Marketing, Stats and Basketball

This is a blog about scientific research in basketball , and it is mainly focused on marketing and statistics. The aim of this blog is to disseminate findings from studies conducted by our research group, share ideas, and discuss. You can write either in English or Spanish (but we recommend English in order to make your comments more accessible to international colleagues). We will be happy to count with your opinion regarding the topics we discuss. Welcome to Basket-Research.

Tuesday, April 2, 2013

Modelling player performance in basketball through mixed models

I am pleased to announce the publication of a new paper (with my colleague Martí Casals) entlited: Modelling player performance in basketball through mixed models.

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: and 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.

Monday, March 11, 2013

Magic Metric Playing Cards

Some good news again about Magic Metric. In the following link, you will find an interesting coparison between the rating system created by Dick Mays and other well-known indexes such as PER or Efficiency.

Beyond the interpretation of which system is the best based on the rankings created, you should consider the theoretical foundations of them. Remember that the Magic Metric rating system is grounded on a system of equations that yield the values of the linear weights employed. PER and Efficiency are much more subjective indexes.