than the contribution of the remaining four skills together. Eom and Schutz2 have also found that block, spike in the phase of attack and spike in the phase of counterattack were the most important for success of a team. In this investigation the variable SPIKE IN THE PHASE OF ATTACK (.71) proved to have the highest predictive value with respect to the criterion. The explanation for such a high predictive value may be found in the fact that spike in the phase of attack is mostly executed after an ideal serve reception, upon which the setter has the opportunity to organize a fast and a combined attack that will hinder the timely formation of the opponents block, thus obstructing the opposing teams anticipation of possible ways of defense. In contemporary volleyball the spikers who can efficiently realize the attack in a situation when the opponent is creating the group block are considered to be particularly effective. Additionally and speaking in favor of the previously said, in the new system of play, the Rally Point System (RPS), a point is scored in attack upon the successful realization of a spike, in contrast to the previous system in which the change of serve occurred upon the spike in the phase of attack. This is substantiated by the fact that the number of spike frequencies is the largest in the phase of attack, and it consequently affects the outcome either victory or defeat. SPIKE IN THE PHASE OF COUNTERATTACK (.37) had a somewhat lower magnitude, probably due to the fact that the new system of play shortened the time necessary to win a point. The reason may be sought in the highly dangerous jump serve that has two goals: to win a point or to make the serve reception difficult so that consequently the point is won by setting up a two-man or a three-man block. Still, if the players delivering the serve and creating the block do not win the point, and the court defense catches the opponents attack, the spike for the execution of counterattack is organized. The variable RECEPT (serve reception) (.33) has a somewhat lower statistically significant magnitude. Among coaches, the importance of serve reception is indisputable, and a wish to elicit the best possible response to dangerous serves resulted in introducing a new player in the body of rules a player specialized only for receiving either a serve or a spike (libero). The variables SERVE (.25) and BLOCK (.28) have also proved to be statistically significant and predictive. The possibility of scoring a point on a serve is 1-2 points per set on average, however, the serve resembles white chess pieces. The way in which the white chess pieces open dictates further course of play. Both winning the point on ones own serve and a serve error have a significant role for the final outcome. An optimal number of error serves in successful teams is about 3.5 points per set (Mareli, 1998). This means that in a five-set match the teams may make on average up to 15 error serves and still win the match. A somewhat larger number of points per set (approximately 3-4) were scored by blocking than by serving. However, the result of introducing into play a new player libero (a more precise serve reception and a better organization of attack) was that the blockers had to parry the opposing spikers by a one-man block, which made higher efficiency in this phase of play significantly more difficult. ----------------- Table 4 here ---------------- Table 5 shows the results of the classification of the sets won and the sets lost on the basis of the discriminant function. Out of 50 sets lost, 38 were well classified, which amounts to 82.61%, whereas out of 26 sets won 18 were well classified, which amounts to 60%. The results confirm a relatively high discriminant value of the variables suggested for the purpose of analyzing volleyball play in terms of the sets won and the sets lost. ----------------- Table 5 here ----------------- CONCLUSION Significant changes of volleyball rules have become the challenge for new kinesiological investigations. It is hoped that the analysis presented in this paper will contribute to a better understanding of changes in top-level volleyball. The intention was to focus on the differences between situational parameters of play in terms of the sets won and the sets lost. To achieve the set goals, canonical discriminant analysis was used. Additionally, the differences were analyzed by means of standard descriptive indices. The canonical discriminant function significantly differentiated between the sets won and the sets lost at the level of significance p<0.00 and the canonical correlation of .58, so that it may be concluded that the predictor variables (serve, reception, block, spike in the phase of attack and spike in the phase of counterattack) statistically significantly differentiated between the sets won and the sets lost. The results showed that the positive pole was defined by all variables, that is, that no variable was to be found on the negative pole. The variable spike in the phase of attack defined the discriminant function with the highest projection, and the variables spike in the phase of counterattack and serve reception with a somewhat smaller projection. The projection of the variables block and serve in defining the discriminant function was the smallest. References: Cox, R.H. (1974). Relationship betwen selected volleyball skill components and team performance of mens northwest AA volleyball teams. Research Quarterly for Exercise and Sport, 45, (1), 441-446. Eom, H.J., & Schuttz, R.W. (1992). Statistical Analyses of Volleyball Team Performance. Research Quarterly for Exercise and Sport, 63, (1), 11-18. Fellingham G. W., Collings B. J., & McGown, C.M. (1994). Developing an Optimal Scoring System With a Special Emphasis on Volleyball. Research Quarterly for Exercise and Sport, 65, (3), 237-243. Fontani, G., Ciccarone, G., & Giulianini, R. (2001). Nuove regole di gioco ed impegno fisico nella pallavolo. Scuola dello Sport, 50, 14 20. Frhner, B. (1995). Aktuelle Computer-und Videotechnologie zur systematischen Untersuchung des technisch-taktischen Handelns im Volleyball aus individueller und mannschaftstaktischer Sicht. Leistungssport, 3, 4-10. Mareli, N. (1994). Utjecaj situacijskih parametara u odbojci na rezultat u odbojkaakom setu. [Influence of situation-related parameters in volleyball on the result in a set. In Croatian.] Hrvatski aportskomedicinski vjesnik, 9 (2-3), 70-76. Mareli, N. (1998). Kinezioloaka analiza karakteristika ekipne igre odbojkaaa juniora. [Kinesiological analysis of the junior team play characteristics in volleyball. In Croatian.] (Unpublished doctoral dissertation, University of Zagreb). Zagreb: Fakultet za fizi ku kulturu Sveu iliata u Zagrebu. Strahonja, A. (1972). Metode za prikupljanje informacija o igri odbojke. [Methods for collecting information on play in volleyball. In Croatian.] Kineziologija, 2 (1), 65-68. Zhang, R. (2000). How to profit by the new rules. The Coach, 1, 9-11. Table 1: Ordinal 5-degree scale Ordinal 5-degree scaledouble negative realisation (=) error, losing a pointnegative realisation (-) action that brings advantage to the opponent neutral realisation (/) action is continued without advantage for a team positive realisation (+) brings advantage after actions double positive realisatiohn (#) winning a point  Table 2: Descriptive statistics of volleyball-specific phases VARIABLEXMinMaxSt. Dev.Sum. SETS WONSERVE2.361.923.36 0.29 70.73RECEPT4.013.474.48 0.27  120.22 BLOCK2.841.254.30 0.61 85.15SMATT3.993.184.65 0.53 119.60SMCATT3.922.505.00 1.52 117.46 SETS LOSTSERVE2.271.852.76 0.22 104.24RECEPT3.832.414.62 0.43 176.15BLOCK2.581.574.84 0.67 118.75SMATT3.662.944.30 0.33 168.14SMCATT3.571.754.77 0.69 164.42  EMBED Excel.Chart.8 \s  Fig. 1. Arithmetic means for the sets won and the sets lost. Table 3: Eigenvalue (), canonical correlation (R), chi-square test ((2), number of degrees of freedom (df) and the level of significance of the discriminant function (p). (R(2dfp00.500.5829.0750.00 Table 4: Correlation of variables with the discriminant function and the position of centroids of groups on the discriminant function VARIABLERoot 1SERVE0.25RECEPT0.33BLOCK0.28SMATT0.71SMCATT0.37Root 1G_1:0-0.56G__2:10.87 Table 5: Classification matrix of the sets won and the sets lost on the basis of discriminant function Classification percentageG_1:0 p=.60526G_2:1 p=.39474G_1:082.61388G_2:160.001218Total73.685026 N. Mareli Faculty of Kinesiology, University of Zagreb Horvaanski zavoj 15 Tel. ++385-1-3658-602 10 000 Z A G R E B C R O A T I A SA}ETAK Ope je poznato da je za efikasnost programiranje treninga u va~na koli ina znanstvenih spoznaja, osobito onih koje su vezane uz metode u enja i vje~banja, izbor sadr~aja treninga, doziranja optereenja & i kona no spoznaja o relacijama tehni ko-takti kih elemenata na natjecanju. Razlozi uspjeanog ili neuspjeanog ishoda utakmice ovise o itavom nizu faktora, meutim ono ato je mjerljivo, odnosi se na pokazatelje situacijske efikasnosti tehni ko-takti kih elemenata ili faza igre na utakmicama. U ovom istra~ivanju koristili smo se uzorkom od 76 setova dobivenih na 20 utakmica talijanske A1 lige s ciljem utvrivanja razlika izmeu dobivenih i izgubljenih setova na osnovu pet situacijskih parametara igre. Razlike su utvrene metodom diskriminacijske analize. Kanoni ka diskriminacijska funkcija zna ajno razlikuje dobivene od izgubljenih setova na razini zna ajnosti p<0.00 . Najveom projekcijom diskriminativnu funkciju definira varijabla sme  u procesu napada, te neato ni~im projekcijama varijable: sme  u procesu kontranapada , prijem servisa , blok i servis. 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