The first cluster was high quality teams (HIGH) (with rankings ranged selleck chemical from 1st to 7th positions), the second cluster was intermediate quality teams (INT) (with ranking positions ranged from 8th to 14th positions), and the third cluster was low quality teams (LOW) (rankings lower than 15th place). In order to analyse the influence of quality of opposition (Marcelino et al., 2011) the sample was divided into three groups of game contexts ��HIGH vs. HIGH�� (n= 729 ball possessions), ��HIGH vs. LOW�� (n= 194 ball possessions), and ��LOW vs. LOW�� (n= 527 ball possessions). Table 1 International FloorbalL Federation (IFF) rankings based on the two previous World Floorball Championships (retrieved from www.floorball.org; accessed on 01.21.2012).

Statistical analysis Binomial Logistic Regression was used to estimate regression weights and odds ratios of the relation between performance indicators and covariates according to ball possessions effectiveness (Bar-Eli et al., 2006; Marcelino et al., 2011). In this non-linear model of regression, the estimated regression coefficients represent the estimated change in the log-odds, corresponding to a unit change in the corresponding explanatory variable conditional on the other explanatory variables remaining constant (Landau and Everitt, 2004). In the first stage, the performance indicators were tested individually and, in a second stage, the adjusted model was performed with all variables that showed a relation to ball possession effectiveness in the previous stage (Landau and Everitt, 2004).

Odds ratios (OR) and their 95% confidence intervals (CI) were calculated and adjusted for ball possession effectiveness. The statistical analyses were performed using SPSS for Windows, version 17.0 (SPSS Inc., Chicago IL), and statistical significance was set at p<0.05. Results The distribution of relative frequencies from the studied variables across quality of opposition contexts is shown in Table 2. Table 2 Distribution of relative frequencies from the studied variables across the three game contexts (HIGH vs. HIGH; HIGH vs. LOW; and LOW vs. LOW) in men��s floorball teams. In the first stage, the models of the Binomial Logistic Regression were computed with one variable at each step (Table 3), the results showed that during the three game contexts there were no significant interactions with the covariate game period (p>0.

05). The relationships found reflected the importance in ball possession effectiveness of some tactical variables Anacetrapib in each game context that were fitted in the second stage of the model. Table 3 Model and fit information for the frequency of technical and tactical indicators performed by the teams during the three game contexts according to ball possessions effectiveness in men��s floorball teams The adjusted model (Table 3) fitted the three game contexts (HIGH vs. HIGH: LRT=154.7, p<0.0001; HIGH vs. LOW: LRT=104.5, p<0.