## 3 Results  
When all contests were combined, six outliers were found, three for each model. When looking at the individual events, only one outlier was found: the FIBA Asia Cup Women. During the regression analyses, three outliers were discovered using [PERSON]'s distance. All of these games were excluded from further investigation. Based on the partial correlation coefficient, it is possible to deduce that the variables that had the biggest influence on the final result in the monitored competitions, in the first model, were \(\Delta\)M2--two points made (\(\beta\) = 0.892; \(p<0.001\)) with partial correlation \(\mathrm{r_{p}}\) = 0.996; \(\Delta\)M3--three points made (\(\beta\) = 0.769; \(p<0.001\)) with partial correlation \(\mathrm{r_{p}}\) = 0.996; and \(\Delta\)MFT--free throws made (\(\beta\) = 0.426; \(p<0.001\)) with partial correlation \(\mathrm{r_{p}}\) = 0.979. In the second model, the variables that had the largest influence on the final outcome were as follows: \(\Delta\)FG%--field goal efficiency (\(\beta\) = 0.334; \(p<0.001\)) with partial correlation \(\mathrm{r_{p}}\) = 0.262; \(\Delta\)TO%--inefficiency of turnover (\(\beta\) = \(-0.445\); \(p<0.001\)) with partial correlation \(\mathrm{r_{p}}\) = \(-0.833\); \(\Delta\)DR%--efficiency of defensive rebound (\(\beta\) = 0.400; \(p<0.001\)) with partial correlation \(\mathrm{r_{p}}\) = 0.802; \(\Delta\)3%--three-point efficiency (\(\beta\) = 0.308; \(p<0.001\)) with partial correlation \(\mathrm{r_{p}}\) = 0.438; and \(\Delta\)2%--two-point efficiency (\(\beta\) = 0.305; \(p<0.001\)) with partial correlation \(\mathrm{r_{p}}\) = 0.273. In addition to standardized betas and significance, the value of partial correlation (\(\mathrm{r_{p}}\)) is highlighted, which expresses the influence of certain variables on the game's final outcome. In the first model, all three obtained variables have a very high correlation. In the second model, two acquired variables have a strong correlation (\(\Delta\)TO% and \(\Delta\)DR%), with \(\Delta\)TO% having a negative correlation. The variable \(\Delta\)3% has a substantial correlation, while two other variables (\(\Delta\)FG% and \(\Delta\)2%) have a minor correlation. Figures S1 (Model 1) and S2 (Model 2) (Supplementary Materials) display the final models for each competition, with \(\Delta\)PTS as the dependent variable and independent variables obtained through factor and regression analysis to reduce dimensionality. Table 2 shows 10 models with R\({}^{2}\) values over 0.640, indicating a high level of determination of \(\Delta\)PTS in relation to the independent variables. Three models demonstrate moderate relationships, while one model displays poor associations. The analysis of variance and F-statistic results indicate that all regression models are highly significant (\(p<0.05\)), with the exception of the 17 th AmeriCup 2023 model (\(p>0.05\)). Table 3 shows the findings for the occurrence of multicollinearity in the observed competitions. The reported values of VIF (Variance Inflation Factor) and tolerance indicate no deleterious multicollinearity in the obtained regression models. It should be noted that Model 2 for competitions 2021-2023 had a VIF rating greater than 10. After eliminating the variable \(\Delta\)FG%, the regression was re-run, resulting in a model without deleterious multicollinearity.