This is the abstract of the paper:
The aims of this study were to identify variables which may potentially influence player performance, and to implement a statistical model to study their relative contribution in order to explain two outcomes: points and win score. We used all the possible variables affecting player performance creating a comprehensive database from two sources of statistical information about the NBA 2007 regular season: www.basketball-reference.com and www.nbastuffer.com. The data employed for the analysis were composed of 2187 cases (27 players * 81 games), having followed a filtering process. We dealt with a balanced study design with repeated measurements given that each player was observed the same number of games, and therefore the player was considered as a random effect. We carried out mixed models to quantify the variability in points and win score among players. Minutes played, the usage percentage and the difference of quality between teams were the main factors for variations in points made and win score. The interaction between player position and age was important in win score. We encourage managers and coaches of sports teams to choose appropriate methods according to their aims. Future research should take into consideration the use of models with random effects on players’ characteristics.
And this is the full reference of the paper
Casals, M. & Martínez, J. A. (2013). Modelling player performance in basketball through mixed models. International Journal of Performance Analysis in Sport, 13 (1), 64-82.