# Changes in Defensive Variables Determining Success in the NBA over the Last 10 Years
## 4 Discussion  
Our study examined the significance of defensive variables in NBA competition between 2008 and 2019. The evolution of these variables over the years was also analyzed. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \begin{tabular}{c} **XGBoost (95\%** \\ **CI)** \\ \end{tabular} & \begin{tabular}{c} **Logistic** \\ **Regression** \\ \end{tabular} & \multirow{2}{*}{**Random Forest**} & \begin{tabular}{c} **Guassian** \\ **Naive Bayes** \\ \end{tabular} & \
\begin{tabular}{c} **K-Near** \\ **Nearbors** \\ \end{tabular} &
\begin{tabular}{c} **Support Vector** \\ **Machine** \\ \end{tabular} \\ \hline Accuracy & 0.86 & 0.81 & 0.84 & 0.84 & 0.84 & 0.83 \\  & (0.83 to 0.88) & (0.78 to 0.83) & (0.81 to 0.86) & (0.81 to 0.86) & (0.80 to 0.85) \\ \hline Precision & 0.87 & 0.81 & 0.84 & 0.84 & 0.84 & 0.83 \\  & (0.84 to 0.89) & (0.78 to 0.83) & (0.81 to 0.86) & (0.81 to 0.86) & (0.80 to 0.85) \\ \hline Recall & 0.86 & 0.81 & 0.84 & 0.84 & 0.84 & 0.83 \\  & (0.83 to 0.88) & (0.78 to 0.83) & (0.81 to 0.86) & (0.81 to 0.86) & (0.81 to 0.86) & (0.80 to 0.85) \\ \hline F1 score & 0.86 & 0.81 & 0.84 & 0.84 & 0.84 & 0.83 \\  & (0.83 to 0.88) & (0.78 to 0.83) & (0.81 to 0.86) & (0.81 to 0.86) & (0.81 to 0.86) & (0.80 to 0.85) \\ \hline \hline \end{tabular} Note. 95% CI: Confidence interval upper and lower limits.  
\end{table} 
Table 4: Prediction success of machine learning algorithm models. Figure 2: The effect of defensive variables on game results by years. Note. Numerical values on the y-axis represent the factor loading of the relevant defensive variable. Factor loading was used to indicate the importance of a variable in this model. Previous research has suggested that defensive performance indicators underscore the importance of the variables discussed in this study [27; 28; 29]. Many studies have explored the defensive and offensive variables. Our study sought to assess fluctuations in the defensive aspects of a game over a decade. Furthermore, it aimed to ascertain how the impact of these variables on competition outcomes changed over time. The findings indicate a notable increase in offensive rebounding among winning teams in recent years, which significantly affects game outcomes. Moreover, there was a significant shift in the influence of offensive rebounding on the competition results over time (\(p<0.05\)). However, this was not identified as the primary determinant of winning or losing teams. Previous research has presented conflicting results, according to the results of this study. A study examining performance indicators that distinguish winning and losing teams emphasized that offensive rebounds are a crucial defensive factor affecting game outcomes [30]. The disparities in findings can be attributed to the timing of the study, which was conducted before the implementation of new rules aimed at accelerating gameplay and was based on data from a single season. A study investigating dynamic models for evaluating team performance in the Basketball World Cup has identified that the number of offensive rebounds can significantly impact game outcomes [31]. In addition to examining the impact of offensive rebounds on the game, certain studies have delved into the individuals responsible for securing the rebounds. A study conducted in Spain aimed to identify the determinants of offensive rebound performance among elite basketball players [32]. Researchers suggest a direct correlation between players' positions and their success in securing offensive rebounds [32]. The discrepancies between the findings of this study and previous research can be ascribed to various factors, such as the retrospective nature of the data evaluation, the simultaneous consideration of different seasons in the analysis and the emphasis on regular season statistics. The findings indicated that defensive rebounding had a moderate impact on the game's outcome regarding wins and losses, favoring wins (ES = 1.39, [95% CI = 1.22-1.56], \(p=0.01\)). Furthermore, defensive rebounding increases by 12% in the case of a win.