The purpose of this study was to present the multiple regression model with attack and counterattack spike as separate variables is more appropriate than the model with the attack and counterattack spike merged as one variable. Two multiple regression analyses were conducted that determine the relationship between situational efficiency parameters of volleyball game phases with the set score. Game phases included into both regression models were the serve, reception, spike, block and dig. One of the regression models had an attack and counterattack spike as two separate variables and the other one had them merged as one. A sample was 40 randomly selected volleyball sets played in the European League for Men in 2011 and 2012. Although the sample wasn't recent, the purpose of this methodologically based study was to present deficiency of merging attack and counterattack spike as one variable. Both multiple regression analyses determined a high and positive relationship between the situ ational efficiency of volleyball game phases with the set score. The spike as a merged variable had 32.5% of common variance with the set score. But when separated into two variables, the attack spike had only 8.9% of common variance and counterattack spike 26.5%. Although the spike was the game phase that had the highest relationship with the set score, the spike in the counterattack was the one that contributed. Ultimately the serve, reception and dig had higher common variance with the set score then the attack spike. Conclusion was that the attack and counterattack spike need to be considered as separate variables because of specificity of the attack and counterattack complexes of the volleyball game.
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