The research subarea of sports performance analysis on women`s basketball games is relatively scarce. Therefore, this study aims to explore the key variables that influence the game outcomes in the Women`s National Basketball Association (WNBA) during the 2023 season. Firstly, chi-square tests and k-means clustering to control variables were applied to categorise games into four groups (home balanced, home unbalanced, away balanced, and away unbalanced). Secondly, stepwise logistic regression was employed to identify key variables influencing game outcomes in each group. The game statistics variables that were significant in home and away balanced games were the field goals made (FG) (+) and attempted (FGA) (-), free throws made (FT) (+), total rebounds (TRB) (+), steals (STL) (+), turnovers (TOV) (-), and personal fouls (PF) (-). Additionally, 3-point field goals made (3P) were significant in home balanced games and assists (AST) (+) in the away balanced games. And FG (+), FGA (-), offensive rebounds (ORB) (+), STL (+), blocks (BLK) (+), and TOV (-) were significant in the home unbalanced games. In addition, in the away unbalanced group 4 variables included 3P (+), offensive rebound percentage (+), defensive rebound percentage (+), and total rebound percentage (+) were identified as key variables.
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