With teams` annual payrolls nearing $100 million and valuations for some teams exceeding $2 billion, the National Basketball Association is big business. That being the case, many pro-basketball general managers are turning to analytics to discover ways to improve organizational performance. The purpose of this paper was to highlight the results of an analytics-based assessment of both player and team performance, using data from the regular 2012-2013 NBA season. The analytical paradigm described in this paper consisted of a two-tiered hierarchical linear modeling design that combined a number of specific on-court and off-court factors. The analysis also introduced a relatively new sports performance metric—entropy, which can be used to measure the degree of disorder at both the player and the team level. The target variable was Hollinger`s Player Efficiency Rating. The results of the analysis revealed that a number of factors were statistically significant, including players` ages, entropy, and compensation. NBA general managers can use this modeling approach to evaluate both trade and draft opportunities.
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