Measuring the efficiency of NBA teams: The effect of the change in salary cap
Antonakis Theodoros
A dissertation submitted in partial fulfillment of the requirements for the degree of Master of Science in Applied Economics & Data Analysis
School of Economics and Business Administration Department of Economics
Master of Science “Applied Economics and Data Analysis”
August 2019 University of Patras, Department of Economics Antonakis Theodoros © 2019 − All rights reserved Three-member Dissertation Committee
Research Supervisor: Kounetas Konstantinos Assistant Professor Dissertation Committee Member: Giannakopoulos Nicholas Associate Professor Dissertation Committee Member: Manolis Tzagarakis Assistant Professor
The present dissertation entitled
«Measuring the efficiency of NBA teams: The effect of the change in salary cap »
was submitted by Antonakis Theodoros, SID 1018620, in partial fulfillment of the requirements for the degree of Master of Science in «Applied Economics & Data Analysis» at the University of Patras and was approved by the Dissertation Committee Members. I would like to dedicate my dissertation to my Research Supervisor, Kon- stantinos Kounetas, for his guidance and co-operation and to my parents for their support throughout my postgraduate studies. Acknowledgments
I would like to express my sincere gratitude to Dr. Nickolaos G. Tzeremes, As- sociate Professor of Economic Analysis Department of Economics, University of Thessaly, for his support with modelling the two-stage DEA additive decomposi- tion procedure. Summary
The aim of this dissertation is to use a two-stage DEA approach to perform an effi- ciency analysis of the 30 teams in the NBA. Particularly, our purpose is to estimate efficiency through a two-stage DEA process for NBA teams due to the increase of salary cap, in the first part and in second, the separation of teams based on the Conference (West-East) to which they belong, we estimate metafrontier and find- ing technology gaps. We decompose the overall team efficiency into two additive efficiencies: the first-stage salary cap efficiency that measures the effectiveness of transforming payrolls to on-court performance and the second-stage on-court ef- ficiency that measures the efficacy of transforming players’ on-court performance to a better winning rate and higher revenue. For this reason, 30 teams in the NBA are being tested for 18 seasons, from 2001-2002 season to 2018-2019. Empir- ical results show that teams belonging to the Western conference achieve higher overall efficiency than those in the East. Utah Jazz, San Antonio Spurs, Chicago Bulls, Atlanta Hawks, Golden State Warriors and Toronto Raptors are among the top efficient teams, whereas New York Knicks, Dallas Mavericks, Orlando Magic, Minnesota Timberwolves and New Orleans Pelicans rank among the lowest effi- cient teams. Regarding, the conference efficiency scores the empirical results show that on average the overall team efficiency scores range between 71.2% and 91.03% through the sample period. It is understood that the continuous increase in the salary cap has affected the performance of the teams to the best, and as shown the results, firstly there is an increase in efficiency scores over time as well as a decrease in the variation of efficiency which helps to develop the competitiveness of the teams.
Keywords: Sports efficiency, NBA, two-stage DEA approach, Metafrontier, Salary cap
i Περίληψη
Σκοπός της παρούσας διατριβής είναι η χρήση μιας προσέγγισης DΕΑ δύο σταδίων για την ανάλυση αποτελεσματικότητας των 30 ομάδων στο ΝΒΑ. Ιδιαίτερα, ο σκοπός μας είναι να υπολογίσουμε την αποτελεσματικότητα μέσω μιας διαδικασίας DΕΑ δύο σταδίων για τις ομάδες ΝΒΑ λόγω της αύξησης του salary cap, στο πρώτο μέρος και δεύτερον, τον διαχωρισμό των ομάδων με βάση την περιφέρεια (West-East) στην οποία ανήκουν, εκτιμούμε τα μεταβατικά όρια και την εξεύρεση κενών στην τεχνολογία. Αποσυντίθεται η συνολική αποδοτικότητα των ομάδων σε δύο πρόσ- θετες αποδόσεις: η αποδοτικότητα του πρώτου σταδίου (salary cap efficiency) που μετρά την αποτελεσματικότητα του μετασχηματισμού των πληρωμών σε επιδόσεις στο γήπεδο και τη δεύτερο στάδιο (on-court efficiency) που μετρά την αποτελεσ- ματικότητα των παικτών να μετατρέπουν την απόδοση τους στο γήπεδο σε νίκες και υψηλότερα έσοδα. Για το λόγο αυτό, 30 ομάδες στο ΝΒΑ δοκιμάζονται για 18 σεζόν, από την περίοδο 2001-2002 έως το 2018-2019. Τα εμπειρικά αποτελέσματα δείχνουν ότι οι ομάδες που ανήκουν στη δυτική περιφέρεια επιτυγχάνουν μεγαλύτερη συνο- λική αποτελεσματικότητα από εκείνες στην Ανατολή. Η Utah Jazz, San Antonio Spurs, Chicago Bulls, Atlanta Hawks, Golden State Warriors, Toronto Raptors είναι από τις πιο αποδοτικές ομάδες, ενώ οι New York Knicks, Dallas Mavericks, Orlando Magic, Minnesota Timberwolves, New Orlean Pelicans είναι οι ομάδες με την χαμηλότερη αποτελεσματικότητα. ΄Οσον αφορά τα αποτελέσματα σε επίπεδο περιφέρειας, τα εμπειρικά αποτελέσματα δείχνουν ότι κατά μέσο όρο οι συνολικές βα- θμολογίες αποτελεσματικότητας των ομάδων κυμαίνονται μεταξύ 71,2% και 91,03% κατά τη διάρκεια της περιόδου του δείγματος μας. Είναι κατανοητό ότι η συνεχής αύξηση του salary cap έχει επηρεάσει τις επιδόσεις των ομάδων προς το καλύτερο και, όπως φαίνεται από τα αποτελέσματα, καταρχήν υπάρχει αύξηση της αποδοτικότητας με την πάροδο του χρόνου, καθώς και μείωση της διακύμανσης της αποδοτικότητας που συμβάλλει στην ανάπτυξη της ανταγωνιστικότητας των ομάδων.
Keywords: Sports efficiency, NBA, two-stage DEA approach, Metafrontier, Salary cap
i Contents
1 Introduction 1
2 Literature Review 5
3 Methodology 9 3.1 Additive efficiency decomposition approach in the two-stage process9 3.1.1 Two-stage DEA model: Constant returns to scale ...... 10 3.1.2 Two-stage DEA Model: Variable returns to scale ...... 15 3.2 Technology heterogeneity in NBA teams ...... 18
4 Data 19 4.1 Descriptive Statistics ...... 21
5 Empirical Results 23 5.1 Overall efficiency scores ...... 23 5.1.1 Salary cap and on-court efficiency ...... 28 5.2 Efficiency scores by Conference ...... 30 5.2.1 Salary cap and on-court efficiency by conference ...... 35 5.3 Technology Gap ...... 36
6 Conclusions 39
Appendix A Overall team performance scores 42
Appendix B Efficiency scores by Conference 62
Appendix C Technology gap 82
References 100
ii List of Tables
1 Summary statistics of empirical data ...... 21 2 Number of avg. wins, attendance and team performance by Con- ference ...... 22
3 Overall team performance scores ...... 24 4 Overall team performance scores ...... 25 5 Conference team performance scores ...... 30 6 Conference team performance scores ...... 32 7 Technology Gap ...... 37
A.1 Overall team performance scores ...... 42
B.1 Efficiency score over East conference ...... 62 B.2 Efficiency scores over West conference ...... 72
C.1 Technology gap ...... 82
iii List of Figures
1 Two-stage framework of overall team performance ...... 3
2 Relationship between Team Salary Cap and Team Performance . . 22
3 Overall efficiency and stage efficiency versus Wins ...... 26 4 Boxplot of Overall and Stage efficiency by Conference ...... 27 5 Kernel Density of overall efficiency and stage efficiency through time 27 6 Conference efficiency and stage efficiency versus salary cap . . . . . 33 7 Boxplot of Conference and Stage efficiency by Conference ...... 33 8 Kernel Density of conference efficiency and stage efficiency through time ...... 34
iv Chapter 1
Introduction
National Basketball Association (NBA) is one of the four major professional sports leagues in the United States and Canada and it is widely considered to be the pro- fessional basketball league in the world due to popularity, advertising and broad- casting rights. According to Forbes, total revenue across the organization reached $8 billion last season. Each one of the teams is worth at least $1 billion, and a team is worth on average $1.9 billion for last year, about three times the valuation from just five years ago. NBA broadcasts 277 regular season games nationally per year plus 90 or so playoff games. TV accounts for most of the NBA’s revenue. For the 2016-2017 sea- son, TNT and ESPN reached an agreement with the NBA by signing a $ 24 billion TV rights deal. Furthermore, national TV contracts produce enough revenue to shelter salaries. However, those national contracts still leave 1078 regular-season games unaccounted for. Filling in that gap, local TV contracts can gross between $120 million and $150 million annually. The top five markets outside the U.S. as of the end of the 2017-18 season were China, Australia, Brazil, Canada, and Mexico. In Europe, the UK is the No. 1 market for NBA spectators, followed by Germany and France. For the first time in the NBA’s history, teams attempted to place sponsors on their jerseys thus increasing team’s net profits by $9.3 million annually. According to ESPN, for the 2018-2019 season, teams saw an average
1 attendance from just under 15,000 to just over 20,000 per home game. With tick- ets costing close to $100 on average brought in revenue of between $1.5 and $2 million. Calculating all the above creates the total budgets of the teams, which are dif- ferent for each team. For this reason and to avoid any issues of unfair competition, the NBA Organizing Committee established the salary cap. The NBA salary cap is the limit to the total amount of money that National Basketball Association teams can pay their players. Such as various professional sports leagues, the NBA has a salary cap to control costs and benefit parity, de- fined by the league’s collective bargaining agreement (CBA). This limit is subject to a complex system of rules and exceptions and is calculated as a percentage of the league’s revenue from the previous season. Under the CBA approved in July 2017, the cap will continue to differ in forthcoming seasons based on league revenues. For the 2019–20 season, the cap is set at $109.14 million. To ensure the players get their share of the basketball-related income (BRI), teams are required to spend 90 percent of the salary cap each year, the salary floor for the 2019–20 season is $98.226 million. In December 2016, the league and the players’ union reached a tentative agreement on a new CBA, with both sides ratifying it by the end of that month. The new agreement will run through the 2023–24 season, with either side able to optout after the 2022–23 season. The sport economics literature regarding the use of salary cap in professional team sports has been widely examined by several authors (Staudohar, 1998; Quirk and Fort, 1992; Vrooman, 1995, 2000; Késenne, 2000, 2003; Dietl et all., 2012). Specifically, Quirk and Fort (1992) indicate that salary cap can enhance the com- petitive equilibrium as they avoid big market clubs from offering for additional talent the entire marginal price. This impact enables small-scale clubs to main- tain their star players. Vrooman (1995, 2000) claims that salary cap represents a collusion of teams to increase their league profits by regulating employment ex- penses at the cost of the league’s less competitive equilibrium. Késenne (2000)
2 creates a two-team model composed of a small and a big market club, demon- strating the ability to enhance the competitive equilibrium as well as allocation of player’s wages throughout the league by a National Basketball Association (NBA) type of salary cap, described as a set proportion of total league profits separated by numbers of players over the previous season. In addition, it demonstrates that both the tiny club and the big club will gain in revenues. Rathke (2009) analyzes in a league with profit-maximizing clubs how an exogenously determined salary cap is impacting social welfare. Dietl et all. (2012) demonstrate that an increase in salary cap increases the balance of competition and reduces overall pay in the league. We also show that social welfare can increase if fans prefer aggregated tal- ent relatively highly, because this means an excessively unbalanced unregulated group. Our research focuses on the efficiency of the teams, we preferred the salary cap (input), as the element of our production process since it shows us the finan- cial ability that teams have to buy players to reach the desired result, which is none other than to increase profits through tickets and winnings (outputs) will succeed. Figure 1 shows a two-stage structure for sport teams production process. Teams uses the salary cap at the first stage on recruiting talented or well-established players. In the second phase of manufacturing the main objective is to combine the performance of an individual player to produce final results such as won games and receipts. This two-stage production concept has been used for team efficiency analysis in MLB; for example. Lewis et al. (2004) and Sexton and Lewis (2007).
Figure 1: Two-stage framework of overall team performance
3 The aim of this study is to use a two-stage DEA approach to perform an effi- ciency analysis of the 30 teams in the NBA. Particularly, our purpose is to estimate efficiency through a two-stage DEA process for NBA teams due to the increase of salary cap, in the first part and in second, the separation of teams based on the Conference (West-East) to which they belong, we estimate metafrontier and finding technology gaps. For this reason, we take in the two-stage DEA approach developed by Chen et al. (2009) to analyze the efficiency of NBA teams. We decompose the overall team efficiency into two additive efficiencies: the first-stage salary cap efficiency that measures the effectiveness of transforming payrolls to on-court performance and the second-stage on-court efficiency that measures the efficacy of transforming players’ on-court performance to a better winning rate and higher revenue. Evaluations obtained using this method empower team managers to identify the problem that either the first or second stage should be dealt with first by considering the relationship of the two stages and then choosing which stage they should take first to increase overall efficiency.
4 Chapter 2
Literature Review
For player outputs and team outputs are mostly multiple outputs, DEA is wide adopted for evaluating efficiency within the sports business. Two streams of studies adopting the DEA model in measuring efficiency exist within the sport’s economic science literature. One involves measure player efficiency and therefore the other measures team efficiency by giving the operation method as a one-stage framework. However, another perspective in measuring team efficiency. Team operations dur- ing a two-stage framework, demonstrates its benefits over a regular DEA model (Sexton and Lewis 2003). The analysis of player efficiency is rising within the literature however remains rare. Anderson and Sharp (1997) are the first to construct a composite index to measure pitcher efficiency in Major League Baseball (MLB). Hakes and Turner (2011) examine tendencies in player productivity related with their ages using panel data in MLB. Yang (2014) measure team performance constructing an over- all player performance index for using as an intermediate factor in two-stage DEA in NBA teams. In the other hand Cooper et all (2009) construct multipliers to evaluate various outputs and then apply DEA to specify component profiles and overall indices of basketball players’ performances. Concerning the efficiency evaluation at the team level, a large amount of stud- ies has occurred recently, though they are dealing with sports production as a
5 one-stage framework. Some current studies have begun to establish the concept of multiple production stages into the efficiency evaluation of sports teams. Anderson and Sharp (1997) published one of the first papers that implemented a DEA approach to evaluate sports performance, namely that of baseball batters. However, most of the previous works on DEA applied to sports discusses soccer leagues. Therefore, Haas (2003a) presented an input-oriented DEA model, both VRS and CRS, that takes total wages and salaries as inputs, plus population of the clubs’ hometown as a non-discretionary input variable. The outputs include points awarded during the season and the total revenue figures which serve as an indicator for a team’s success in international competitions. Haas (2003b) studied the technical efficiency of the Major Soccer League in the United States consider- ing players’ wages and head coach’s wage as inputs and awarded points, number of viewers and revenues as outputs. Espitia-Escuer and García-Cebrián (2006) studied the potential of the teams in the Spanish soccer league between the years 1998 and 2005, analyzing each year separately. The evaluation conducted from an output-oriented perspective: the efficiency in acquiring better results consid- ering the available resources on the domain of play. With the purpose of perform that objective, they considered a system which takes as inputs the attacking and defensive moves against the opposing team and the total points awarded as the single output. Sexton and Lewis (2004) apply the Network DEA Model under a two-stage structure to analyze MLB team efficiency, which allows them to look deeper into both front office and on-field operations. Lewis et all (2007) use a two- stage DEA model as a part of a larger analysis to determine the minimum total player salary required to be competitive in each non-strike year of MLB. Hofler and Payne (2006) use a stochastic frontier approach to learn if better coaching will raise team’s efficiency in NBA teams. Regrettably, the above-mentioned research uses the two-stage DEA method to assess the efficiency separately, ignoring the possibility of a relationship be- tween the two stages. Jane et al. (2010) examine whether players’ individual and
6 club-level efficiencies have significant impacts on club performance in Taiwan’s professional baseball league. Empirical results illustrate a positive relationship among individual player efficiency, club-level efficiency, and team performance in terms of winning rate. Tiedemann et al. (2011) present an innovative model for evaluating the performance of players in German soccer. Their estimates expose a transparent affirmative relationship between a team’s average player efficiency score and its rank within the league standings at the tip of the season. Barros et al. (2010) and Barros and Garcia-del-Barrio (2011) implemented a DEA bootstrapping method to investigate the technical efficiency of Brazilian first soccer league and Spanish first division soccer league, respectively. In the first stage, a bootstrapped DEA is used to figure out the relative efficiency scores. Afterwards, in the second stage, the Simar and Wilson’s procedure is applied to bootstrap the DEA scores with a truncated regression, to further explain the in- fluence of variables in the efficiency results. As far as we know, there are only a couple of papers on DEA applied to basketball. Yang (2014) estimate the efficiency of National Basketball Associa- tion (NBA) teams based on a two-stage DEA framework. Applying the additive efficiency method, overall team efficiency decomposed into first-stage wage effi- ciency and second-stage on-court efficiency and discover the indepented endoge- nous weights for each stage, respectively. The empirical results illustrate that NBA teams present a better performance on wage efficiency than for on-court ef- ficiency, as on-court efficiency is affected by many overwhelming factors. Moreno and Lozano (2012) applied a Network DEA approach to evaluate the efficiency of NBA teams is compared with a black-box (i.e. single-process) DEA approach. The study assumes the distribution of the budget between first-team players and the rest of the wages. The results demonstrate that network DEA has more dis- criminating power and predicts more insight than the traditional DEA approach. Moreover, in terms of discrimination on wages and how this affects the prof- itability of the groups, again most research focuses on American football and
7 baseball. First, Depken (1999) addresses how wage differences impact teamwork on professional baseball teams. The spectacular increase in baseball salaries has detonate interest that wage disparity among team player, may cause a breakdown of team performance. As team productivity is objectively defined and accurate measures of player salaries are available, it is relatively easy to test two competing hypotheses of wage disparities on team performance. Mondello and Maxcy (2009) examine the effects of salary distribution and incentive pay on team performance for the National Football League (NFL). The empirical results have shown a rela- tionship among improved on-field performance and increased payroll, lower levels of salary distribution, and increased incentive payments. In the other hand, con- cerning the National Basketball Association (NBA) Katayama and Nuch (2006) evaluate the causal effect of team salary dispersion on team performance. They used three measures of salary distribution and examine the effect at three levels: whether the outcome of the game is influenced by salary dispersion among (1) players participating in the current game (active players), (2) players who played more than half of their team’s games in a season (regular and occasional players) and (3) the entire player population. Regardless of the measures used, salary dis- persion does not influence team performance. As observed by our research in the literature, some recent research has adopted the two-stage DEA approach in the field of sports, with most articles focusing on the site of football and baseball. Furthermore, we saw that wages affect the per- formance of the teams. Thus, the main purpose of this research is to determine whether the performance of the NBA teams is affected by the increase in the salary cap over time by using the additive efficiency decomposition in the two-stage DEA developed by Chen et al. (2009).
8 Chapter 3
Methodology
3.1 Additive efficiency decomposition approach
in the two-stage process
Additive efficiency decomposition approach in the two-stage process model has been developed by Chen et all. (2009) and it’s a model that utilizes linear pro- gramming to obtain results. This two-stage process is suitable to assist the re- sourceful stages of the innovative procedure. It considers the outputs of the first stage as an intermediate output and then transformed as an input to the second stage. First, it calculates the overall efficiency and provides weights to each stage. Through these weights, it calculates the unique efficiencies of each stage. The stage that has given averting importance has its efficiency calculated first. The overall efficiency can then be obtained through the efficiencies of the two stages through a weighted mean. An alternative way would be a simple arithmetic mean, but the weighted one has been chosen in order to emphasize the importance of each stage.
9 3.1 Additive efficiency decomposition approach in the two-stage process
3.1.1 Two-stage DEA model: Constant returns to scale
Let us assume n DMUs (NBA teams), and that each DMUj (j = 1, 2,... n) has
K inputs to the first stage, xij, (i = 1, 2,... m), which in our case is salary cap.
It also has D outputs from this stage, zdj, (d = 1, 2,... D), which is the Team Performance. These D outputs then become the inputs to the second stage and are referred to as intermediate measures. The outputs from second stage are denoted yqj, (q = 1, 2,... s), and they represent team total Wins and Annual Attendance. The (CRS) efficiency scores in the first and second stages can be calculated with the following two CCR models (1), (2), respectively:
PD ηAz θ1 = max d=1 d dj0 j0 Pm i=1 vixij0 s.t. PD A d=1 ηd zdj Pm 6 1, j = 1, ..., n (3.1) i=1 vixij
A ηd , vi > 0
and Ps u y θ2 = max q=1 q qjo jo PD B d=1 ηd zdjo s.t. Ps u y q=1 q qjo < 1, j = 1, ..., n (3.2) PD B d=1 ηd zdjo
B ηd , ur > 0
The overall CRS efficiency score can be measured from the following CCR model: Ps q=1 uqyrjo max Pm i=1 vixij0
s.t.
10 3.1 Additive efficiency decomposition approach in the two-stage process
Ps q=1 uqyqj Pm ≤ 1, j = 1, .., n (3.3) i=1 vixij
vi, uq > 0
In two-stage DEA approach, it is required that the input of the second stage to be the anticipated output of the first stage (Kao and Hwang’s,2008).Kao and Huang
a B assume that ηd = ηd = ηd , and their model for measuring the overall efficiency of a DMU is donated by:
PD η z Ps u y Ps u y θ = max d=1 d dj0 = q=1 q qj = q=1 q qjo j0 Pm PD Pm i=1 vixij0 d=1 ηdzdj i=1 vixijo s.t. PD d=1 ηdzdj Pm 6 1, j = 1, ..., n (3.4) i=1 vixij
PS q=1 uqyqj PD < 1, j = 1, ..., n d=1 ηdzdj
vi, uq, ηd > 0
It can be detected from the objective function of model (4) that the over-
1 2 all efficiency is the product of the efficiencies of the two stages, i.e., θjo ∗ θjo = Ps u y PD ηAz Ps u y q=1 q qjo = θ ,where θ1 = d=1 d dj0 and θ2 = q=1 q qjo and (*) denotes Pm jo j0 Pm jo PD B i=1 vixij0 i=1 vixij0 d=1 ηd zdjo optimal value from model (4).
a B Mention that ηd = ηd means that the values of inputs of the first stage is the same as the values of the variables that insert the second stage as intermediate products. In the interest of molding two-stage processes in a more general way, and no- tably to allow for VRS settings, we propose that rather than combine the stages in a multiplicative (geometric) manner as in Kao and Huang, we use a weighted additive (arithmetic mean) approach.
11 3.1 Additive efficiency decomposition approach in the two-stage process
We aim to define overall efficiency of the two-stage process as:
PD Ps d=1 ηdzdj0 r=1 uryrjo w1 ∗ Pm + w2 ∗ PD (3.5) i=1 vixij0 d=1 ηdzdjo
where w1, w2 are user-specified weights such that w1 + w2 = 1. These weights are not optimization variables, but rather are functions of the optimization vari- ables. We thus nominate deriving the overall efficiency of the process by solving the following problem:
PD Ps h d=1 ηdzdj0 q=1 uqyqjo i max w1 ∗ Pm + w2 ∗ PD i=1 vixij0 d=1 ηdzdjo
s.t. PD d=1 ηdzdj Pm 6 1 (3.6) i=1 vixij Ps q=1 uqyqj PD 6 1 d=1 ηdzdj
vi, uq, ηd ≥ 0, j = 1, ...., n
It is ascertained that model (6) cannot be turned into a linear program using
the usual Charnes and Cooper (1962) transformation. Note that w1 and w2 are supposed to represent the relative importance or contribution of the performances of stages 1 and 2, respectively, to the overall performance of the DMU. One ar- gument is that the ’size’ of a stage reflects its importance, (as measured by its weight). One reasonable representation of size is the portion of total resources
Pm PD devoted to each stage. Letting i=1 vixij0 + d=1 ηdzdj0 represent the total size Pm of (amount of resources consumed by) the two-stage process, and i=1 vixij0 and PD d=1 ηdzdj0 , the sizes of the stages 1 and 2 respectively, we define
Pm i=1 vixij0 w1 = Pm PD i=1 vixij0 + d=1 ηdzdj0
12 3.1 Additive efficiency decomposition approach in the two-stage process
and PD d=1 ηdzdj0 w2 = Pm PD (3.7) i=1 vixij0 + d=1 ηdzdj0 Then, the objective function of model (6) becomes:
PD Ps d=1 ηdzdj0 + q=1 uqyrjo Pm PD (3.8) i=1 vixij0 + d=1 ηdzdj0
Under the constant returns to scale case, model (6) becomes
PD Ps d=1 ηdzdj0 + q=1 uqyqjo max Pm PD i=1 vixij0 + d=1 ηdzdj0 s.t. PD d=1 ηdzdj Pm 6 1 (3.9) i=1 vixij Ps q=1 uqyqj PD 6 1 d=1 ηdzdj
vi, uq, ηd ≥ 0, j = 1, 2, ...., n
Using the Charnes-Cooper transformation, model (8) is equivalent to
s D X X max µqyrjo + πdzdjo q=1 d=1
s.t. D m X X πdzdj − ωixij ≤ 0 d=1 i=1
s D X X µqyqj − πdzdj ≤ 0 (3.10) q=1 d=1
m D X X ωixijo + πdzdjo = 1 i=1 d=1
ωi, µq, πd ≥ 0, j = 1, ...., n
It is substantial to remark that in dealing with multiplicative processes (two-
13 3.1 Additive efficiency decomposition approach in the two-stage process
stage here), the process can be viewed as a box. The initial inputs xij enter the
box and the final outputs yqj drop the box. The measurement inside the box are all an intermediate type. Our approach is to take the weighted arithmetic mean of the efficiencies of the components. This is comparable to aggregating the outputs of all the components and dividing this by the aggregate of the inputs of those components. Once we obtain an optimal solution to (10), we can calculate efficiency scores for the two individual stages. Nevertheless, model (10) have alternative optimal solutions. As a result, the decomposition of the overall efficiency defined in (5) may not be distinct. We find a set of multipliers which produces the largest first (or second) stage efficiency score while maintaining the overall efficiency score. We therefore recommend the following procedure. Given the overall efficiency
obtained from (10) (denoted as θo), we calculate either the first stage’s efficiency
1∗ 2∗ (θj ) or the second stage efficiency (θj ) first, and then derive from that the effi- ciency of the other stage. In case the first stage is to give averting priority, the following model deter-
1∗ mines its efficiency (θo ), while maintaining the overall efficiency score at (θo) estimated from model (10)
PD 1∗ d=1 ηdzdj0 θo = max Pm i=1 vixij0
s.t. PD d=1 ηdzdj Pm ≤ 1 i=1 vixij Ps q=1 uqyqj PD ≤ 1 (3.11) d=1 ηdzdj
PD Ps d=1 ηdzdj0 + q=1 uqyrjo Pm PD = θo i=1 vixij0 + d=1 ηdzdj0
vi, uq, ηd ≥ 0, j = 1, ...., n
14 3.1 Additive efficiency decomposition approach in the two-stage process
or equivalently, D 1∗ X θo = max πdzdjo d=1 s.t. D m X X πdzdj − ωixij ≤ 0 d=1 i=1
s D X X µqyrj − πdzdj ≤ 0 (3.12) q=1 d=1
D s X X (1 − θo) πdzdjo + µryrjo = θo d=1 r=1
m X ωixijo = 1 i=1
ωi, µq, πd ≥ 0, j = 1, ...., n
The efficiency for the second stage is then calculated as
∗ 1∗ 2 θo − w1 ∗ θo θo = ∗ w2
∗ ∗ where w1 and w2 represent optimal weights obtained from model (10) by way of (7). Note that we here use (*) in to indicate that the efficiency of the first stage is given the averting priority and is optimized first. In this case, the resulting second
2 stage efficiency score is denoted as θo.
3.1.2 Two-stage DEA Model: Variable returns to scale
We can establish the efficiency scores for the two stages by the following VRS output-oriented model (Banker et al. 1984):
PD ηAz + uA maxE1 = d=1 d djo jo Pm i=1 vixijo s.t. PD A A d=1 ηd zdj + u Pm ≤ 1, j = 1, 2...., n i=1 vixij
15 3.1 Additive efficiency decomposition approach in the two-stage process
A A vi, ηd ≥ 0, , u : free of sign and PDs u y + uB maxE2 = q=1 q qjo jo PD B d=1 ηd zdjo s.t. PDs u y + uB q=1 q qj ≤ 1, j = 1, 2...., n PD B d=1 ηd zdj
B B uq, ηd ≥ 0, u : free in sign
Using our approach, we have the VRS overall efficiency as using the weights defined under the CRS assumption
PD A PDs B d=1 ηdzdjo + u + q=1 uqyqjo + u max Pm PD i=1 vixijo + d=1 ηdzdjo s.t. PD A d=1 ηdzdj + u Pm ≤ 1 (3.13) i=1 vixij
Ps B q=1 uqyqj + u PD ≤ 1 d=1 ηdzdj
uq, vi, ηd ≥ 0
uA, uB : free in sign
Note that this is an input-oriented model. If we use output-oriented VRS mod- PD d=1 ηdzdjo els, the weights will be defined as w1 = Ps PD and q=1 uqyqjo + d=1 ηdzdjo Ps q=1 uqyqjo w2 = Ps PD q=1 uryrjo + d=1 ηdzdjo
Model (13) is equivalent to the following linear programming program:
s D X 1 X 2 max µqyqjo + u + πdzdjo + u q=1 d=1
16 3.1 Additive efficiency decomposition approach in the two-stage process s.t. D m X X 1 πdzdj − ωixij + u ≤ 0 d=1 i=1
s D X X 2 µqyqj − πdzdj + u ≤ 0 (3.14) q=1 d=1
m D X X ωixijo + πdzdjo = 1 i=1 d=1
µr, ωi, πd ≥ 0, j = 1, 2, ..., n
u1, u2 : free in sign
Once we obtain the overall efficiency, a model can be developed to determine the efficiency of each stage. Specifically, assume averting priority for stage 1, the
1 following model determines that stage’s efficiency (Ejo ), while maintaining the overall efficiency score at Eo calculated from model (14),
D 1 X 1 Ejo = max πdzdjo + u d=1 s.t. D m X 1 X πdzdj + u − ωixij ≤ 0 d=1 i=1
s D X 2 X µqyqj + u − πdzdj ≤ 0 (3.15) q=1 d=1
D s X X 1 2 (1 − Eo) πdzdjo + µqyqjo + u + u = Eo d=1 q=1
m X ωixijo = 1 i=1
µq, ωi, πd ≥ 0, j = 1, 2, ..., n
u1, u2 : free in sign
17 3.2 Technology heterogeneity in NBA teams
3.2 Technology heterogeneity in NBA teams
We relax the technological isolation assumption (Tsekouras et al.2016; 2017), to compare the performance of NBA teams operating under heterogeneous technolo- gies i.e.the East and West conference frontier (Tsekouras et al., 2016) at the Amer- ican technology level. The introduction of metafrontier analysis can be used in order to explain differences in production opportunities that can be attributed to available resource endowments, different ownership types (Casu et al. 2013) eco- nomic infrastructure, and other characteristics of the physical, social and economic environment in which production takes place (O’Donnell et al. 2008; Kontolaimou et al. 2012). Moreover, it accounts for structure of national markets, national regulations and policies, cultural profiles and legal and institutional framework (Tsekouras et al., 2016) and different rate of access and acceptance of General Purpose Technologies-GPT (Kounetas et al. 2009). Following closely O’Donnell et al. (2008) extended the Battese et al. (2004) framework using conventional Shep- ard distance functions to estimate technical efficiency with respect to the same metatechnology and several individual technology sets. Each productive efficiency score obtained from the estimation with respect to the common technology can be used to define the so-called metatechnology ratio which is considered a measure of proximity of the k-th group individual frontier to its metafrontier or in other words how close a team that belong to the East or West conference frontier is to the American metatechnology (metafrontier). Thus, we can define the distance function with respect to the East and West conference and then to metafrontier MF, in order to calculate the technology gap ratio (Battese et al., 2004) or the reciprocal relationship of metatechnology ratio (O’Donnell et al., 2008). The esti- mation of the technology gap is defined from the following:
MTE(x,y) MTR(x,y) = (3.16) TE(x,y)
18 Chapter 4
Data
This study adopts the additive efficiency decomposition (Chen et al. 2009) of a two-stage DEA model to evaluate NBA team’s efficiency. The specific methodol- ogy has been implemented in the NBA championship from 2001-2002 till 2018-2019 season. National Basketball Association is the major basketball league in the USA and the most important basketball competition all around the world. There are 30 teams in the NBA (29 teams in the USA and one which is in Canada), grouped into two conferences (East and West). NBA consists of two phases: regular season and playoffs. The top eight teams from each conference proceed to the conference playoffs and the two winners from each conference (East and West) play for the title in the last playoff. Regarding regular season, every team play 82 games and it is mandatory to achieve a good place in the ranking to gain access to the post- season. The top eight teams in each Conference reach the post-season, with the No. 1 seed facing No. 8 in the first round, No. 2 vs. No. 7 etc. The winners of each Conference meet in the best-of-seven NBA Finals. We conceive of a NBA team as a two-stage acquisition and production oper- ation. In the first stage we use the salary cap as an input due to the limit for total amount of money that NBA teams have the ability to pay for their players instead of team payroll (Moreno and Lozano 2012; Young 2014).The main reason is that our research focuses on the efficiency of the teams, we preferred the salary
19 cap since it shows us the financial ability that teams have to buy players to reach the desired result.Because our research focuses on the efficiency of the teams, we preferred the salary cap since it shows us the financial ability that teams have to buy players to reach the desired result. In the second stage total wins (Win) (Dep- ken, 2000; Moreno and Lozano, 2014; Yang et al. 2014) of the teams in regular period and the number of spectators (Annual Attendance) (Moreno and Lozano, 2014; Yang et al. 2014) in each game are used as outputs. We know that the purpose of each team is to achieve the highest percentage of wins that can allow teams proceed the next phase, and the increased performance of teams in games is related to the increase of victories and spectators who come to the stadium, therefore there is more revenue due to the tickets being sold. Regarding the measurement of intermediate factor (Team Performance), we built an indicator which measures the performance of NBA teams based on Yang et al. study (2014). The intermediate factor has been calculated from the different statistical data of the teams(offensive records, defensive records, and turnovers). Thus, Team Performance (TP) can be measured using the following formula (as follows):
TP = X(Rebounds, Assists, Blocks, Steals, P oints)
− (F ieldGoalsAttempt − F ieldGoalsMade) (4.1)
− (F reeT hrowsAttempt − F reeT hrowsMade) − T urnovers
Our initial data consisted of the statistics of 30 teams from the 2001-2002 season to 2018-2019 as well the data concerning salary cap and the number of spectators for the same period. A common problem that had to be solved, is that NBA teams often change their name due to the franchise. In particular, for the Oklahoma City Thunder (Seattle Supersonics 1967-2008), Brooklyn Nets (New Jersey Nets 1977-2012) and New Orlean Pelicans (2002-2013) for which it was preferred to use their current name for the ease to create the final set of data. Hence, the final dataset used in this study combine all the above character-
20 4.1 Descriptive Statistics istics from the 2001-2002 season to the 2018-2019, yielding an unbalanced panel of 536 observations. Information on team performance, the number of wins in Regular Season, the salary cap and Annual Attendance are collected from the of- ficial NBA website (NBA.com) and BasketballReference.com web site, respectivly.
4.1 Descriptive Statistics
At this point we will take a look at the descriptive statistics of our variables and their properties, so we will be able to have a better analysis.
Table 1. Summary statistics of empirical data
Variables Mean Std. Dev. Correlation Matrix Inputs Team Salary Cap 73,789 21,478 1.000 Intermediate Factor Team Performance 111.398 8.686 0.564 1.000 Outputs Wins 40.544 12.349 0.165 0.588 1.000 Annual Attendance 17,475.85 2,008.871 0.262 0.307 0.457 1.000
Table 1 demonstrates the descriptive statistics and correlation matrix of the input, intermediate, and output variables. Positive correlations exist among in- puts and outputs and all coefficients are significant at the 5 percent statistical level. These variables are appropriate for examining the two-stage framework of crew efficiency in this study. Table 2 shows an increase trend through years, in average values, between the performance of teams, the number of wins and the spectators, which shows us that the choice of variables is right for our research. There is also a difference between the conferences.
21 4.1 Descriptive Statistics
Table 2. Number of avg. wins, attendance and team performance by Conference
East West Season Wins Attendance TP Wins Attendance TP 2001-2002 39.2 17,218.86 104.979 42.57 17,134.79 109.771 2002-2003 37.7 16,962.86 103.185 44.06 16,808.27 108.518 2003-2004 37 17,120.14 100.901 44.73 16,983.27 107.084 2004-2005 38.9 17,330.73 105.743 43.06 17,296.73 109.193 2005-2006 39.2 17,720.27 105.739 42.8 17,393.8 106.628 2006-2007 38.84 17,887.47 105.483 43.13 17,626.33 110.819 2007-2008 38.8 17,717.8 108.444 43.2 17,070.93 113.971 2008-2009 41.4 17,563.07 109.906 40.6 17,430.4 111.682 2009-2010 39.6 17,067.07 109.036 42.4 17,231.27 113.649 2010-2011 38.6 17,226.4 107.886 43.4 17,411 113.396 2011-2012 31.68 16,905.73 104.083 34.4 17,640.53 110.110 2012-2013 38.46 17,148.53 107.333 43.46 17,547.87 113.527 2013-2014 37.06 17,015.87 108.458 44.93 17,798.73 116.482 2014-2015 38.46 17,760.93 108.974 43.53 17,856.87 114.552 2015-2016 40.53 17,874.4 113.922 41.46 17,823.67 116.319 2016-2017 39.6 17,956.67 117.443 42.4 17,811.53 119.737 2017-2018 40.2 18,098.4 119.485 41.8 17,877.87 120.224 2018-2019 39.28 17,978.73 124.167 42.8 17,735.13 127.721
Figure 2: Relationship between Team Salary Cap and Team Performance
In Figure 2 we observe the relationship between salary cap (input) and Team Performance (intermediate) per conference and for each team, respectively. What we observe in this case is the positive relationship that appears between the 2 variables as well as a sharp increase in salary cap after the 2010-2011 season.
22 Chapter 5
Empirical Results
In this section the results of our research will be presented. The first part will present the overall efficiency, salary cap efficiency and on-court efficiency of the teams for selected seasons. The seasons are: 2001-2002, 2006-2007, 2011-2012, 2016-17, 2018-2019 and selected to show the effect of the continuous increase of the salary cap. Following are the efficiencies by conference for the same periods. Finally, the results of the technology gaps for the same zones are presented. The aggregate results for the entire range of our data set from the 2001-2002 to the 2018-2019 season are presented in Appendix.
5.1 Overall efficiency scores
Considering Table 3 and 4 the top ranking teams in terms of overall efficiency varies season by season, because of the high competition that exists between NBA teams. Los Angeles Clippers, Chicago Bulls, Indiana Pacers, Utah Jazz and Toronto Raptors represent the highest efficiency during the 2001-2002, 2006-2007, 2011- 2012, 2016-2017 and 2018-2019 seasons, respectively. The team that shows the lowest overall efficiency changed every season, for the same reason mentioned above. During the same season, that mentioned before, the least efficient teams were the New York Knicks, Portland Trailblazers, Phoenix Suns, Detroit Pistons
23 5.1 Overall efficiency scores and Atlanta Hawks.
Table 3. Overall team performance scores
2001-2002 2006-2007 Overall Salary Cap On-court Overall Salary Cap On-court Team Conference Wins Wins efficiency efficiceny efficiency efficiency efficiceny efficiency Atlanta Hawks East 0.622 0.622 0.622 33 0.804 0.804 0.804 30 Boston Celtics East 0.778* 0.711 0.868 49 0.717 0.646 0.717 24 Brooklyn Nets East 0.604 0.473 0.721 52 0.716* 0.669 0.736 41 Charlotte Hornets East - - - - 0.870 0.870 0.870 33 Chicago Bulls East 0.827 0.724 0.827 21 0.897* 0.814 0.897 49 Cleveland Cavaliers East 0.717 0.717 0.717 29 0.792* 0.674 0.843 50 Dallas Mavericks West 0.753* 0.655 0.875 57 0.677* 0.512 0.731 67 Denver Nuggets West 0.653 0.589 0.653 27 0.732* 0.718 0.739 45 Detroit Pistons East 0.839* 0.801 0.895 50 0.856* 0.748 0.856 53 Golden State Warriors West 0.695 0.695 0.695 21 0.743* 0.723 0.743 42 Houston Rockets West 0.619 0.619 0.619 28 0.742* 0.680 0.769 52 Indiana Pacers East 0.695* 0.656 0.695 42 0.690 0.656 0.690 35 Los Angeles Clippers West 0.921 0.921 0.921 39 0.782 0.735 0.782 40 Los Angeles Lakers West 0.788** 0.682 0.924 58 0.681* 0.592 0.681 42 Memphis Grizzlies West 0.658 0.618 0.658 23 0.690 0.690 0.690 22 Miami Heat East 0.667 0.581 0.667 36 0.765* 0.653 0.765 44 Milwaukee Bucks East 0.699 0.627 0.699 41 0.705 0.664 0.705 28 Minnesota Timberwolves West 0.729* 0.672 0.800 50 0.682 0.637 0.682 32 New Orleans Pelicans West - - - - 0.809 0.763 0.809 39 New York Knicks East 0.534 0.367 0.534 30 0.496 0.348 0.496 33 Oklahoma City Thunder West 0.773 0.773 0.773 45 0.749 0.749 0.749 31 Orlando Magic East 0.760* 0.760 0.760 44 0.733* 0.660 0.733 40 Philadelphia 76ers East 0.718* 0.564 0.718 43 0.643 0.598 0.643 35 Phoenix Suns West 0.660 0.602 0.660 36 0.790* 0.774 0.810 61 Portland Trailblazers West 0.553* 0.422 0.553 49 0.632 0.533 0.632 32 Sacramento Kings West 0.805* 0.704 0.941 61 0.723 0.664 0.723 33 San Antonio Spurs West 0.865* 0.761 0.865 58 0.775** 0.691 0.812 58 Toronto Raptors East 0.749* 0.622 0.749 42 0.856* 0.856 0.856 47 Utah Jazz West 0.738* 0.675 0.738 44 0.795 0.740* 0.821 51 Washington Wizards East 0.747 0.599 0.747 37 0.758* 0.713 0.758 41
Notes: *Playof teams, **League Champion
What is perceived in the first place is the gradual increase of overall efficiency over the season due to the increase in salary cap. Important reference should be made to the New York Knicks, who have a tremendous increase in Overall efficiency of 53.4% reached close to 80%. The San Antonio Spurs, Los Angeles Lakers, Toronto Raptors, Washington Wizards are seen to have a steady course in the evolution of overall efficiency to near 75%. With the Toronto Raptors reaching the 2018-2019 season, their highest percentage is 92.1%, which is also the highest for that season, which has led them to win the championship. Milwaukee Bucks, Philadelphia 76ers and Golden State Warriors are the teams with the greatest progress in overall efficiency, from 69% in the 2001-2002 season,
24 5.1 Overall efficiency scores Wins On-court efficiency efficiceny Salary Cap Overall efficiency Wins On-court efficiency efficiceny Salary Cap Overall efficiency Wins Overall team performance scores On-court efficiency Table 4. efficiceny Salary Cap 2011-2012 2016-2017 2018-2019 Overall efficiency TeamAtlanta HawksBoston CelticsBrooklyn NetsCharlotte HornetsChicago BullsCleveland Cavaliers EastDallas Conference Mavericks EastDenver Nuggets East EastDetroit 0.750* PistonsGolden East State 0.728* WarriorsHouston East Rockets 0.774 0.692 0.714 WestIndiana Pacers 0.757 0.622Los West Angeles West Clippers 0.866* 0.728Los 0.840 0.704 0.777* Angeles Lakers EastMemphis Grizzlies 0.696 0.728 0.844* 0.854 WestMiami 0.763 40 Heat 0.774 0.658 0.714 WestMilwaukee Bucks 0.684 39 East 0.757 0.716*Minnesota 0.844 Timberwolves 0.832 West 0.812 0.866 7 22New 0.819* 0.777 0.830* Orleans West Pelicans 21 0.627New West York 0.932* 0.649 Knicks 0.844 50 0.696* 0.790 0.854 0.706Oklahoma 0.812 36 City 0.750 Thunder 0.755 0.658* 0.774* EastOrlando Magic 0.803* 0.684 West 38 0.858 0.932 East 23 0.776Philadelphia 0.595 0.687 76ers 0.790 0.644 West 0.812Phoenix 0.506 0.819 0.907 0.700 Suns 25 0.853** 0.778 0.845 0.671 43Portland 0.740 East 0.781** 0.858 0.932 Trailblazers 34 0.696 0.523 0.916* 0.790Sacramento 0.726 40 53 Kings 0.654 0.697 0.774 0.892 0.630San 0.778 0.845 42 0.676 Antonio 0.817 0.795* Spurs 0.765* East 0.717 41 0.858 East 0.701* 0.729* 20Toronto 36 0.916 Raptors 0.687 West 51 41Utah 0.754* 0.570 0.977 Jazz 41 0.567 0.778 0.778 0.845 0.663* 26 0.736 0.942 0.641Washington 0.790* 0.709 West Wizards 0.740 0.684* 0.576 0.611 33 0.667* West 0.750 0.916 0.757 67 0.745 0.719 West 0.678 31 40 0.760 46 0.645 0.576 21 0.686 0.855 0.789 0.769 0.765 0.537 0.622 0.673 47 0.798 0.778 0.559 0.846* 0.855 East 0.601 0.617 0.813* East 37 0.712 0.735 0.840* 0.594 0.767 29 0.704 0.760 55 36 0.811* 0.696 0.778 51 49 0.653 0.790 0.684 0.745 0.641 0.789 0.746* 0.749 0.855 0.762 0.856 0.712 42 0.757 0.667* 0.806* 0.756 0.851 West 0.605 0.757 0.724 0.791* 42 0.666 26 0.747 0.760 35 37 39 43 0.827 19 0.778* 0.673 0.640 0.877 28 0.855 0.856 0.752 0.980 22 0.685 0.883* 0.986 0.851 0.794 31 0.775 0.848 0.722 0.608 0.672 0.717 0.835 0.724 33 33 0.690* 57 0.698 22 0.792 42 54 50 0.856 0.749 41 0.883 0.997 34 0.851 0.708 47 0.848 0.825 0.724 0.563 0.829 0.660 0.729 0.571 0.889* 41 0.769* 0.815 23 0.806 53 0.840* 0.760 20 0.738 48 0.883 31 0.820 0.848 0.672 0.829 0.753 0.812 48 0.752* 0.657 0.725 0.625 0.723* 0.675 36 0.767 0.788 0.760 37 0.754 28 29 33 41 0.829 0.621 1.032 0.737 0.891 0.642 0.867 0.890* 36 0.844 0.816* 0.878 0.666 0.760 0.884* 24 60 32 61 0.794 0.766* 39 0.793 49 0.818 0.753 33 0.788 0.805 0.730 0.814 0.869* 51 49 0.907 17 0.930 0.849 0.921** 0.927 0.717 0.826 0.793 0.912 51 51 42 0.854 53 0.734 0.893* 0.893 0.825 0.912 0.960 19 48 39 0.863 0.912 58 0.910 32 50 Notes: *Playof teams, **League Champion
25 5.1 Overall efficiency scores the Golden State Warriors reached 85.4% in the 2016-2017 season conquering and the championship. The Milwaukee Bucks and Philadelphia 76ers in the 2018-2019 season reached 89%. Noteworthy is the reverse trend followed by the Los Angeles Clippers who, from 92.1%, the highest in the 2001-2002 season, dropped to 70% in the 2016-2017 season. Why would the western conference be on average more efficient than the east- ern conference? The possible reasons are as follows. It is well known that the western conference has won an astounding 15 of the last 20 NBA Finals since the end of the winning dynasty established by the Chicago bulls in the eastern confer- ence from the 1995–1996 to 1997–1998 seasons. We can see from Table 2 that the average win percentage of teams in the Western Conference is higher than that of teams in the Eastern Conference. These results are justified by the following graphs.
Figure 3: Overall efficiency and stage efficiency versus Wins
Figure 3 shows the overall efficiency and stage efficiency score versus its num- ber of wins. A substantial number of wins is usually enough to achieve a high efficiency score. We notice that the efficiency of the teams in the west confer- ence is higher than in the east showing an average of about 80%. While in both
26 5.1 Overall efficiency scores conferences the on-court efficiency (2nd stage) of the teams is observed to affect the result. In addition, the results of the western conference teams are observed to be concentrated right on the graph suggesting the greater efficiency of the teams.
Figure 4: Boxplot of Overall and Stage efficiency by Conference
Figure 5: Kernel Density of overall efficiency and stage efficiency through time
The box-plot of the overall efficiency scores are shown in Fig. 4, grouping the teams according to their conference. Note that the overall efficiency is almost the same in both conferences. Second, given the longer “whiskers” for overall
27 5.1 Overall efficiency scores efficiency in eastern conference, we can interpret that they vary in the efficiency scores. Third the skew of the data. If you look at the overall efficiency, the box and whiskers are even on either side of the median/mean. We observe that there are more outliers in eastern conference. As far as the stages are concerned, the range of the wage efficiency scores (1st stage) is bigger in eastern conference, given the longer “whiskers” for wage efficiency in eastern conference, we can interpret that they vary in the efficiency scores. On-court efficiency (2nd stage) vary in eastern conference as it shown from the bigger “whiskers”. Although, the box in western conference indicate that the efficiency scores are higher. In Figure 5 we notice how the data from the overall efficiency and stage effi- ciency of the teams is distributed per season. What is being vague from the outset is the continuous increase in efficiency and how the two stages impact on this in- crease. It is also understood that in the first season of our data the distribution has a very wide range and the height is low, suggesting that the efficiency at the beginning is low and increases as time goes by leading to a concentration of our data on the left side.
5.1.1 Salary cap and on-court efficiency
NBA teams possesses the two-stage feature, understanding each team’s efficiency score in these two stages are crucial. This section discusses each stage’s efficiency score of each stage. salary cap is major for each NBA team for hiring better players and a higher salary cap generally demonstrates a higher on-court per- formance. Conversely, whether on-court performance efficiently transforms into winning games and earning more gate receipts sometimes is affected by uncontrol- lable factors such as spectators, the luck factor, and others. Returning to Tables 3 and 4 again, we see for each team the salary cap ef- ficiency (1st stage) and on-court efficiency (2nd stage). The results for the first stage salary cap efficiency show that Los Angeles Clippers (92.1%), Atlanta Hawks
28 5.1 Overall efficiency scores
(80.4%), Indiana Pacers (93.2%), Philadelphia 76ers (84.8) and Washington Wiz- ards (91.2%) achieve high salary cap efficiency during the sample period. Some teams showed a specific trend toward wage efficiency. For example, we find that Washington Wizards and Toronto Raptors increased their salary cap efficiency from 59.9% and 62.2% during the 2001-2002 season to 91.2% and 85.4% during the 2018-2019 season, respectively. Noteworthy is the reverse trend followed by the Los Angeles Clippers who, from 92.1%, the highest in the 2001-2002 season, dropped to 57.6% in the 2016-2017 season. Looking in the results of the second stage on-court efficiency some interesting findings are coming up. First, is observed wide variation of on-court efficiency suggests that, even though most players perform well on-court, it does not guar- antee the winning of more games. There is a wide difference between teams in their ability to organize and to cooperate effectively. Moreover, the impacts of some unexpected factors could not be eliminated, which increase the uncertainty of games and attracts more spectators. In comparison with salary cap efficiency, we observe more teams achieving a higher efficiency score. Sacramento Kings (94.1%), Chicago Bulls (89.7%), San Antonio Spurs (98.6%), Golden State War- riors (97.7%) achieve high on-court efficiency during the sample period. Milwau- kee Bucks need special mention for excellent performance in on-court efficiency (132%) during 2018-2019 season. New York Knicks witness a low on-court ef- ficiency (53.4%) during 2001-2002 season and (49.6%) during season 2006-2007. Also, Phoenix Suns (67.3%), Orlando Magic (67.2%) and Atlanta Hawks (64.5%) shows low on-court efficiency during 2011-2012, 2016-2017 and 208-2019 seasons, respectively. Boston Celtics, Los Angeles Lakers, San Antonio Spurs, Oklahoma City Thunder, Toronto Raptors and Houston Rockets demonstrates a steady a steady course in on-court efficiency during sample data. By contrast, Memphis Grizzles normally witness a low on-court efficiency score during the sample period, reaching only 65.8, 69, and 66%, on average.
29 5.2 Efficiency scores by Conference
5.2 Efficiency scores by Conference
In this section we have divided the teams based on the conference they belong, as this will create two sub-leagues from which will emerge in the end the two finalists who will claim the ring of the NBA champion. We expect the efficiency of the teams to be different from the ones we analyzed earlier.
Table 5. Conference team performance scores
2001-2002 2006-2007 Conference Salary Cap On-court Conference Salary Cap On-court Team Conference Wins Wins efficiency efficiceny efficiency efficiency efficiceny efficiency Atlanta Hawks East 0.745 0.745 0.745 33 0.804 0.804 0.804 30 Boston Celtics East 0.934* 0.888 1.021 49 0.717 0.646 0.717 24 Brooklyn Nets East 0.740 0.590 0.929 52 0.718 0.669 0.787 41 Charlotte Hornets East - - - - 0.870 0.870 0.870 33 Chicago Bulls East 0.937 0.904 0.937 21 0.897* 0.814 0.897 49 Cleveland Cavaliers East 0.811 0.811 0.811 29 0.798* 0.674 0.970 50 Detroit Pistons East 1.000* 1.000 1.000 50 0.856 0.748 0.856 53 Indiana Pacers East 0.828* 0.818 0.839 42 0.690 0.656 0.690 35 Miami Heat East 0.779 0.724 0.829 36 0.765* 0.653 0.765 44 Milwaukee Bucks East 0.814 0.782 0.845 41 0.705 0.664 0.705 28 New York Knicks East 0.626 0.458 0.626 30 0.496 0.348 0.496 33 Orlando Magic East 0.904* 0.904 0.904 44 0.733* 0.660 0.733 40 Philadelphia 76ers East 0.826* 0.703 0.830 43 0.643 0.598 0.643 35 Toronto Raptors East 0.860* 0.776 0.943 42 0.876* 0.870 0.885 47 Washington Wizards East 0.856 0.748 0.856 37 0.758* 0.713 0.758 41 Dallas Mavericks West 0.753* 0.655 0.875 57 0.796* 0.661 0.796 67 Denver Nuggets West 0.653 0.589 0.653 27 0.874* 0.874 0.874 45 Golden State Warriors West 0.695 0.695 0.695 21 0.897* 0.897 0.897 42 Houston Rockets West 0.619 0.619 0.619 28 0.865* 0.865 0.865 52 Los Angeles Clippers West 0.921 0.921 0.921 39 0.946 0.946 0.946 40 Los Angeles Lakers West 0.788** 0.682 0.924 58 0.835* 0.765 0.835 42 Memphis Grizzlies West 0.658 0.618 0.658 23 0.832 0.832 0.832 22 Minnesota Timberwolves West 0.729* 0.672 0.800 50 0.829 0.823 0.829 32 New Orleans Pelicans West - - - - 0.977 0.977 0.977 39 Oklahoma City Thunder West 0.773 0.773 0.773 45 0.901 0.901 0.901 31 Phoenix Suns West 0.660 0.602 0.660 36 0.905* 0.905 0.905 61 Portland Trailblazers West 0.553* 0.422 0.553 49 0.779 0.688 0.779 32 Sacramento Kings West 0.805* 0.704 0.941 61 0.879 0.858 0.879 33 San Antonio Spurs West 0.865* 0.761 0.865 58 0.904** 0.893 0.904 58 Utah Jazz West 0.738* 0.675 0.738 44 0.950 0.950* 0.950 51
Notes: *Playof teams, **League Champion
Observing the results from tables 5 and 6, it is easy to understand that the range of efficiency has diminished throughout the sample. In the Eastern confer- ence the Detroit Pistons, during season 2001-2002, achieved the highest efficiency of 100% compared with other teams, suggesting that this team is the most ef- ficient in transforming salary into the intermediate output of players’ on-court
30 5.2 Efficiency scores by Conference performances, leading to the final outputs of winning games and generating rev- enue. Chicago Bulls (89.7%), Indiana Pacers (94.2%), Boston Celtics (93.1%) and Toronto Raptors (92.1%) represent the highest efficiency during the 2006-2007, 2011-2012, 2016-2017 and 2018-2019 seasons, respectively. During the same sea- son, that mentioned before, the least efficient teams were the New York Knicks (62.6%), Detroit Pistons (69.4%) and Atlanta Hawks (63%). Needs attention the course of the Detroit Pistons to the top of the efficient-section the 2001-2002 sea- son, came in last place the 2011-2012 season. As for the western conference, Los Angeles Clippers (92.1%), New Orleans Pelicans (97.7%), Oklahoma City Thunder (94.8%), Utah Jazz (86.7, 97.3%) repre- sent the highest efficiency during the 2001-2002, 2006-2007, 2011-2012, 2016-2017 and 2018-2019 seasons,respectively. During the same seasons, that mentioned be- fore, the least efficient teams were the Portland Trailblazers (55.3, 77.9%), Phoenix Suns (70.3%), Memphis Grizzlies (66.7, 79.6%). The San Antonio Spurs, Los An- geles Lakers, Los Angeles Clippers, Sacramento Kings, Oklahoma City Thunder and Utah Jazz are seen to have a steady course in the evolution of overall efficiency to near 85%. Important reference should be made to the Portland Trailblazers and Huston Rockets, are the teams with the greatest progress in conference efficiency, from 55.3% and 61.9% in the 2001-2002 season to 96.5% and 88.5% in the 2018- 2019 season, respectively. Contrary to what happens when everyone is racing with everyone we notice some differences. First, the difference between a team’s behavior in terms of their efficiency is the opposite of what it used to be, for example, the Los Angeles Clippers have a steady course in that case and their efficiency moves to 86%, in relation to the overall efficiency that was declining. It is also important that the range of results is smaller, due to the large increase in salary cap, which is shown in the following graphs. The only remaining stable are the highest results achieved in the Western conference and in this case.
31 5.2 Efficiency scores by Conference Wins On-court efficiency efficiceny Salary Cap Overall efficiency Wins On-court efficiency efficiceny Salary Cap Overall efficiency Wins Conference team performance scores On-court efficiency Table 6. efficiceny Salary Cap 2011-2012 2016-2017 2018-2019 Overall efficiency TeamAtlanta HawksBoston CelticsBrooklyn NetsCharlotte HornetsChicago BullsCleveland Cavaliers EastDetroit Conference Pistons EastIndiana Pacers East EastMiami 0.759* HeatMilwaukee East Bucks 0.738*New East York 0.784 Knicks 0.708 0.723Orlando Magic East 0.767 0.636Philadelphia 76ers 0.876* East 0.745Toronto 0.842 Raptors 0.719 EastWashington Wizards 0.711 0.738 0.694 East 0.780 East 40Dallas 0.942* 0.784 Mavericks 0.723Denver 39 Nuggets 0.787 East East 0.767 0.641 0.799* 0.791**Golden State 0.775* 0.876 0.942 East 7 Warriors 22 East 0.931*Houston Rockets 21 0.800* 0.787Los 0.694* 0.691 0.749 0.694 Angeles 50 Clippers 0.854 0.772 0.655 WestLos 0.942 0.861 West Angeles 0.872 0.734* Lakers 0.866Memphis 0.787 0.873* Grizzlies 25 West 0.549 0.787 0.949 0.881Minnesota 42 0.854 0.794* 0.744 Timberwolves 0.775 0.861 0.861 West 0.584 1.045 WestNew 0.866 Orleans 0.723 31 Pelicans 0.775 0.893* 46 43 0.800 0.830* 0.694Oklahoma West City 36 West Thunder 0.658 0.854 0.788 53Phoenix 0.857* 0.861 Suns 0.832 0.791* 0.805 West 0.857 0.807 0.866 0.630 35 0.658Portland 0.893 37 0.873 0.829 Trailblazers 0.792 West West 0.868 0.734* 0.729* 20 36Sacramento 0.823 Kings 20 51 0.750 0.770 23 0.799* 0.916 0.861San 0.737 0.857 41 0.699 Antonio 0.567 0.757 Spurs 0.893 0.663* 0.830 0.948* 0.709 0.702Utah 0.815* 0.745 0.611 0.595 0.859 36 Jazz West 0.750 0.835* 23 0.929 0.700 0.745 0.826 0.916 37 38 0.650 0.857 42 0.868 0.645 0.576 0.922 West 0.687 0.622 0.741 0.792 0.853** West 0.717 0.778 0.846 0.871 0.717 0.763 0.601 40 0.746* 42 West 0.845 0.778* 34 0.893 0.594 41 29 0.916 0.737 31 0.696 0.774 49 41 0.703 0.980 26 0.523 0.701* 0.745 0.944 0.864 0.889* 0.752 0.795* 0.904 0.617 0.762 0.640 41 0.806 0.861* 28 0.698 0.845 29 0.757 0.788 42 0.778 47 0.763 39 49 0.977 21 0.641 0.576 0.687 West 0.812 51 0.667* 19 0.864 0.890* 0.736 0.816* 0.763 0.792 0.756 22 0.675 0.815 0.811* 0.912** 0.845 0.666 67 0.706 0.686 0.763 33 0.921 0.908* 0.756 0.798 0.559 1.032 28 0.818 0.864 41 0.753 0.855 48 40 0.912 0.969 0.747 0.844 0.925* 0.862 0.788 0.666 0.778 33 51 0.693* 0.763 60 0.895 0.854 22 55 0.749 0.893* 0.930 50 0.849 39 0.912 0.914 0.831 17 0.867* 26 0.829 31 0.757 0.732 0.571 0.717 0.885 43 0.918 0.960 0.769* 51 0.825 42 32 47 0.870 0.819 0.933 0.837 34 0.829 0.862 0.796 36 58 0.794* 0.657 0.722 0.625 0.919* 0.934 57 0.830 0.820 0.867* 0.819 33 0.886 41 0.829 0.765 0.938 0.753 54 0.891 0.889 48 0.965* 0.766 0.830 0.898 24 0.819 53 32 61 0.812 0.937 0.933 37 0.805 36 0.900 0.889 0.948* 0.830 33 49 51 33 0.986 0.805 0.948 0.889 0.973 53 0.805 0.948 0.889 0.973* 19 48 39 0.973 50 Notes: *Playof teams, **League Champion
32 5.2 Efficiency scores by Conference
Figure 6: Conference efficiency and stage efficiency versus salary cap
Figure 6 shows the overall efficiency and stage efficiency score versus salary cap. In the eastern conference there are some outliers in the first stage, in addi- tion there are teams with a big amount of salary cap who achieve a low percentage of efficiency. While in the western conference many teams increase their efficiency by using a small amount of salary cap. In addition, the results of the western conference teams are observed to be concentrated right on the graph suggesting the greater efficiency of the teams.
Figure 7: Boxplot of Conference and Stage efficiency by Conference
33 5.2 Efficiency scores by Conference
Figure 8: Kernel Density of conference efficiency and stage efficiency through time
Figure 7 shows box-plot of conference efficiency, grouping the teams by their conference. Observing the longer “whiskers” for conference efficiency in eastern conference, we can interpret that they vary in the efficiency scores. On the other hand, in western conference the efficiency scores are higher and with less variation, because the median is higher than in the east. As far as the stages are concerned, the range of the wage efficiency scores (1st stage) is bigger in eastern conference, given the longer “whiskers” for wage efficiency in eastern conference, we can inter- pret that they vary in the efficiency scores. On-court efficiency (2nd stage) vary in eastern conference as it shown from the bigger “whiskers”. Although, the box in western conference indicate that the efficiency scores are higher. In Figure 8 we notice how the data from the conference efficiency and stage efficiency of the teams is distributed per season. What is being vague from the outset is the continuous increase in efficiency and how the two stages impact on this increase. It is also understood that in the first season of our data the distri- bution has a very wide range and the height is low, suggesting that the efficiency at the beginning is low and increases as time goes by leading to a concentration of our data on the left side.
34 5.2 Efficiency scores by Conference
5.2.1 Salary cap and on-court efficiency by conference
Looking back at Tables 5 and 6 again, we see for each team the salary cap ef- ficiency (1st stage) and on-court efficiency (2nd stage). The results for the first stage salary cap efficiency shows that in the eastern conference the Detroit Pis- tons, during season 2001-2002, achieved the highest efficiency of 100% compared with other teams. Charlotte Hornets (87%), Indiana Pacers (94.2%), Philadelphia 76ers (91.6%) and Washington Wizards (91.2%) represent the highest efficiency during the 2006-2007, 2011-2012, 2016-2017 and 2018-2019 seasons, respectively. The same season, that mentioned before, the least efficient teams were the New York Knicks (45.8, 34.8%), Orlando Magic (54.9%), Cleveland Cavaliers (58.4%) and Atlanta Hawks (56.7%). Needs attention the course of the Detroit Pistons to the top of the efficient section the 2001-2002 season, drop second in the 2011- 2012 season. We find that Washington Wizards and Toronto Raptors increased their salary cap efficiency from 74.8% and 77.6% during the 2001-2002 season to 91.2% and 85.4% during the 2018-2019 season, respectively. In the western con- ference, Los Angeles Clippers (92.1%), New Orleans Pelicans (97.7%), Oklahoma City Thunder (92.2%), Denver Nuggets (84.5%) and Utah Jazz (97.3%) represent the highest efficiency during the 2001-2002, 2006-2007, 2011-2012, 2016-2017 and 2018-2019 seasons, respectively. Looking in the results of second stage on-court efficiency some interesting find- ings are coming up. The impacts of some unexpected factors could not be elimi- nated, which increase the uncertainty of games and attracts more spectators. In comparison with salary cap efficiency, we observe more teams achieving a higher efficiency score. Detroit Pistons (100%), Boston Celtics (102%), San Antonio Spurs (96.9%), Golden State Warriors (93.3%) achieve high on-court efficiency during the sample period. Milwaukee Bucks need special mention for excellent performance in on-court efficiency (132%) during 2018-2019 season. New York Knicks witness a low on-court efficiency (49.6%) during season 2006-2007. Also, Phoenix Suns (66%), Orlando Magic (69.4%) and Atlanta Hawks (64.5%) shows
35 5.3 Technology Gap low on-court efficiency during 2011-2012,206-2017 and 208-2019 seasons, respec- tively. Boston Celtics, Los Angeles Lakers, San Antonio Spurs, Oklahoma City Thunder, Toronto Raptors and Houston Rockets demonstrates a steady course in on-court efficiency during sample data. By contrast, Memphis Grizzles shows fluctuation on-court efficiency score which starts in season 2001-2002 with 65.8% reaching a historic high for the team 89.3% in season 2011-2012 and then drops again in season 2016-2017 at 74.9%
5.3 Technology Gap
The introduction of metafrontier analysis can be used in order to explain dif- ferences in production opportunities that can be attributed to available resource endowments, different ownership types economic infrastructure, and other char- acteristics of the physical, social and economic environment in which production takes place. Each productive efficiency score obtained from the estimation with respect to the common technology can be used to define the so-called metatechnol- ogy ratio which is considered a measure of proximity of the k-th group individual frontier to its metafrontier or in other words how close a team that belong to the East or West conference frontier is to the American metatechnology (metafrontier).
The results presented in Table 7 provide valuable information for the perfor- mance of the teams regarding the metatechnology ratios under the condition that all have access to common technology, in our case all teams have access to salary cap. Of the 28 teams during season 2001-2002, 14 are efficient. The relatively high scores can be explained as follows. Technology Gap is defined as the ratio of the conference efficiency score to overall efficiency score. Since the frontier is con- structed assuming the conference efficiency, the data more closely than the frontier constructed using overall efficiency the ratio of these two distances leads to values very close or equal to one. Noteworthy is the fact that all teams belonging to the
36 5.3 Technology Gap
Table 7. Technology Gap
Season Team Conference 2001-2002 2006-2007 2011-2012 2016-2017 2018-2019 Atlanta Hawks East 0.836 1.000 0.987 0.896 1.000 Boston Celtics East 0.834 1.000 0.987 0.891 1.000 Brooklyn Nets East 0.816 0.997 0.987 0.925 1.000 Charlotte Hornets East - 1.000 0.987 0.914 1.000 Chicago Bulls East 0.882 1.000 0.988 0.920 1.000 Cleveland Cavaliers East 0.884 0.994 0.987 0.897 1.000 Dallas Mavericks West 1.000 0.851 0.979 1.000 0.915 Denver Nuggets West 1.000 0.838 0.945 1.000 0.911 Detroit Pistons East 0.839 1.000 0.987 0.905 1.000 Golden State Warriors West 1.000 0.828 0.992 1.000 0.915 Houston Rockets West 1.000 0.859 0.948 1.000 0.911 Indiana Pacers East 0.839 1.000 0.989 0.908 1.000 Los Angeles Clippers West 1.000 0.827 0.956 1.000 0.912 Los Angeles Lakers West 1.000 0.816 0.948 1.000 0.912 Memphis Grizzlies West 1.000 0.829 0.969 1.000 0.910 Miami Heat East 0.856 1.000 0.987 0.912 1.000 Milwaukee Bucks East 0.859 1.000 0.988 0.900 1.000 Minnesota Timberwolves West 1.000 0.822 0.989 0.997 0.914 New Orleans Pelicans West - 0.828 0.992 0.997 0.916 New York Knicks East 0.852 1.000 0.987 0.914 1.000 Oklahoma City Thunder West 1.000 0.831 0.966 1.000 0.914 Orlando Magic East 0.841 1.000 0.986 0.912 1.000 Philadelphia 76ers East 0.869 1.000 0.988 0.926 1.000 Phoenix Suns West 1.000 0.873 0.957 1.000 0.907 Portland Trailblazers West 1.000 0.811 0.992 0.997 0.916 Sacramento Kings West 1.000 0.822 0.989 0.997 0.916 San Antonio Spurs West 1.000 0.858 0.976 1.000 0.917 Toronto Raptors East 0.871 0.978 0.988 0.901 1.000 Utah Jazz West 1.000 0.837 0.973 1.000 0.918 Washington Wizards East 0.873 1.000 0.988 0.886 1.000 western conference are efficient, while those belonging to the eastern allocate their resources inefficiently and thus do not accommodate the effects of salary cap. During season 2006-2007, 12 out of a total of 30 teams are the most efficient with a significant difference these twelve teams are from the eastern conference. In season 2011-2012 the performance of all teams is close to the unit without anyone being able to utilize its resources effectively, but in averages their performance has increased compared to previous seasons. In the last two seasons 2016-2017 and 2018-2019 of our sample, we observe that the bandwidth of the team performances is relatively eliminated and approaching all the unit. In the 2016-2017 season there are 11 teams that have a performance equal to the unit and belong to the western conference, with the rest ranging between 0.886 and 0.997. In contrast, for the 2018-2019 season there are 15 teams with a unit performance and belonging to
37 5.3 Technology Gap the eastern conference, with the remaining ranging between 0.907 and 0.918. Overall, the performance in terms of efficiency of NBA teams seems to increase on average during 2006-2007, 2011-2012 and 2018-2019 compared to 2001-2002 sea- son. Furthermore, In each season there is a change of the conference that has the highest performing teams. A possible explanation for this increase may be at- tributed to rapid growth that has occurred in salary cap, as teams have managed to reach a unified market. Finally, this change in our regions indicates to which conference the champion belongs.
38 Chapter 6
Conclusions
Combining resources to produce results is the main financial objective for the managers of professional sports teams. Hence, understanding the overall team efficiency as well as the relative efficiency and importance of various stages’ oper- ation is a crucial and important issue from the perception of team management. As the production process of sports teams is essentially two stages, it is crucial to adopt an appropriate method to evaluate team efficiency and the two different stages, aiming to provide perceptive information for teams’ decision makers. This study estimates the efficiency of NBA teams using the additive efficiency decomposition approach of two-stage DEA developed by Chen et al. (2009). This method permits us to separate the overall team efficiency into the first-stage salary cap efficiency and the second-stage on-court efficiency. Based on the unbalanced panel dataset of NBA teams during the 2001–2002 to 2018–2019 seasons, the empirical results show that on average the overall team efficiency scores range between 67.5% and 88.5% through the sample period. Furthermore, the results suggest that teams belonging to the Western conference achieve higher overall ef- ficiency than those in the East. Utah Jazz, San Antonio Spurs, Chicago Bulls, Atlanta Hawks, Golden State Warriors and Toronto Raptors are among the top efficient teams, whereas New York Knicks, Dallas Mavericks, Orlando Magic, Min- nesota Timberwolves and New Orleans Pelicans rank among the lowest efficient
39 teams. Regarding, the conference efficiency scores the empirical results show that on average the overall team efficiency scores range between 71.2% and 91.03% through the sample period. Utah Jazz, Dallas Mavericks, Atlanta Hawks, Detroit Pistons, New Orleans Pelicans, Chicago Bulls, San Antonio Spurs are the top 8 efficient teams. Separating overall and conference efficiency into salary cap and on-court effi- ciency, empirical findings shows that wide variation of on-court efficiency suggests that, even though most players perform well on-court, it does not guarantee the winning of more games. There is a wide difference between teams in their ability to organize and to cooperate effectively. Moreover, the impacts of some unex- pected factors could not be eliminated, which increase the uncertainty of games and attracts more spectators. Bearing in mind all of the above, it is understood that the continuous increase in the salary cap has affected the performance of the teams to the best, and as shown the results, firstly there is an increase in efficiency scores over time as well as a decrease in the variation of efficiency which helps to develop the competitive- ness of the teams. Also, based on the analyses strained from the two-stage DEA, this study offers some management allegations for improving salary cap efficiency as well as on-court efficiency. Moreover, we also discover that big-market teams like the Golden State Warriors, Chicago Bulls, San Antonio Spurs, Boston Celtics and the Lakers shows a higher stage 2 efficiency rather than stage 1, reflecting that big-market teams are more efficient in the factor efficiency of gate receipts than small-market teams. Finally, we estimate the Technology Gap in order to see how close a team that belong to the East or West conference frontier is to the American metatechnology (metafrontier). Empirical findings show that the performance in terms of effi- ciency of NBA teams seems to increase on average through seasons. Furthermore, in each season there is a change of the conference that has the highest performing teams. A possible explanation for this increase may be attributed to rapid growth
40 that has occurred in salary cap, as teams have managed to reach a unified market. Finally, this change in our regions indicates to which conference the champion belongs.
41 Appendix A
Overall team performance scores
Table A.1. Overall team performance scores
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
2001 Atlanta Hawks East 0.622 0.622 0.622 33
Boston Celtics* East 0.778 0.711 0.868 49
Brooklyn Nets East 0.604 0.473 0.721 52
Chicago Bulls East 0.827 0.724 0.827 21
Cleveland Cavaliers East 0.717 0.717 0.717 29
Dallas Mavericks* West 0.753 0.655 0.875 57
Denver Nuggets West 0.653 0.589 0.653 27
Detroit Pistons* East 0.839 0.801 0.895 50
Golden State Warriors West 0.695 0.695 0.695 21
Houston Rockets West 0.619 0.619 0.619 28
Indiana Pacers* East 0.695 0.656 0.695 42
Los Angeles Clippers West 0.921 0.921 0.921 39
Los Angeles Lakers** West 0.788 0.682 0.924 58
Memphis Grizzlies West 0.658 0.618 0.658 23
Miami Heat East 0.667 0.581 0.667 36
Milwaukee Bucks East 0.699 0.627 0.699 41
Minnesota Timberwolves* West 0.729 0.672 0.800 50
42 Table A.1 continued.
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
New York Knicks East 0.534 0.367 0.534 30
Oklahoma City Thunder West 0.773 0.773 0.773 45
Orlando Magic* East 0.760 0.760 0.760 44
Philadelphia 76ers* East 0.718 0.564 0.718 43
Phoenix Suns West 0.660 0.602 0.660 36
Portland Trailblazers* West 0.553 0.422 0.553 49
Sacramento Kings* West 0.805 0.704 0.941 61
San Antonio Spurs* West 0.865 0.761 0.865 58
Toronto Raptors* East 0.749 0.622 0.749 42
Utah Jazz* West 0.738 0.675 0.738 44
Washington Wizards East 0.747 0.599 0.747 37
2002 Atlanta Hawks East 0.727 0.727 0.727 35
Boston Celtics* East 0.832 0.783 0.877 44
Brooklyn Nets East 0.783 0.753 0.810 49
Chicago Bulls East 0.957 0.957 0.957 30
Cleveland Cavaliers East 0.718 0.718 0.718 17
Dallas Mavericks* West 0.789 0.685 0.873 60
Denver Nuggets West 0.788 0.762 0.788 17
Detroit Pistons* East 0.942 0.890 0.942 50
Golden State Warriors West 0.838 0.838 0.838 38
Houston Rockets West 0.819 0.819 0.819 43
Indiana Pacers* East 0.845 0.845 0.845 48
Los Angeles Clippers West 0.916 0.916 0.916 27
Los Angeles Lakers** West 0.803 0.757 0.843 50
Memphis Grizzlies West 0.719 0.719 0.719 28
Miami Heat East 0.733 0.664 0.733 25
Milwaukee Bucks* East 0.779 0.779 0.779 42
Minnesota Timberwolves* West 0.809 0.809 0.809 51
43 Table A.1 continued.
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
New Orleans Pelicans* West 0.914 0.914 0.914 47
New York Knicks East 0.606 0.465 0.606 37
Oklahoma City Thunder West 0.793 0.793 0.793 40
Orlando Magic* East 0.822 0.822 0.822 42
Philadelphia 76ers* East 0.783 0.703 0.783 48
Phoenix Suns* West 0.806 0.799 0.811 44
Portland Trailblazers* West 0.576 0.427 0.650 50
Sacramento Kings* West 0.785 0.713 0.879 59
San Antonio Spurs** West 0.920 0.851 0.988 60
Toronto Raptors East 0.833 0.728 0.833 24
Utah Jazz* West 0.887 0.887 0.887 47
Washington Wizards East 0.946 0.909 0.946 37
2003 Atlanta Hawks East 0.597 0.560 0.597 28
Boston Celtics* East 0.670 0.611 0.670 36
Brooklyn Nets* East 0.667 0.584 0.729 47
Chicago Bulls East 0.765 0.626 0.765 23
Cleveland Cavaliers East 0.829 0.823 0.829 35
Dallas Mavericks* West 0.643 0.553 0.706 52
Denver Nuggets* West 0.887 0.887 0.887 43
Detroit Pistons** East 0.818 0.692 0.818 54
Golden State Warriors West 0.720 0.687 0.720 37
Houston Rockets* West 0.717 0.644 0.776 45
Indiana Pacers* East 0.783 0.643 0.897 61
Los Angeles Clippers West 0.855 0.855 0.855 28
Los Angeles Lakers* West 0.734 0.617 0.826 56
Memphis Grizzlies* West 0.734 0.692 0.772 50
Miami Heat* East 0.764 0.734 0.793 42
Milwaukee Bucks* East 0.741 0.738 0.741 41
44 Table A.1 continued.
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Minnesota Timberwolves* West 0.689 0.563 0.780 58
New Orleans Pelicans* West 0.734 0.722 0.746 41
New York Knicks* East 0.555 0.411 0.555 39
Oklahoma City Thunder West 0.714 0.714 0.714 37
Orlando Magic East 0.700 0.687 0.700 21
Philadelphia 76ers East 0.714 0.564 0.714 33
Phoenix Suns West 0.626 0.541 0.626 29
Portland Trailblazers West 0.549 0.442 0.549 41
Sacramento Kings* West 0.701 0.626 0.761 55
San Antonio Spurs* West 0.881 0.807 0.956 57
Toronto Raptors East 0.675 0.522 0.675 33
Utah Jazz West 0.979 0.979 0.979 42
Washington Wizards East 0.770 0.747 0.770 25
2004 Atlanta Hawks East 0.613 0.556 0.613 13
Boston Celtics* East 0.513 0.409 0.577 45
Brooklyn Nets* East 0.540 0.424 0.614 42
Charlotte Hornets East 0.844 0.844 0.844 18
Chicago Bulls* East 0.578 0.419 0.578 47
Cleveland Cavaliers East 0.634 0.521 0.634 42
Dallas Mavericks* West 0.446 0.295 0.513 58
Denver Nuggets* West 0.672 0.585 0.749 49
Detroit Pistons* East 0.630 0.459 0.630 54
Golden State Warriors West 0.547 0.458 0.547 34
Houston Rockets* West 0.557 0.417 0.644 51
Indiana Pacers* East 0.488 0.356 0.559 44
Los Angeles Clippers West 0.632 0.563 0.632 37
Los Angeles Lakers West 0.516 0.385 0.516 34
Memphis Grizzlies* West 0.492 0.366 0.561 45
45 Table A.1 continued.
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Miami Heat* East 0.616 0.453 0.726 59
Milwaukee Bucks East 0.516 0.430 0.516 30
Minnesota Timberwolves West 0.484 0.377 0.544 44
New Orleans Pelicans West 0.485 0.386 0.485 18
New York Knicks East 0.368 0.239 0.368 33
Oklahoma City Thunder West 0.606 0.460 0.707 52
Orlando Magic East 0.458 0.381 0.502 36
Philadelphia 76ers* East 0.469 0.351 0.469 43
Phoenix Suns* West 0.765 0.660 0.893 62
Portland Trailblazers West 0.400 0.289 0.400 27
Sacramento Kings* West 0.560 0.448 0.635 50
San Antonio Spurs** West 0.705 0.544 0.836 59
Toronto Raptors East 0.515 0.408 0.515 33
Utah Jazz West 0.671 0.547 0.671 26
Washington Wizards* East 0.609 0.499 0.692 45
2005 Atlanta Hawks East 0.759 0.759 0.759 26
Boston Celtics East 0.679 0.607 0.683 33
Brooklyn Nets* East 0.618 0.511 0.699 49
Charlotte Hornets East 0.898 0.898 0.898 26
Chicago Bulls* East 0.753 0.603 0.753 41
Cleveland Cavaliers* East 0.774 0.673 0.781 50
Dallas Mavericks* West 0.522 0.366 0.607 60
Denver Nuggets* West 0.697 0.651 0.701 44
Detroit Pistons* East 0.762 0.615 0.771 64
Golden State Warriors West 0.699 0.594 0.699 34
Houston Rockets West 0.567 0.461 0.572 34
Indiana Pacers* East 0.536 0.426 0.541 41
Los Angeles Clippers* West 0.742 0.706 0.745 47
46 Table A.1 continued.
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Los Angeles Lakers* West 0.614 0.489 0.621 45
Memphis Grizzlies* West 0.604 0.486 0.689 49
Miami Heat** East 0.714 0.598 0.721 52
Milwaukee Bucks* East 0.634 0.546 0.639 40
Minnesota Timberwolves West 0.627 0.538 0.632 33
New Orleans Pelicans West 0.842 0.780 0.847 38
New York Knicks East 0.394 0.250 0.394 23
Oklahoma City Thunder West 0.732 0.722 0.732 35
Orlando Magic East 0.538 0.436 0.543 36
Philadelphia 76ers East 0.519 0.415 0.524 38
Phoenix Suns* West 0.758 0.758 0.758 54
Portland Trailblazers West 0.605 0.497 0.605 21
Sacramento Kings* West 0.651 0.564 0.657 44
San Antonio Spurs* West 0.714 0.556 0.845 63
Toronto Raptors East 0.642 0.552 0.642 27
Utah Jazz West 0.698 0.577 0.705 41
Washington Wizards* East 0.706 0.639 0.711 42
2006 Atlanta Hawks East 0.804 0.804 0.804 30
Boston Celtics East 0.717 0.646 0.717 24
Brooklyn Nets* East 0.716 0.669 0.736 41
Charlotte Hornets East 0.870 0.870 0.870 33
Chicago Bulls* East 0.897 0.814 0.897 49
Cleveland Cavaliers* East 0.792 0.674 0.843 50
Dallas Mavericks* West 0.677 0.512 0.731 67
Denver Nuggets* West 0.732 0.718 0.739 45
Detroit Pistons* East 0.856 0.748 0.856 53
Golden State Warriors* West 0.743 0.723 0.743 42
Houston Rockets* West 0.742 0.680 0.769 52
47 Table A.1 continued.
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Indiana Pacers East 0.690 0.656 0.690 35
Los Angeles Clippers West 0.782 0.735 0.782 40
Los Angeles Lakers* West 0.681 0.592 0.681 42
Memphis Grizzlies West 0.690 0.690 0.690 22
Miami Heat* East 0.765 0.653 0.765 44
Milwaukee Bucks East 0.705 0.664 0.705 28
Minnesota Timberwolves West 0.682 0.637 0.682 32
New Orleans Pelicans West 0.809 0.763 0.809 39
New York Knicks East 0.496 0.348 0.496 33
Oklahoma City Thunder West 0.749 0.749 0.749 31
Orlando Magic* East 0.733 0.660 0.733 40
Philadelphia 76ers East 0.643 0.598 0.643 35
Phoenix Suns* West 0.790 0.774 0.810 61
Portland Trailblazers West 0.632 0.533 0.632 32
Sacramento Kings West 0.723 0.664 0.723 33
San Antonio Spurs** West 0.775 0.691 0.812 58
Toronto Raptors* East 0.856 0.856 0.856 47
Utah Jazz* West 0.795 0.740 0.821 51
Washington Wizards* East 0.758 0.713 0.758 41
2007 Atlanta Hawks* East 0.872 0.872 0.872 37
Boston Celtics** East 0.880 0.785 0.974 66
Brooklyn Nets East 0.807 0.807 0.807 34
Charlotte Hornets East 0.845 0.845 0.845 32
Chicago Bulls East 0.922 0.856 0.922 33
Cleveland Cavaliers* East 0.776 0.649 0.793 45
Dallas Mavericks* West 0.689 0.570 0.704 51
Denver Nuggets* West 0.756 0.756 0.756 50
Detroit Pistons* East 0.928 0.865 0.939 59
48 Table A.1 continued.
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Golden State Warriors West 0.903 0.903 0.903 48
Houston Rockets* West 0.845 0.792 0.899 55
Indiana Pacers East 0.737 0.737 0.737 36
Los Angeles Clippers West 0.799 0.792 0.799 23
Los Angeles Lakers* West 0.856 0.856 0.856 57
Memphis Grizzlies West 0.790 0.790 0.790 22
Miami Heat East 0.781 0.648 0.781 15
Milwaukee Bucks East 0.792 0.792 0.792 26
Minnesota Timberwolves West 0.722 0.722 0.722 22
New Orleans Pelicans* West 0.892 0.892 0.892 56
New York Knicks East 0.663 0.519 0.663 23
Oklahoma City Thunder West 0.754 0.754 0.754 20
Orlando Magic* East 0.915 0.915 0.915 52
Philadelphia 76ers* East 0.722 0.722 0.722 40
Phoenix Suns* West 0.853 0.853 0.853 55
Portland Trailblazers West 0.810 0.720 0.824 41
Sacramento Kings West 0.774 0.774 0.774 38
San Antonio Spurs* West 0.855 0.772 0.936 56
Toronto Raptors* East 0.863 0.863 0.863 41
Utah Jazz* West 0.898 0.898 0.898 54
Washington Wizards* East 0.838 0.837 0.838 43
2008 Atlanta Hawks* East 0.862 0.862 0.862 47
Boston Celtics** East 0.865 0.817 0.933 62
Brooklyn Nets East 0.838 0.838 0.838 34
Charlotte Hornets East 0.825 0.825 0.825 35
Chicago Bulls* East 0.921 0.921 0.921 41
Cleveland Cavaliers* East 0.821 0.696 0.873 66
Dallas Mavericks* West 0.771 0.684 0.806 50
49 Table A.1 continued.
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Denver Nuggets* West 0.880 0.880 0.880 54
Detroit Pistons* East 0.901 0.820 0.901 39
Golden State Warriors West 0.875 0.875 0.875 29
Houston Rockets* West 0.857 0.835 0.867 53
Indiana Pacers East 0.790 0.790 0.790 36
Los Angeles Clippers West 0.837 0.837 0.837 19
Los Angeles Lakers** West 0.894 0.877 0.918 65
Memphis Grizzlies West 0.807 0.807 0.807 24
Miami Heat* East 0.862 0.862 0.862 43
Milwaukee Bucks East 0.787 0.787 0.787 34
Minnesota Timberwolves West 0.778 0.778 0.778 24
New Orleans Pelicans* West 0.875 0.875 0.875 49
New York Knicks East 0.716 0.637 0.716 32
Oklahoma City Thunder West 0.855 0.850 0.855 23
Orlando Magic* East 0.902 0.889 0.923 59
Philadelphia 76ers* East 0.830 0.830 0.830 41
Phoenix Suns West 0.845 0.845 0.845 46
Portland Trailblazers* West 0.863 0.774 0.903 54
Sacramento Kings West 0.721 0.721 0.721 17
San Antonio Spurs* West 0.907 0.896 0.912 54
Toronto Raptors East 0.829 0.829 0.829 33
Utah Jazz* West 0.936 0.936 0.936 48
Washington Wizards East 0.795 0.795 0.795 19
2009 Atlanta Hawks* East 0.889 0.889 0.889 47
Boston Celtics** East 0.773 0.693 0.813 62
Brooklyn Nets East 0.777 0.777 0.777 34
Charlotte Hornets* East 0.806 0.779 0.821 35
Chicago Bulls* East 0.887 0.798 0.887 41
50 Table A.1 continued.
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Cleveland Cavaliers* East 0.836 0.718 0.897 66
Dallas Mavericks* West 0.784 0.681 0.835 50
Denver Nuggets* West 0.832 0.802 0.849 54
Detroit Pistons East 0.911 0.846 0.911 39
Golden State Warriors West 0.864 0.864 0.864 29
Houston Rockets West 0.812 0.812 0.812 53
Indiana Pacers East 0.768 0.768 0.768 36
Los Angeles Clippers West 0.846 0.846 0.846 19
Los Angeles Lakers** West 0.763 0.640 0.916 65
Memphis Grizzlies West 0.841 0.841 0.841 24
Miami Heat* East 0.809 0.741 0.846 43
Milwaukee Bucks* East 0.822 0.817 0.828 34
Minnesota Timberwolves West 0.810 0.810 0.810 24
New Orleans Pelicans West 0.771 0.771 0.771 49
New York Knicks East 0.765 0.657 0.765 32
Oklahoma City Thunder* West 0.937 0.937 0.937 23
Orlando Magic* East 0.827 0.711 0.987 59
Philadelphia 76ers East 0.778 0.778 0.778 41
Phoenix Suns* West 0.904 0.904 0.904 46
Portland Trailblazers* West 0.989 0.978 0.990 54
Sacramento Kings West 0.738 0.738 0.738 17
San Antonio Spurs* West 0.796 0.736 0.829 54
Toronto Raptors East 0.846 0.846 0.846 33
Utah Jazz* West 0.872 0.871 0.873 48
Washington Wizards East 0.762 0.712 0.762 19
2010 Atlanta Hawks* East 0.686 0.631 0.690 44
Boston Celtics* East 0.706 0.582 0.839 56
Brooklyn Nets East 0.728 0.728 0.728 24
51 Table A.1 continued.
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Charlotte Hornets East 0.712 0.659 0.717 34
Chicago Bulls* East 0.943 0.891 0.948 62
Cleveland Cavaliers East 0.886 0.796 0.886 19
Dallas Mavericks** West 0.699 0.579 0.707 57
Denver Nuggets* West 0.758 0.749 0.770 50
Detroit Pistons East 0.735 0.683 0.739 30
Golden State Warriors West 0.765 0.712 0.769 36
Houston Rockets West 0.705 0.701 0.705 43
Indiana Pacers* East 0.686 0.686 0.686 37
Los Angeles Clippers West 0.853 0.853 0.853 32
Los Angeles Lakers* West 0.669 0.545 0.794 57
Memphis Grizzlies* West 0.711 0.681 0.748 46
Miami Heat East 0.821 0.744 0.925 58
Milwaukee Bucks East 0.684 0.612 0.690 35
Minnesota Timberwolves West 0.791 0.791 0.791 17
New Orleans Pelicans* West 0.717 0.666 0.780 46
New York Knicks* East 0.798 0.748 0.802 42
Oklahoma City Thunder* West 0.880 0.880 0.880 55
Orlando Magic* East 0.646 0.510 0.654 52
Philadelphia 76ers* East 0.692 0.692 0.692 41
Phoenix Suns West 0.763 0.747 0.765 40
Portland Trailblazers* West 0.756 0.612 0.766 48
Sacramento Kings West 0.834 0.834 0.834 24
San Antonio Spurs* West 0.819 0.724 0.946 61
Toronto Raptors East 0.704 0.656 0.708 22
Utah Jazz West 0.732 0.633 0.740 39
Washington Wizards East 0.784 0.757 0.787 23
2011 Atlanta Hawks* East 0.750 0.692 0.840 40
52 Table A.1 continued.
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Boston Celtics* East 0.728 0.622 0.728 39
Brooklyn Nets East 0.714 0.704 0.714 22
Charlotte Hornets East 0.774 0.728 0.774 7
Chicago Bulls* East 0.866 0.763 0.866 50
Cleveland Cavaliers East 0.757 0.696 0.757 21
Dallas Mavericks* West 0.777 0.658 0.777 36
Denver Nuggets* West 0.844 0.844 0.844 38
Detroit Pistons East 0.684 0.627 0.684 25
Golden State Warriors West 0.854 0.832 0.854 23
Houston Rockets West 0.812 0.812 0.812 34
Indiana Pacers* East 0.932 0.932 0.932 42
Los Angeles Clippers* West 0.819 0.750 0.819 40
Los Angeles Lakers* West 0.696 0.595 0.696 41
Memphis Grizzlies* West 0.774 0.700 0.892 41
Miami Heat** East 0.781 0.676 0.942 46
Milwaukee Bucks East 0.778 0.778 0.778 31
Minnesota Timberwolves West 0.858 0.858 0.858 26
New Orleans Pelicans West 0.740 0.717 0.740 21
New York Knicks* East 0.765 0.641 0.765 36
Oklahoma City Thunder* West 0.916 0.916 0.916 47
Orlando Magic* East 0.684 0.537 0.684 37
Philadelphia 76ers* East 0.790 0.769 0.790 35
Phoenix Suns West 0.673 0.641 0.673 33
Portland Trailblazers West 0.757 0.617 0.757 28
Sacramento Kings West 0.855 0.855 0.855 22
San Antonio Spurs* West 0.840 0.756 0.986 50
Toronto Raptors East 0.856 0.856 0.856 23
Utah Jazz* West 0.883 0.883 0.883 36
53 Table A.1 continued.
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Washington Wizards East 0.851 0.851 0.851 20
2012 Atlanta Hawks* East 0.792 0.792 0.792 44
Boston Celtics* East 0.780 0.728 0.814 41
Brooklyn Nets* East 0.719 0.610 0.780 49
Charlotte Hornets East 0.799 0.799 0.799 21
Chicago Bulls* East 0.813 0.685 0.813 45
Cleveland Cavaliers East 0.746 0.732 0.746 24
Dallas Mavericks West 0.832 0.827 0.832 41
Denver Nuggets* West 0.865 0.865 0.865 57
Detroit Pistons East 0.752 0.752 0.752 29
Golden State Warriors* West 0.835 0.802 0.860 47
Houston Rockets* West 0.886 0.886 0.886 45
Indiana Pacers* East 0.809 0.786 0.825 49
Los Angeles Clippers* West 0.837 0.775 0.880 56
Los Angeles Lakers* West 0.661 0.551 0.716 45
Memphis Grizzlies* West 0.883 0.825 0.969 56
Miami Heat** East 0.824 0.700 0.902 66
Milwaukee Bucks* East 0.796 0.796 0.796 38
Minnesota Timberwolves West 0.749 0.749 0.749 31
New Orleans Pelicans West 0.728 0.728 0.728 27
New York Knicks* East 0.791 0.670 0.864 54
Oklahoma City Thunder* West 0.885 0.885 0.885 60
Orlando Magic East 0.671 0.588 0.671 20
Philadelphia 76ers East 0.671 0.607 0.671 34
Phoenix Suns West 0.783 0.783 0.783 25
Portland Trailblazers West 0.780 0.692 0.780 33
Sacramento Kings West 0.796 0.796 0.796 28
San Antonio Spurs* West 0.866 0.850 0.879 58
54 Table A.1 continued.
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Toronto Raptors East 0.798 0.779 0.798 34
Utah Jazz West 0.830 0.817 0.839 43
Washington Wizards East 0.762 0.755 0.762 29
2013 Atlanta Hawks* East 0.842 0.842 0.842 38
Boston Celtics East 0.798 0.749 0.798 25
Brooklyn Nets* East 0.630 0.510 0.711 44
Charlotte Hornets* East 0.785 0.761 0.809 43
Chicago Bulls* East 0.865 0.762 0.865 48
Cleveland Cavaliers East 0.811 0.811 0.811 33
Dallas Mavericks* West 0.844 0.821 0.869 49
Denver Nuggets West 0.784 0.784 0.784 36
Detroit Pistons East 0.796 0.796 0.796 29
Golden State Warriors* West 0.872 0.852 0.896 51
Houston Rockets* West 0.892 0.886 0.900 54
Indiana Pacers* East 0.908 0.831 0.992 56
Los Angeles Clippers* West 0.890 0.864 0.920 57
Los Angeles Lakers West 0.737 0.683 0.737 27
Memphis Grizzlies* West 0.830 0.770 0.892 50
Miami Heat* East 0.793 0.683 0.893 54
Milwaukee Bucks East 0.755 0.755 0.755 15
Minnesota Timberwolves West 0.800 0.800 0.800 40
New Orleans Pelicans West 0.798 0.798 0.798 34
New York Knicks East 0.729 0.619 0.729 37
Oklahoma City Thunder* West 0.909 0.886 0.948 59
Orlando Magic East 0.713 0.682 0.713 23
Philadelphia 76ers East 0.828 0.828 0.828 19
Phoenix Suns West 0.885 0.885 0.885 48
Portland Trailblazers* West 0.831 0.762 0.900 54
55 Table A.1 continued.
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Sacramento Kings West 0.815 0.815 0.815 28
San Antonio Spurs** West 0.984 0.984 0.984 62
Toronto Raptors* East 0.824 0.765 0.884 48
Utah Jazz West 0.898 0.898 0.898 25
Washington Wizards* East 0.768 0.731 0.804 44
2014 Atlanta Hawks* East 0.995 0.995 0.995 60
Boston Celtics* East 0.859 0.859 0.859 40
Brooklyn Nets* East 0.669 0.568 0.686 38
Charlotte Hornets East 0.744 0.659 0.761 33
Chicago Bulls* East 0.816 0.690 0.843 50
Cleveland Cavaliers* East 0.806 0.675 0.891 53
Dallas Mavericks* West 0.787 0.682 0.856 50
Denver Nuggets West 0.828 0.828 0.828 30
Detroit Pistons East 0.787 0.787 0.787 32
Golden State Warriors** West 0.934 0.876 1.011 67
Houston Rockets* West 0.824 0.701 0.937 56
Indiana Pacers East 0.758 0.706 0.769 38
Los Angeles Clippers* West 0.801 0.703 0.891 56
Los Angeles Lakers West 0.760 0.674 0.772 21
Memphis Grizzlies* West 0.843 0.736 0.963 55
Miami Heat East 0.757 0.609 0.777 37
Milwaukee Bucks* East 0.816 0.816 0.816 41
Minnesota Timberwolves West 0.722 0.722 0.722 16
New Orleans Pelicans* West 0.787 0.748 0.826 45
New York Knicks East 0.745 0.594 0.745 17
Oklahoma City Thunder West 0.770 0.706 0.814 45
Orlando Magic East 0.841 0.841 0.841 25
Philadelphia 76ers East 0.791 0.791 0.791 18
56 Table A.1 continued.
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Phoenix Suns West 0.795 0.782 0.798 39
Portland Trailblazers* West 0.773 0.660 0.870 51
Sacramento Kings West 0.746 0.716 0.751 29
San Antonio Spurs* West 0.884 0.843 0.930 55
Toronto Raptors* East 0.796 0.691 0.866 49
Utah Jazz West 0.894 0.864 0.902 38
Washington Wizards* East 0.757 0.670 0.813 46
2015 Atlanta Hawks* East 0.853 0.853 0.853 48
Boston Celtics* East 0.848 0.835 0.854 48
Brooklyn Nets East 0.692 0.666 0.692 21
Charlotte Hornets* East 0.825 0.800 0.835 48
Chicago Bulls East 0.835 0.716 0.835 42
Cleveland Cavaliers** East 0.740 0.587 0.786 57
Dallas Mavericks* West 0.879 0.822 0.904 42
Denver Nuggets West 0.771 0.771 0.771 33
Detroit Pistons* East 0.754 0.677 0.781 44
Golden State Warriors* West 0.875 0.787 1.006 73
Houston Rockets* West 0.759 0.699 0.781 41
Indiana Pacers* East 0.844 0.844 0.844 45
Los Angeles Clippers* West 0.764 0.658 0.801 53
Los Angeles Lakers West 0.856 0.751 0.856 17
Memphis Grizzlies* West 0.770 0.708 0.792 42
Miami Heat* East 0.819 0.723 0.856 48
Milwaukee Bucks East 0.781 0.781 0.781 33
Minnesota Timberwolves West 0.757 0.757 0.757 29
New Orleans Pelicans West 0.763 0.750 0.763 30
New York Knicks East 0.867 0.799 0.867 32
Oklahoma City Thunder* West 0.787 0.738 0.836 55
57 Table A.1 continued.
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Orlando Magic East 0.896 0.896 0.896 35
Philadelphia 76ers East 0.823 0.823 0.823 10
Phoenix Suns West 0.832 0.820 0.832 23
Portland Trailblazers* West 0.957 0.957 0.957 44
Sacramento Kings West 0.834 0.834 0.834 33
San Antonio Spurs* West 0.874 0.776 0.975 67
Toronto Raptors* East 0.922 0.855 0.970 56
Utah Jazz West 0.933 0.906 0.945 40
Washington Wizards East 0.782 0.741 0.797 41
2016 Atlanta Hawks* East 0.716 0.649 0.776 43
Boston Celtics* East 0.830 0.755 0.907 53
Brooklyn Nets East 0.790 0.790 0.790 20
Charlotte Hornets East 0.706 0.644 0.726 36
Chicago Bulls* East 0.803 0.671 0.817 41
Cleveland Cavaliers* East 0.658 0.506 0.697 51
Dallas Mavericks West 0.687 0.523 0.687 33
Denver Nuggets West 0.845 0.845 0.845 40
Detroit Pistons East 0.654 0.570 0.678 37
Golden State Warriors** West 0.853 0.774 0.977 67
Houston Rockets* West 0.795 0.736 0.855 55
Indiana Pacers* East 0.754 0.719 0.767 42
Los Angeles Clippers* West 0.701 0.576 0.798 51
Los Angeles Lakers West 0.778 0.686 0.778 26
Memphis Grizzlies* West 0.667 0.559 0.749 43
Miami Heat East 0.735 0.605 0.775 41
Milwaukee Bucks* East 0.712 0.667 0.752 42
Minnesota Timberwolves West 0.760 0.760 0.760 31
New Orleans Pelicans West 0.704 0.666 0.717 34
58 Table A.1 continued.
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
New York Knicks East 0.724 0.608 0.724 31
Oklahoma City Thunder* West 0.811 0.747 0.835 47
Orlando Magic East 0.672 0.563 0.672 29
Philadelphia 76ers East 0.848 0.848 0.848 28
Phoenix Suns West 0.829 0.829 0.829 24
Portland Trailblazers* West 0.690 0.571 0.725 41
Sacramento Kings West 0.729 0.657 0.737 32
San Antonio Spurs* West 0.769 0.625 0.891 61
Toronto Raptors* East 0.752 0.621 0.794 51
Utah Jazz* West 0.867 0.766 0.907 51
Washington Wizards* East 0.723 0.642 0.793 49
2017 Atlanta Hawks East 0.794 0.794 0.794 24
Boston Celtics* East 0.875 0.778 0.919 55
Brooklyn Nets East 0.847 0.847 0.847 28
Charlotte Hornets East 0.791 0.777 0.796 36
Chicago Bulls East 0.983 0.967 0.983 27
Cleveland Cavaliers* East 0.814 0.689 0.855 50
Dallas Mavericks West 0.980 0.980 0.980 24
Denver Nuggets West 0.865 0.865 0.865 46
Detroit Pistons East 0.800 0.734 0.824 39
Golden State Warriors** West 0.823 0.778 0.861 58
Houston Rockets* West 0.893 0.806 0.967 65
Indiana Pacers* East 0.910 0.910 0.910 48
Los Angeles Clippers West 0.803 0.770 0.816 42
Los Angeles Lakers West 0.885 0.873 0.890 35
Memphis Grizzlies West 0.775 0.748 0.784 22
Miami Heat* East 0.806 0.679 0.848 44
Milwaukee Bucks* East 0.799 0.767 0.813 44
59 Table A.1 continued.
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Minnesota Timberwolves* West 0.826 0.808 0.834 47
New Orleans Pelicans* West 0.813 0.813 0.813 48
New York Knicks East 0.869 0.833 0.883 29
Oklahoma City Thunder* West 0.781 0.678 0.822 48
Orlando Magic East 0.881 0.881 0.881 25
Philadelphia 76ers* East 0.966 0.966 0.966 52
Phoenix Suns West 0.862 0.862 0.862 21
Portland Trailblazers* West 0.858 0.751 0.897 49
Sacramento Kings West 0.882 0.860 0.891 27
San Antonio Spurs* West 0.850 0.780 0.882 47
Toronto Raptors* East 0.903 0.849 0.953 59
Utah Jazz* West 0.881 0.847 0.898 48
Washington Wizards* East 0.810 0.754 0.830 43
2018 Atlanta Hawks East 0.630 0.567 0.645 29
Boston Celtics* East 0.729 0.611 0.778 49
Brooklyn Nets* East 0.663 0.576 0.696 42
Charlotte Hornets East 0.709 0.622 0.745 39
Chicago Bulls East 0.745 0.594 0.757 22
Cleveland Cavaliers East 0.750 0.601 0.762 19
Dallas Mavericks West 0.789 0.653 0.827 33
Denver Nuggets* West 0.813 0.712 0.980 54
Detroit Pistons* East 0.746 0.640 0.792 41
Golden State Warriors* West 0.846 0.789 0.877 57
Houston Rockets* West 0.806 0.685 0.997 53
Indiana Pacers* East 0.778 0.698 0.815 48
Los Angeles Clippers* West 0.791 0.722 0.825 48
Los Angeles Lakers West 0.794 0.708 0.820 37
Memphis Grizzlies West 0.724 0.660 0.753 33
60 Table A.1 continued.
Overall Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Miami Heat East 0.806 0.675 0.844 39
Milwaukee Bucks* East 0.889 0.812 1.032 60
Minnesota Timberwolves West 0.749 0.738 0.754 36
New Orleans Pelicans West 0.760 0.760 0.760 33
New York Knicks East 0.788 0.666 0.788 17
Oklahoma City Thunder* West 0.840 0.767 0.878 49
Orlando Magic* East 0.816 0.753 0.849 42
Philadelphia 76ers* East 0.890 0.818 0.930 51
Phoenix Suns West 0.730 0.717 0.734 19
Portland Trailblazers* West 0.884 0.805 0.927 53
Sacramento Kings West 0.814 0.793 0.825 39
San Antonio Spurs* West 0.869 0.826 0.893 48
Toronto Raptors** East 0.921 0.854 0.960 58
Utah Jazz* West 0.893 0.863 0.910 50
Washington Wizards East 0.912 0.912 0.912 32
Notes: *Playof teams, **League Champion
61 Appendix B
Efficiency scores by Conference
Table B.1. Efficiency score over East conference
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
2001 Atlanta Hawks East 0.745 0.745 0.745 33
Boston Celtics* East 0.934 0.888 1.021 49
Brooklyn Nets East 0.740 0.590 0.929 52
Chicago Bulls East 0.937 0.904 0.937 21
Cleveland Cavaliers East 0.811 0.811 0.811 29
Detroit Pistons* East 1.000 1.000 1.000 50
Indiana Pacers* East 0.828 0.818 0.839 42
Miami Heat East 0.779 0.724 0.829 36
Milwaukee Bucks East 0.814 0.782 0.845 41
New York Knicks East 0.626 0.458 0.626 30
Orlando Magic* East 0.904 0.904 0.904 44
Philadelphia 76ers* East 0.826 0.703 0.830 43
Toronto Raptors* East 0.860 0.776 0.943 42
Washington Wizards East 0.856 0.748 0.856 37
2002 Atlanta Hawks East 0.751 0.751 0.751 35
Boston Celtics* East 0.851 0.803 0.928 44
Brooklyn Nets East 0.835 0.772 0.934 49
62 Table B.1 continued.
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Chicago Bulls East 0.970 0.970 0.970 30
Cleveland Cavaliers East 0.728 0.728 0.728 17
Detroit Pistons* East 0.955 0.913 0.955 50
Indiana Pacers* East 0.886 0.886 0.886 48
Miami Heat East 0.744 0.681 0.744 25
Milwaukee Bucks* East 0.798 0.798 0.798 42
New York Knicks East 0.617 0.477 0.617 37
Orlando Magic* East 0.856 0.856 0.856 42
Philadelphia 76ers* East 0.795 0.721 0.795 48
Toronto Raptors East 0.845 0.747 0.845 24
Washington Wizards East 0.959 0.933 0.959 37
2003 Atlanta Hawks East 0.674 0.674 0.674 28
Boston Celtics* East 0.752 0.743 0.752 36
Brooklyn Nets* East 0.751 0.710 0.788 47
Chicago Bulls East 0.859 0.761 0.859 23
Cleveland Cavaliers East 0.918 0.918 0.918 35
Detroit Pistons** East 0.914 0.841 0.914 54
Indiana Pacers* East 0.877 0.781 0.973 61
Miami Heat* East 0.851 0.851 0.851 42
Milwaukee Bucks* East 0.825 0.825 0.825 41
New York Knicks* East 0.635 0.499 0.635 39
Orlando Magic East 0.782 0.782 0.782 21
Philadelphia 76ers East 0.805 0.686 0.805 33
Toronto Raptors East 0.763 0.634 0.763 33
Washington Wizards East 0.857 0.857 0.857 25
2004 Atlanta Hawks East 0.613 0.556 0.613 13
Boston Celtics* East 0.517 0.409 0.596 45
Brooklyn Nets* East 0.544 0.424 0.635 42
63 Table B.1 continued.
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Charlotte Hornets East 0.844 0.844 0.844 18
Chicago Bulls* East 0.578 0.419 0.578 47
Cleveland Cavaliers East 0.634 0.521 0.634 42
Detroit Pistons* East 0.630 0.459 0.630 54
Indiana Pacers* East 0.490 0.356 0.575 44
Miami Heat* East 0.623 0.453 0.760 59
Milwaukee Bucks East 0.516 0.430 0.516 30
New York Knicks East 0.368 0.239 0.368 33
Orlando Magic East 0.459 0.381 0.511 36
Philadelphia 76ers* East 0.469 0.351 0.469 43
Toronto Raptors East 0.515 0.408 0.515 33
Washington Wizards* East 0.612 0.499 0.712 45
2005 Atlanta Hawks East 0.759 0.759 0.759 26
Boston Celtics East 0.679 0.607 0.683 33
Brooklyn Nets* East 0.618 0.511 0.714 49
Charlotte Hornets East 0.898 0.898 0.898 26
Chicago Bulls* East 0.753 0.603 0.753 41
Cleveland Cavaliers* East 0.774 0.673 0.781 50
Detroit Pistons* East 0.762 0.615 0.771 64
Indiana Pacers* East 0.536 0.426 0.541 41
Miami Heat** East 0.714 0.598 0.721 52
Milwaukee Bucks* East 0.634 0.546 0.639 40
New York Knicks East 0.394 0.250 0.394 23
Orlando Magic East 0.538 0.436 0.543 36
Philadelphia 76ers East 0.519 0.415 0.524 38
Toronto Raptors East 0.642 0.552 0.642 27
Washington Wizards* East 0.706 0.639 0.711 42
2006 Atlanta Hawks East 0.804 0.804 0.804 30
64 Table B.1 continued.
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Boston Celtics East 0.717 0.646 0.717 24
Brooklyn Nets* East 0.718 0.669 0.787 41
Charlotte Hornets East 0.870 0.870 0.870 33
Chicago Bulls* East 0.897 0.814 0.897 49
Cleveland Cavaliers* East 0.798 0.674 0.970 50
Detroit Pistons* East 0.856 0.748 0.856 53
Indiana Pacers East 0.690 0.656 0.690 35
Miami Heat* East 0.765 0.653 0.765 44
Milwaukee Bucks East 0.705 0.664 0.705 28
New York Knicks East 0.496 0.348 0.496 33
Orlando Magic* East 0.733 0.660 0.733 40
Philadelphia 76ers East 0.643 0.598 0.643 35
Toronto Raptors* East 0.876 0.870 0.885 47
Washington Wizards* East 0.758 0.713 0.758 41
2007 Atlanta Hawks* East 0.872 0.872 0.872 37
Boston Celtics** East 0.880 0.785 0.974 66
Brooklyn Nets East 0.807 0.807 0.807 34
Charlotte Hornets East 0.845 0.845 0.845 32
Chicago Bulls East 0.922 0.856 0.922 33
Cleveland Cavaliers* East 0.776 0.649 0.793 45
Detroit Pistons* East 0.928 0.865 0.939 59
Indiana Pacers East 0.737 0.737 0.737 36
Miami Heat East 0.781 0.648 0.781 15
Milwaukee Bucks East 0.792 0.792 0.792 26
New York Knicks East 0.663 0.519 0.663 23
Orlando Magic* East 0.915 0.915 0.915 52
Philadelphia 76ers* East 0.722 0.722 0.722 40
Toronto Raptors* East 0.863 0.863 0.863 41
65 Table B.1 continued.
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Washington Wizards* East 0.838 0.837 0.838 43
2008 Atlanta Hawks* East 0.888 0.888 0.888 47
Boston Celtics** East 0.891 0.864 0.933 62
Brooklyn Nets East 0.862 0.862 0.862 34
Charlotte Hornets East 0.849 0.849 0.849 35
Chicago Bulls* East 0.948 0.948 0.948 41
Cleveland Cavaliers* East 0.848 0.736 0.897 66
Detroit Pistons* East 0.929 0.867 0.929 39
Indiana Pacers East 0.813 0.813 0.813 36
Miami Heat* East 0.888 0.888 0.888 43
Milwaukee Bucks East 0.811 0.811 0.811 34
New York Knicks East 0.740 0.674 0.740 32
Orlando Magic* East 0.929 0.929 0.929 59
Philadelphia 76ers* East 0.855 0.855 0.855 41
Toronto Raptors East 0.854 0.854 0.854 33
Washington Wizards East 0.820 0.820 0.820 19
2009 Atlanta Hawks* East 0.941 0.941 0.941 47
Boston Celtics** East 0.829 0.775 0.847 62
Brooklyn Nets East 0.825 0.825 0.825 34
Charlotte Hornets* East 0.860 0.860 0.860 35
Chicago Bulls* East 0.943 0.892 0.943 41
Cleveland Cavaliers* East 0.891 0.803 0.923 66
Detroit Pistons East 0.966 0.946 0.966 39
Indiana Pacers East 0.820 0.820 0.820 36
Miami Heat* East 0.868 0.829 0.883 43
Milwaukee Bucks* East 0.873 0.873 0.873 34
New York Knicks East 0.817 0.735 0.817 32
Orlando Magic* East 0.882 0.795 1.015 59
66 Table B.1 continued.
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Philadelphia 76ers East 0.825 0.825 0.825 41
Toronto Raptors East 0.903 0.903 0.903 33
Washington Wizards East 0.812 0.796 0.812 19
2010 Atlanta Hawks* East 0.735 0.708 0.737 44
Boston Celtics* East 0.758 0.653 0.885 56
Brooklyn Nets East 0.776 0.776 0.776 24
Charlotte Hornets East 0.762 0.739 0.764 34
Chicago Bulls* East 1.000 1.000 1.000 62
Cleveland Cavaliers East 0.943 0.892 0.943 19
Detroit Pistons East 0.786 0.766 0.787 30
Indiana Pacers* East 0.732 0.732 0.732 37
Miami Heat East 0.875 0.835 0.937 58
Milwaukee Bucks East 0.734 0.686 0.738 35
New York Knicks* East 0.850 0.839 0.852 42
Orlando Magic* East 0.696 0.572 0.704 52
Philadelphia 76ers* East 0.739 0.739 0.739 41
Toronto Raptors East 0.754 0.736 0.755 22
Washington Wizards East 0.836 0.836 0.836 23
2011 Atlanta Hawks* East 0.759 0.708 0.842 40
Boston Celtics* East 0.738 0.636 0.738 39
Brooklyn Nets East 0.723 0.719 0.723 22
Charlotte Hornets East 0.784 0.745 0.784 7
Chicago Bulls* East 0.876 0.780 0.876 50
Cleveland Cavaliers East 0.767 0.711 0.767 21
Detroit Pistons East 0.694 0.641 0.694 25
Indiana Pacers* East 0.942 0.942 0.942 42
Miami Heat** East 0.791 0.691 0.949 46
Milwaukee Bucks East 0.787 0.787 0.787 31
67 Table B.1 continued.
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
New York Knicks* East 0.775 0.655 0.775 36
Orlando Magic* East 0.694 0.549 0.694 37
Philadelphia 76ers* East 0.800 0.787 0.800 35
Toronto Raptors East 0.866 0.866 0.866 23
Washington Wizards East 0.861 0.861 0.861 20
2012 Atlanta Hawks* East 0.853 0.853 0.853 44
Boston Celtics* East 0.844 0.839 0.849 41
Brooklyn Nets* East 0.783 0.703 0.835 49
Charlotte Hornets East 0.861 0.861 0.861 21
Chicago Bulls* East 0.882 0.789 0.882 45
Cleveland Cavaliers East 0.807 0.807 0.807 24
Detroit Pistons East 0.812 0.812 0.812 29
Indiana Pacers* East 0.873 0.873 0.873 49
Miami Heat** East 0.893 0.807 0.956 66
Milwaukee Bucks* East 0.857 0.857 0.857 38
New York Knicks* East 0.859 0.772 0.919 54
Orlando Magic East 0.732 0.677 0.732 20
Philadelphia 76ers East 0.731 0.700 0.731 34
Toronto Raptors East 0.862 0.862 0.862 34
Washington Wizards East 0.824 0.824 0.824 29
2013 Atlanta Hawks* East 0.842 0.842 0.842 38
Boston Celtics East 0.798 0.749 0.798 25
Brooklyn Nets* East 0.630 0.510 0.711 44
Charlotte Hornets* East 0.785 0.761 0.809 43
Chicago Bulls* East 0.865 0.762 0.865 48
Cleveland Cavaliers East 0.811 0.811 0.811 33
Detroit Pistons East 0.796 0.796 0.796 29
Indiana Pacers* East 0.908 0.831 0.992 56
68 Table B.1 continued.
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Miami Heat* East 0.793 0.683 0.893 54
Milwaukee Bucks East 0.755 0.755 0.755 15
New York Knicks East 0.729 0.619 0.729 37
Orlando Magic East 0.713 0.682 0.713 23
Philadelphia 76ers East 0.828 0.828 0.828 19
Toronto Raptors* East 0.824 0.765 0.884 48
Washington Wizards* East 0.768 0.731 0.804 44
2014 Atlanta Hawks* East 1.000 1.000 1.000 60
Boston Celtics* East 0.859 0.859 0.859 40
Brooklyn Nets* East 0.669 0.568 0.686 38
Charlotte Hornets East 0.744 0.659 0.761 33
Chicago Bulls* East 0.816 0.690 0.843 50
Cleveland Cavaliers* East 0.806 0.675 0.891 53
Detroit Pistons East 0.787 0.787 0.787 32
Indiana Pacers East 0.758 0.706 0.769 38
Miami Heat East 0.757 0.609 0.777 37
Milwaukee Bucks* East 0.818 0.818 0.818 41
New York Knicks East 0.745 0.594 0.745 17
Orlando Magic East 0.841 0.841 0.841 25
Philadelphia 76ers East 0.791 0.791 0.791 18
Toronto Raptors* East 0.796 0.691 0.866 49
Washington Wizards* East 0.757 0.670 0.813 46
2015 Atlanta Hawks* East 0.861 0.861 0.861 48
Boston Celtics* East 0.855 0.847 0.858 48
Brooklyn Nets East 0.698 0.675 0.698 21
Charlotte Hornets* East 0.831 0.811 0.840 48
Chicago Bulls East 0.842 0.727 0.842 42
Cleveland Cavaliers** East 0.747 0.596 0.793 57
69 Table B.1 continued.
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Detroit Pistons* East 0.760 0.687 0.787 44
Indiana Pacers* East 0.851 0.851 0.851 45
Miami Heat* East 0.826 0.734 0.862 48
Milwaukee Bucks East 0.787 0.787 0.787 33
New York Knicks East 0.874 0.811 0.874 32
Orlando Magic East 0.902 0.902 0.902 35
Philadelphia 76ers East 0.829 0.829 0.829 10
Toronto Raptors* East 0.929 0.867 0.974 56
Washington Wizards East 0.788 0.752 0.802 41
2016 Atlanta Hawks* East 0.799 0.749 0.881 43
Boston Celtics* East 0.931 0.872 1.045 53
Brooklyn Nets East 0.854 0.854 0.854 20
Charlotte Hornets East 0.772 0.744 0.788 36
Chicago Bulls* East 0.873 0.775 0.873 41
Cleveland Cavaliers* East 0.734 0.584 0.805 51
Detroit Pistons East 0.723 0.658 0.757 37
Indiana Pacers* East 0.830 0.829 0.830 42
Miami Heat East 0.807 0.699 0.868 41
Milwaukee Bucks* East 0.791 0.770 0.826 42
New York Knicks East 0.792 0.702 0.792 31
Orlando Magic East 0.737 0.650 0.737 29
Philadelphia 76ers East 0.916 0.916 0.916 28
Toronto Raptors* East 0.835 0.717 0.904 51
Washington Wizards* East 0.815 0.741 0.944 49
2017 Atlanta Hawks East 0.802 0.802 0.802 24
Boston Celtics* East 0.883 0.791 0.921 55
Brooklyn Nets East 0.855 0.855 0.855 28
Charlotte Hornets East 0.800 0.791 0.803 36
70 Table B.1 continued.
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Chicago Bulls East 0.992 0.984 0.992 27
Cleveland Cavaliers* East 0.824 0.701 0.868 50
Detroit Pistons East 0.810 0.746 0.834 39
Indiana Pacers* East 0.920 0.920 0.920 48
Miami Heat* East 0.816 0.691 0.860 44
Milwaukee Bucks* East 0.808 0.781 0.819 44
New York Knicks East 0.877 0.848 0.890 29
Orlando Magic East 0.890 0.890 0.890 25
Philadelphia 76ers* East 0.977 0.977 0.977 52
Toronto Raptors* East 0.913 0.863 1.005 59
Washington Wizards* East 0.819 0.768 0.839 43
2018 Atlanta Hawks East 0.630 0.567 0.645 29
Boston Celtics* East 0.729 0.611 0.778 49
Brooklyn Nets* East 0.663 0.576 0.696 42
Charlotte Hornets East 0.709 0.622 0.745 39
Chicago Bulls East 0.745 0.594 0.757 22
Cleveland Cavaliers East 0.750 0.601 0.762 19
Detroit Pistons* East 0.746 0.640 0.792 41
Indiana Pacers* East 0.778 0.698 0.815 48
Miami Heat East 0.806 0.675 0.844 39
Milwaukee Bucks* East 0.889 0.812 1.032 60
New York Knicks East 0.788 0.666 0.788 17
Orlando Magic* East 0.816 0.753 0.849 42
Philadelphia 76ers* East 0.890 0.818 0.930 51
Toronto Raptors** East 0.921 0.854 0.960 58
Washington Wizards East 0.912 0.912 0.912 32
Notes: *Playof teams, **League Champion
71 Table B.2. Efficiency scores over West conference
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
2001 Dallas Mavericks* West 0.753 0.655 0.875 57
Denver Nuggets West 0.653 0.589 0.653 27
Golden State Warriors West 0.695 0.695 0.695 21
Houston Rockets West 0.619 0.619 0.619 28
Los Angeles Clippers West 0.921 0.921 0.921 39
Los Angeles Lakers** West 0.788 0.682 0.924 58
Memphis Grizzlies West 0.658 0.618 0.658 23
Minnesota Timberwolves* West 0.729 0.672 0.800 50
Oklahoma City Thunder West 0.773 0.773 0.773 45
Phoenix Suns West 0.660 0.602 0.660 36
Portland Trailblazers* West 0.553 0.422 0.553 49
Sacramento Kings* West 0.805 0.704 0.941 61
San Antonio Spurs* West 0.865 0.761 0.865 58
Utah Jazz* West 0.738 0.675 0.738 44
2002 Dallas Mavericks* West 0.801 0.685 0.851 60
Denver Nuggets West 0.830 0.762 0.830 17
Golden State Warriors West 0.877 0.877 0.877 38
Houston Rockets West 0.827 0.827 0.827 43
Los Angeles Clippers West 0.966 0.966 0.966 27
Los Angeles Lakers** West 0.831 0.757 0.865 50
Memphis Grizzlies West 0.753 0.753 0.753 28
Minnesota Timberwolves* West 0.812 0.812 0.812 51
New Orleans Pelicans* West 0.928 0.928 0.928 47
Oklahoma City Thunder West 0.822 0.808 0.822 40
Phoenix Suns* West 0.830 0.799 0.845 44
Portland Trailblazers* West 0.599 0.427 0.599 50
Sacramento Kings* West 0.785 0.713 0.879 59
72 Table B.2 continued.
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
San Antonio Spurs** West 0.920 0.851 0.956 60
Utah Jazz* West 0.935 0.921 0.935 47
2003 Dallas Mavericks* West 0.669 0.553 0.718 52
Denver Nuggets* West 0.920 0.920 0.920 43
Golden State Warriors West 0.738 0.687 0.766 37
Houston Rockets* West 0.735 0.644 0.780 45
Los Angeles Clippers West 0.872 0.872 0.872 28
Los Angeles Lakers* West 0.751 0.617 0.815 56
Memphis Grizzlies* West 0.748 0.692 0.819 50
Minnesota Timberwolves* West 0.703 0.563 0.848 58
New Orleans Pelicans* West 0.753 0.722 0.770 41
Oklahoma City Thunder West 0.738 0.728 0.743 37
Phoenix Suns West 0.639 0.541 0.639 29
Portland Trailblazers West 0.570 0.442 0.613 41
Sacramento Kings* West 0.710 0.626 0.808 55
San Antonio Spurs* West 0.893 0.807 0.946 57
Utah Jazz West 1.000 1.000 1.000 42
2004 Dallas Mavericks* West 0.617 0.446 0.634 58
Denver Nuggets* West 0.883 0.883 0.883 49
Golden State Warriors West 0.757 0.693 0.767 34
Houston Rockets* West 0.736 0.632 0.788 51
Los Angeles Clippers West 0.861 0.853 0.862 37
Los Angeles Lakers West 0.725 0.583 0.744 34
Memphis Grizzlies* West 0.685 0.554 0.701 45
Minnesota Timberwolves West 0.678 0.571 0.692 44
New Orleans Pelicans West 0.674 0.585 0.674 18
Oklahoma City Thunder West 0.793 0.697 0.847 52
Phoenix Suns* West 0.961 0.961 0.961 62
73 Table B.2 continued.
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Portland Trailblazers West 0.573 0.438 0.586 27
Sacramento Kings* West 0.746 0.679 0.756 50
San Antonio Spurs** West 0.904 0.824 0.956 59
Utah Jazz West 0.906 0.829 0.906 26
2005 Dallas Mavericks* West 0.639 0.469 0.644 60
Denver Nuggets* West 0.833 0.833 0.833 44
Golden State Warriors West 0.845 0.762 0.845 34
Houston Rockets West 0.692 0.592 0.696 34
Los Angeles Clippers* West 0.882 0.882 0.882 47
Los Angeles Lakers* West 0.748 0.627 0.754 45
Memphis Grizzlies* West 0.720 0.623 0.765 49
Minnesota Timberwolves West 0.759 0.690 0.759 33
New Orleans Pelicans West 1.000 1.000 1.000 38
Oklahoma City Thunder West 0.869 0.869 0.869 35
Phoenix Suns* West 0.883 0.883 0.883 54
Portland Trailblazers West 0.737 0.638 0.737 21
Sacramento Kings* West 0.785 0.723 0.788 44
San Antonio Spurs* West 0.832 0.713 0.895 63
Utah Jazz West 0.843 0.740 0.849 41
2006 Dallas Mavericks* West 0.796 0.661 0.796 67
Denver Nuggets* West 0.874 0.874 0.874 45
Golden State Warriors* West 0.897 0.897 0.897 42
Houston Rockets* West 0.865 0.865 0.865 52
Los Angeles Clippers West 0.946 0.946 0.946 40
Los Angeles Lakers* West 0.835 0.765 0.835 42
Memphis Grizzlies West 0.832 0.832 0.832 22
Minnesota Timberwolves West 0.829 0.823 0.829 32
New Orleans Pelicans West 0.977 0.977 0.977 39
74 Table B.2 continued.
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Oklahoma City Thunder West 0.901 0.901 0.901 31
Phoenix Suns* West 0.905 0.905 0.905 61
Portland Trailblazers West 0.779 0.688 0.779 32
Sacramento Kings West 0.879 0.858 0.879 33
San Antonio Spurs** West 0.904 0.893 0.904 58
Utah Jazz* West 0.950 0.950 0.950 51
2007 Dallas Mavericks* West 0.725 0.578 0.764 51
Denver Nuggets* West 0.782 0.782 0.782 50
Golden State Warriors West 0.945 0.945 0.945 48
Houston Rockets* West 0.873 0.803 0.981 55
Los Angeles Clippers West 0.840 0.803 0.840 23
Los Angeles Lakers* West 0.879 0.879 0.879 57
Memphis Grizzlies West 0.822 0.822 0.822 22
Minnesota Timberwolves West 0.757 0.756 0.757 22
New Orleans Pelicans* West 0.936 0.936 0.936 56
Oklahoma City Thunder West 0.788 0.788 0.788 20
Phoenix Suns* West 0.876 0.876 0.876 55
Portland Trailblazers West 0.844 0.730 0.844 41
Sacramento Kings West 0.809 0.809 0.809 38
San Antonio Spurs* West 0.878 0.783 0.913 56
Utah Jazz* West 0.941 0.941 0.941 54
2008 Dallas Mavericks* West 0.785 0.684 0.785 50
Denver Nuggets* West 0.915 0.915 0.915 54
Golden State Warriors West 0.924 0.924 0.924 29
Houston Rockets* West 0.887 0.835 0.945 53
Los Angeles Clippers West 0.884 0.884 0.884 19
Los Angeles Lakers** West 0.935 0.877 1.002 65
Memphis Grizzlies West 0.843 0.843 0.843 24
75 Table B.2 continued.
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Minnesota Timberwolves West 0.819 0.819 0.819 24
New Orleans Pelicans* West 0.898 0.882 0.917 49
Oklahoma City Thunder West 0.907 0.850 0.907 23
Phoenix Suns West 0.859 0.859 0.859 46
Portland Trailblazers* West 0.873 0.774 0.873 54
Sacramento Kings West 0.755 0.755 0.755 17
San Antonio Spurs* West 0.935 0.896 0.983 54
Utah Jazz* West 0.958 0.958 0.958 48
2009 Dallas Mavericks* West 0.795 0.681 0.894 50
Denver Nuggets* West 0.851 0.802 0.900 54
Golden State Warriors West 0.869 0.869 0.869 29
Houston Rockets West 0.815 0.813 0.818 53
Los Angeles Clippers West 0.851 0.851 0.851 19
Los Angeles Lakers** West 0.781 0.640 0.895 65
Memphis Grizzlies West 0.859 0.859 0.859 24
Minnesota Timberwolves West 0.815 0.815 0.815 24
New Orleans Pelicans West 0.771 0.771 0.771 49
Oklahoma City Thunder* West 0.951 0.951 0.951 23
Phoenix Suns* West 0.923 0.923 0.923 46
Portland Trailblazers* West 0.989 0.978 0.989 54
Sacramento Kings West 0.742 0.742 0.742 17
San Antonio Spurs* West 0.808 0.736 0.876 54
Utah Jazz* West 0.884 0.871 0.899 48
2010 Dallas Mavericks** West 0.733 0.579 0.832 57
Denver Nuggets* West 0.788 0.749 0.827 50
Golden State Warriors West 0.771 0.712 0.771 36
Houston Rockets West 0.725 0.701 0.743 43
Los Angeles Clippers West 0.861 0.856 0.861 32
76 Table B.2 continued.
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Los Angeles Lakers* West 0.696 0.545 0.809 57
Memphis Grizzlies* West 0.732 0.681 0.780 46
Minnesota Timberwolves West 0.803 0.803 0.803 17
New Orleans Pelicans* West 0.740 0.666 0.807 46
Oklahoma City Thunder* West 0.913 0.908 0.920 55
Phoenix Suns West 0.767 0.747 0.767 40
Portland Trailblazers* West 0.759 0.612 0.759 48
Sacramento Kings West 0.841 0.841 0.841 24
San Antonio Spurs* West 0.840 0.724 0.955 61
Utah Jazz West 0.738 0.633 0.738 39
2011 Dallas Mavericks* West 0.794 0.658 0.823 36
Denver Nuggets* West 0.893 0.893 0.893 38
Golden State Warriors West 0.861 0.832 0.861 23
Houston Rockets West 0.857 0.857 0.857 34
Los Angeles Clippers* West 0.857 0.750 0.929 40
Los Angeles Lakers* West 0.734 0.595 0.846 41
Memphis Grizzlies* West 0.799 0.700 0.893 41
Minnesota Timberwolves West 0.868 0.859 0.871 26
New Orleans Pelicans West 0.745 0.717 0.752 21
Oklahoma City Thunder* West 0.948 0.922 0.980 47
Phoenix Suns West 0.703 0.641 0.756 33
Portland Trailblazers West 0.763 0.617 0.763 28
Sacramento Kings West 0.864 0.864 0.864 22
San Antonio Spurs* West 0.861 0.756 0.969 50
Utah Jazz* West 0.908 0.895 0.918 36
2012 Dallas Mavericks West 0.890 0.827 0.922 41
Denver Nuggets* West 0.893 0.878 0.901 57
Golden State Warriors* West 0.883 0.802 0.924 47
77 Table B.2 continued.
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Houston Rockets* West 0.925 0.925 0.925 45
Los Angeles Clippers* West 0.872 0.775 0.918 56
Los Angeles Lakers* West 0.700 0.551 0.750 45
Memphis Grizzlies* West 0.904 0.825 0.945 56
Minnesota Timberwolves West 0.791 0.749 0.811 31
New Orleans Pelicans West 0.768 0.768 0.768 27
Oklahoma City Thunder* West 0.912 0.899 0.918 60
Phoenix Suns West 0.816 0.816 0.816 25
Portland Trailblazers West 0.818 0.692 0.818 33
Sacramento Kings West 0.842 0.842 0.842 28
San Antonio Spurs* West 0.896 0.850 0.920 58
Utah Jazz West 0.880 0.817 0.912 43
2013 Dallas Mavericks* West 0.902 0.824 0.924 49
Denver Nuggets West 0.850 0.833 0.855 36
Golden State Warriors* West 0.920 0.855 0.939 51
Houston Rockets* West 0.923 0.889 0.955 54
Los Angeles Clippers* West 0.922 0.867 0.971 57
Los Angeles Lakers West 0.788 0.686 0.812 27
Memphis Grizzlies* West 0.859 0.772 0.929 50
Minnesota Timberwolves West 0.829 0.829 0.829 40
New Orleans Pelicans West 0.864 0.864 0.864 34
Oklahoma City Thunder* West 0.932 0.889 0.972 59
Phoenix Suns West 0.914 0.914 0.914 48
Portland Trailblazers* West 0.866 0.764 0.893 54
Sacramento Kings West 0.875 0.875 0.875 28
San Antonio Spurs** West 1.000 1.000 1.000 62
Utah Jazz West 0.959 0.921 0.959 25
2014 Dallas Mavericks* West 0.839 0.722 0.869 50
78 Table B.2 continued.
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Denver Nuggets West 0.880 0.880 0.880 30
Golden State Warriors** West 0.962 0.927 1.012 67
Houston Rockets* West 0.851 0.741 0.906 56
Los Angeles Clippers* West 0.834 0.744 0.879 56
Los Angeles Lakers West 0.830 0.714 0.830 21
Memphis Grizzlies* West 0.871 0.779 0.980 55
Minnesota Timberwolves West 0.783 0.780 0.783 16
New Orleans Pelicans* West 0.828 0.791 0.848 45
Oklahoma City Thunder West 0.819 0.747 0.839 45
Phoenix Suns West 0.850 0.828 0.856 39
Portland Trailblazers* West 0.820 0.698 0.877 51
Sacramento Kings West 0.802 0.757 0.802 29
San Antonio Spurs* West 0.917 0.892 0.932 55
Utah Jazz West 0.955 0.914 0.955 38
2015 Dallas Mavericks* West 0.897 0.822 0.947 42
Denver Nuggets West 0.788 0.788 0.788 33
Golden State Warriors* West 0.875 0.787 1.006 73
Houston Rockets* West 0.776 0.699 0.820 41
Los Angeles Clippers* West 0.791 0.658 0.862 53
Los Angeles Lakers West 0.858 0.751 0.858 17
Memphis Grizzlies* West 0.792 0.708 0.840 42
Minnesota Timberwolves West 0.770 0.770 0.770 29
New Orleans Pelicans West 0.778 0.750 0.782 30
Oklahoma City Thunder* West 0.806 0.738 0.848 55
Phoenix Suns West 0.842 0.820 0.846 23
Portland Trailblazers* West 0.979 0.979 0.979 44
Sacramento Kings West 0.852 0.852 0.852 33
San Antonio Spurs* West 0.874 0.776 0.936 67
79 Table B.2 continued.
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Utah Jazz West 0.951 0.906 0.960 40
2016 Dallas Mavericks West 0.687 0.523 0.687 33
Denver Nuggets West 0.845 0.845 0.845 40
Golden State Warriors** West 0.853 0.774 0.977 67
Houston Rockets* West 0.795 0.736 0.855 55
Los Angeles Clippers* West 0.701 0.576 0.798 51
Los Angeles Lakers West 0.778 0.686 0.778 26
Memphis Grizzlies* West 0.667 0.559 0.749 43
Minnesota Timberwolves West 0.763 0.763 0.763 31
New Orleans Pelicans West 0.706 0.666 0.717 34
Oklahoma City Thunder* West 0.811 0.747 0.831 47
Phoenix Suns West 0.829 0.829 0.829 24
Portland Trailblazers* West 0.693 0.571 0.722 41
Sacramento Kings West 0.732 0.657 0.753 32
San Antonio Spurs* West 0.769 0.625 0.891 61
Utah Jazz* West 0.867 0.766 0.900 51
2017 Dallas Mavericks West 1.000 1.000 1.000 24
Denver Nuggets West 0.868 0.868 0.868 46
Golden State Warriors** West 0.831 0.778 0.867 58
Houston Rockets* West 0.893 0.806 0.954 65
Los Angeles Clippers West 0.804 0.770 0.811 42
Los Angeles Lakers West 0.895 0.873 0.901 35
Memphis Grizzlies West 0.790 0.748 0.798 22
Minnesota Timberwolves* West 0.830 0.808 0.845 47
New Orleans Pelicans* West 0.820 0.820 0.820 48
Oklahoma City Thunder* West 0.783 0.678 0.846 48
Phoenix Suns West 0.880 0.880 0.880 21
Portland Trailblazers* West 0.858 0.751 0.880 49
80 Table B.2 continued.
Conference Salary Cap On-court Season Team Conference Wins efficiency efficiency efficiency
Sacramento Kings West 0.897 0.860 0.906 27
San Antonio Spurs* West 0.851 0.780 0.899 47
Utah Jazz* West 0.884 0.847 0.912 48
2018 Dallas Mavericks West 0.862 0.757 0.862 33
Denver Nuggets* West 0.893 0.825 0.934 54
Golden State Warriors* West 0.925 0.914 0.933 57
Houston Rockets* West 0.885 0.794 0.938 53
Los Angeles Clippers* West 0.867 0.837 0.886 48
Los Angeles Lakers West 0.870 0.820 0.898 37
Memphis Grizzlies West 0.796 0.765 0.812 33
Minnesota Timberwolves West 0.819 0.819 0.819 36
New Orleans Pelicans West 0.830 0.830 0.830 33
Oklahoma City Thunder* West 0.919 0.889 0.937 49
Phoenix Suns West 0.805 0.805 0.805 19
Portland Trailblazers* West 0.965 0.933 0.986 53
Sacramento Kings West 0.889 0.889 0.889 39
San Antonio Spurs* West 0.948 0.948 0.948 48
Utah Jazz* West 0.973 0.973 0.973 50
Notes: *Playof teams, **League Champion
81 Appendix C
Technology gap
Table C.1. Technology gap
Season Team Conference Technology Gap
2001 Atlanta Hawks East 0.836
Boston Celtics* East 0.834
Brooklyn Nets East 0.816
Chicago Bulls East 0.882
Cleveland Cavaliers East 0.884
Dallas Mavericks* West 1.000
Denver Nuggets West 1.000
Detroit Pistons* East 0.839
Golden State Warriors West 1.000
Houston Rockets West 1.000
Indiana Pacers* East 0.839
Los Angeles Clippers West 1.000
Los Angeles Lakers** West 1.000
Memphis Grizzlies West 1.000
Miami Heat East 0.856
Milwaukee Bucks East 0.859
Minnesota Timberwolves* West 1.000
New York Knicks East 0.852
82 Table C.1 continued.
Season Team Conference Technology Gap
Oklahoma City Thunder West 1.000
Orlando Magic* East 0.841
Philadelphia 76ers* East 0.869
Phoenix Suns West 1.000
Portland Trailblazers* West 1.000
Sacramento Kings* West 1.000
San Antonio Spurs* West 1.000
Toronto Raptors* East 0.871
Utah Jazz* West 1.000
Washington Wizards East 0.873
2002 Atlanta Hawks East 0.969
Boston Celtics* East 0.978
Brooklyn Nets East 0.937
Chicago Bulls East 0.987
Cleveland Cavaliers East 0.986
Dallas Mavericks* West 0.984
Denver Nuggets West 0.949
Detroit Pistons* East 0.987
Golden State Warriors West 0.956
Houston Rockets West 0.991
Indiana Pacers* East 0.954
Los Angeles Clippers West 0.949
Los Angeles Lakers** West 0.966
Memphis Grizzlies West 0.955
Miami Heat East 0.985
Milwaukee Bucks* East 0.976
Minnesota Timberwolves* West 0.996
New Orleans Pelicans* West 0.985
New York Knicks East 0.983
83 Table C.1 continued.
Season Team Conference Technology Gap
Oklahoma City Thunder West 0.965
Orlando Magic* East 0.961
Philadelphia 76ers* East 0.985
Phoenix Suns* West 0.971
Portland Trailblazers* West 0.961
Sacramento Kings* West 1.000
San Antonio Spurs** West 1.000
Toronto Raptors East 0.985
Utah Jazz* West 0.950
Washington Wizards East 0.987
2003 Atlanta Hawks East 0.886
Boston Celtics* East 0.890
Brooklyn Nets* East 0.888
Chicago Bulls East 0.891
Cleveland Cavaliers East 0.903
Dallas Mavericks* West 0.961
Denver Nuggets* West 0.965
Detroit Pistons** East 0.895
Golden State Warriors West 0.976
Houston Rockets* West 0.975
Indiana Pacers* East 0.892
Los Angeles Clippers West 0.981
Los Angeles Lakers* West 0.977
Memphis Grizzlies* West 0.982
Miami Heat* East 0.898
Milwaukee Bucks* East 0.898
Minnesota Timberwolves* West 0.981
New Orleans Pelicans* West 0.975
New York Knicks* East 0.874
84 Table C.1 continued.
Season Team Conference Technology Gap
Oklahoma City Thunder West 0.968
Orlando Magic East 0.895
Philadelphia 76ers East 0.887
Phoenix Suns West 0.981
Portland Trailblazers West 0.964
Sacramento Kings* West 0.987
San Antonio Spurs* West 0.986
Toronto Raptors East 0.884
Utah Jazz West 0.979
Washington Wizards East 0.899
2004 Atlanta Hawks East 1.000
Boston Celtics* East 0.992
Brooklyn Nets* East 0.992
Charlotte Hornets East 1.000
Chicago Bulls* East 1.000
Cleveland Cavaliers East 1.000
Dallas Mavericks* West 0.723
Denver Nuggets* West 0.761
Detroit Pistons* East 1.000
Golden State Warriors West 0.722
Houston Rockets* West 0.757
Indiana Pacers* East 0.996
Los Angeles Clippers West 0.735
Los Angeles Lakers West 0.711
Memphis Grizzlies* West 0.719
Miami Heat* East 0.988
Milwaukee Bucks East 1.000
Minnesota Timberwolves West 0.713
New Orleans Pelicans West 0.720
85 Table C.1 continued.
Season Team Conference Technology Gap
New York Knicks East 1.000
Oklahoma City Thunder West 0.764
Orlando Magic East 0.999
Philadelphia 76ers* East 1.000
Phoenix Suns* West 0.795
Portland Trailblazers West 0.698
Sacramento Kings* West 0.751
San Antonio Spurs** West 0.780
Toronto Raptors East 1.000
Utah Jazz West 0.740
Washington Wizards* East 0.996
2005 Atlanta Hawks East 1.000
Boston Celtics East 1.000
Brooklyn Nets* East 1.000
Charlotte Hornets East 1.000
Chicago Bulls* East 1.000
Cleveland Cavaliers* East 1.000
Dallas Mavericks* West 0.818
Denver Nuggets* West 0.837
Detroit Pistons* East 1.000
Golden State Warriors West 0.828
Houston Rockets West 0.819
Indiana Pacers* East 1.000
Los Angeles Clippers* West 0.841
Los Angeles Lakers* West 0.821
Memphis Grizzlies* West 0.838
Miami Heat** East 1.000
Milwaukee Bucks* East 1.000
Minnesota Timberwolves West 0.825
86 Table C.1 continued.
Season Team Conference Technology Gap
New Orleans Pelicans West 0.842
New York Knicks East 1.000
Oklahoma City Thunder West 0.842
Orlando Magic East 1.000
Philadelphia 76ers East 1.000
Phoenix Suns* West 0.858
Portland Trailblazers West 0.820
Sacramento Kings* West 0.829
San Antonio Spurs* West 0.858
Toronto Raptors East 1.000
Utah Jazz West 0.827
Washington Wizards* East 1.000
2006 Atlanta Hawks East 1.000
Boston Celtics East 1.000
Brooklyn Nets* East 0.997
Charlotte Hornets East 1.000
Chicago Bulls* East 1.000
Cleveland Cavaliers* East 0.994
Dallas Mavericks* West 0.851
Denver Nuggets* West 0.838
Detroit Pistons* East 1.000
Golden State Warriors* West 0.828
Houston Rockets* West 0.859
Indiana Pacers East 1.000
Los Angeles Clippers West 0.827
Los Angeles Lakers* West 0.816
Memphis Grizzlies West 0.829
Miami Heat* East 1.000
Milwaukee Bucks East 1.000
87 Table C.1 continued.
Season Team Conference Technology Gap
Minnesota Timberwolves West 0.822
New Orleans Pelicans West 0.828
New York Knicks East 1.000
Oklahoma City Thunder West 0.831
Orlando Magic* East 1.000
Philadelphia 76ers East 1.000
Phoenix Suns* West 0.873
Portland Trailblazers West 0.811
Sacramento Kings West 0.822
San Antonio Spurs** West 0.858
Toronto Raptors* East 0.978
Utah Jazz* West 0.837
Washington Wizards* East 1.000
2007 Atlanta Hawks* East 1.000
Boston Celtics** East 1.000
Brooklyn Nets East 1.000
Charlotte Hornets East 1.000
Chicago Bulls East 1.000
Cleveland Cavaliers* East 1.000
Dallas Mavericks* West 0.951
Denver Nuggets* West 0.967
Detroit Pistons* East 1.000
Golden State Warriors West 0.956
Houston Rockets* West 0.968
Indiana Pacers East 1.000
Los Angeles Clippers West 0.951
Los Angeles Lakers* West 0.974
Memphis Grizzlies West 0.962
Miami Heat East 1.000
88 Table C.1 continued.
Season Team Conference Technology Gap
Milwaukee Bucks East 1.000
Minnesota Timberwolves West 0.954
New Orleans Pelicans* West 0.953
New York Knicks East 1.000
Oklahoma City Thunder West 0.957
Orlando Magic* East 1.000
Philadelphia 76ers* East 1.000
Phoenix Suns* West 0.974
Portland Trailblazers West 0.960
Sacramento Kings West 0.956
San Antonio Spurs* West 0.973
Toronto Raptors* East 1.000
Utah Jazz* West 0.954
Washington Wizards* East 1.000
2008 Atlanta Hawks* East 0.971
Boston Celtics** East 0.970
Brooklyn Nets East 0.972
Charlotte Hornets East 0.972
Chicago Bulls* East 0.972
Cleveland Cavaliers* East 0.968
Dallas Mavericks* West 0.982
Denver Nuggets* West 0.961
Detroit Pistons* East 0.970
Golden State Warriors West 0.946
Houston Rockets* West 0.966
Indiana Pacers East 0.972
Los Angeles Clippers West 0.947
Los Angeles Lakers** West 0.956
Memphis Grizzlies West 0.957
89 Table C.1 continued.
Season Team Conference Technology Gap
Miami Heat* East 0.971
Milwaukee Bucks East 0.970
Minnesota Timberwolves West 0.950
New Orleans Pelicans* West 0.974
New York Knicks East 0.967
Oklahoma City Thunder West 0.943
Orlando Magic* East 0.971
Philadelphia 76ers* East 0.971
Phoenix Suns West 0.983
Portland Trailblazers* West 0.989
Sacramento Kings West 0.954
San Antonio Spurs* West 0.969
Toronto Raptors East 0.971
Utah Jazz* West 0.978
Washington Wizards East 0.970
2009 Atlanta Hawks* East 0.944
Boston Celtics** East 0.933
Brooklyn Nets East 0.942
Charlotte Hornets* East 0.937
Chicago Bulls* East 0.941
Cleveland Cavaliers* East 0.938
Dallas Mavericks* West 0.985
Denver Nuggets* West 0.978
Detroit Pistons East 0.943
Golden State Warriors West 0.994
Houston Rockets West 0.995
Indiana Pacers East 0.936
Los Angeles Clippers West 0.994
Los Angeles Lakers** West 0.978
90 Table C.1 continued.
Season Team Conference Technology Gap
Memphis Grizzlies West 0.980
Miami Heat* East 0.932
Milwaukee Bucks* East 0.942
Minnesota Timberwolves West 0.994
New Orleans Pelicans West 1.000
New York Knicks East 0.936
Oklahoma City Thunder* West 0.985
Orlando Magic* East 0.938
Philadelphia 76ers East 0.943
Phoenix Suns* West 0.980
Portland Trailblazers* West 1.000
Sacramento Kings West 0.995
San Antonio Spurs* West 0.985
Toronto Raptors East 0.937
Utah Jazz* West 0.987
Washington Wizards East 0.938
2010 Atlanta Hawks* East 0.933
Boston Celtics* East 0.931
Brooklyn Nets East 0.938
Charlotte Hornets East 0.935
Chicago Bulls* East 0.943
Cleveland Cavaliers East 0.940
Dallas Mavericks** West 0.954
Denver Nuggets* West 0.962
Detroit Pistons East 0.936
Golden State Warriors West 0.992
Houston Rockets West 0.972
Indiana Pacers* East 0.937
Los Angeles Clippers West 0.990
91 Table C.1 continued.
Season Team Conference Technology Gap
Los Angeles Lakers* West 0.961
Memphis Grizzlies* West 0.971
Miami Heat East 0.938
Milwaukee Bucks East 0.933
Minnesota Timberwolves West 0.984
New Orleans Pelicans* West 0.969
New York Knicks* East 0.938
Oklahoma City Thunder* West 0.964
Orlando Magic* East 0.928
Philadelphia 76ers* East 0.936
Phoenix Suns West 0.995
Portland Trailblazers* West 0.996
Sacramento Kings West 0.991
San Antonio Spurs* West 0.975
Toronto Raptors East 0.934
Utah Jazz West 0.992
Washington Wizards East 0.938
2011 Atlanta Hawks* East 0.987
Boston Celtics* East 0.987
Brooklyn Nets East 0.987
Charlotte Hornets East 0.987
Chicago Bulls* East 0.988
Cleveland Cavaliers East 0.987
Dallas Mavericks* West 0.979
Denver Nuggets* West 0.945
Detroit Pistons East 0.987
Golden State Warriors West 0.992
Houston Rockets West 0.948
Indiana Pacers* East 0.989
92 Table C.1 continued.
Season Team Conference Technology Gap
Los Angeles Clippers* West 0.956
Los Angeles Lakers* West 0.948
Memphis Grizzlies* West 0.969
Miami Heat** East 0.987
Milwaukee Bucks East 0.988
Minnesota Timberwolves West 0.989
New Orleans Pelicans West 0.992
New York Knicks* East 0.987
Oklahoma City Thunder* West 0.966
Orlando Magic* East 0.986
Philadelphia 76ers* East 0.988
Phoenix Suns West 0.957
Portland Trailblazers West 0.992
Sacramento Kings West 0.989
San Antonio Spurs* West 0.976
Toronto Raptors East 0.988
Utah Jazz* West 0.973
Washington Wizards East 0.988
2012 Atlanta Hawks* East 0.927
Boston Celtics* East 0.924
Brooklyn Nets* East 0.918
Charlotte Hornets East 0.928
Chicago Bulls* East 0.922
Cleveland Cavaliers East 0.924
Dallas Mavericks West 0.935
Denver Nuggets* West 0.969
Detroit Pistons East 0.927
Golden State Warriors* West 0.946
Houston Rockets* West 0.957
93 Table C.1 continued.
Season Team Conference Technology Gap
Indiana Pacers* East 0.926
Los Angeles Clippers* West 0.960
Los Angeles Lakers* West 0.945
Memphis Grizzlies* West 0.976
Miami Heat** East 0.923
Milwaukee Bucks* East 0.929
Minnesota Timberwolves West 0.946
New Orleans Pelicans West 0.948
New York Knicks* East 0.921
Oklahoma City Thunder* West 0.971
Orlando Magic East 0.917
Philadelphia 76ers East 0.918
Phoenix Suns West 0.959
Portland Trailblazers West 0.953
Sacramento Kings West 0.945
San Antonio Spurs* West 0.967
Toronto Raptors East 0.926
Utah Jazz West 0.943
Washington Wizards East 0.925
2013 Atlanta Hawks* East 1.000
Boston Celtics East 1.000
Brooklyn Nets* East 1.000
Charlotte Hornets* East 1.000
Chicago Bulls* East 1.000
Cleveland Cavaliers East 1.000
Dallas Mavericks* West 0.936
Denver Nuggets West 0.922
Detroit Pistons East 1.000
Golden State Warriors* West 0.948
94 Table C.1 continued.
Season Team Conference Technology Gap
Houston Rockets* West 0.966
Indiana Pacers* East 1.000
Los Angeles Clippers* West 0.966
Los Angeles Lakers West 0.936
Memphis Grizzlies* West 0.967
Miami Heat* East 1.000
Milwaukee Bucks East 1.000
Minnesota Timberwolves West 0.965
New Orleans Pelicans West 0.924
New York Knicks East 1.000
Oklahoma City Thunder* West 0.975
Orlando Magic East 1.000
Philadelphia 76ers East 1.000
Phoenix Suns West 0.969
Portland Trailblazers* West 0.959
Sacramento Kings West 0.932
San Antonio Spurs** West 0.984
Toronto Raptors* East 1.000
Utah Jazz West 0.936
Washington Wizards* East 1.000
2014 Atlanta Hawks* East 0.995
Boston Celtics* East 1.000
Brooklyn Nets* East 1.000
Charlotte Hornets East 1.000
Chicago Bulls* East 1.000
Cleveland Cavaliers* East 1.000
Dallas Mavericks* West 0.939
Denver Nuggets West 0.942
Detroit Pistons East 1.000
95 Table C.1 continued.
Season Team Conference Technology Gap
Golden State Warriors** West 0.971
Houston Rockets* West 0.968
Indiana Pacers East 1.000
Los Angeles Clippers* West 0.960
Los Angeles Lakers West 0.915
Memphis Grizzlies* West 0.968
Miami Heat East 1.000
Milwaukee Bucks* East 0.998
Minnesota Timberwolves West 0.922
New Orleans Pelicans* West 0.950
New York Knicks East 1.000
Oklahoma City Thunder West 0.940
Orlando Magic East 1.000
Philadelphia 76ers East 1.000
Phoenix Suns West 0.936
Portland Trailblazers* West 0.943
Sacramento Kings West 0.930
San Antonio Spurs* West 0.964
Toronto Raptors* East 1.000
Utah Jazz West 0.936
Washington Wizards* East 1.000
2015 Atlanta Hawks* East 0.991
Boston Celtics* East 0.992
Brooklyn Nets East 0.991
Charlotte Hornets* East 0.992
Chicago Bulls East 0.992
Cleveland Cavaliers** East 0.991
Dallas Mavericks* West 0.981
Denver Nuggets West 0.979
96 Table C.1 continued.
Season Team Conference Technology Gap
Detroit Pistons* East 0.991
Golden State Warriors* West 1.000
Houston Rockets* West 0.978
Indiana Pacers* East 0.992
Los Angeles Clippers* West 0.966
Los Angeles Lakers West 0.998
Memphis Grizzlies* West 0.972
Miami Heat* East 0.992
Milwaukee Bucks East 0.992
Minnesota Timberwolves West 0.984
New Orleans Pelicans West 0.982
New York Knicks East 0.992
Oklahoma City Thunder* West 0.976
Orlando Magic East 0.993
Philadelphia 76ers East 0.992
Phoenix Suns West 0.989
Portland Trailblazers* West 0.977
Sacramento Kings West 0.980
San Antonio Spurs* West 1.000
Toronto Raptors* East 0.992
Utah Jazz West 0.981
Washington Wizards East 0.992
2016 Atlanta Hawks* East 0.896
Boston Celtics* East 0.891
Brooklyn Nets East 0.925
Charlotte Hornets East 0.914
Chicago Bulls* East 0.920
Cleveland Cavaliers* East 0.897
Dallas Mavericks West 1.000
97 Table C.1 continued.
Season Team Conference Technology Gap
Denver Nuggets West 1.000
Detroit Pistons East 0.905
Golden State Warriors** West 1.000
Houston Rockets* West 1.000
Indiana Pacers* East 0.908
Los Angeles Clippers* West 1.000
Los Angeles Lakers West 1.000
Memphis Grizzlies* West 1.000
Miami Heat East 0.912
Milwaukee Bucks* East 0.900
Minnesota Timberwolves West 0.997
New Orleans Pelicans West 0.997
New York Knicks East 0.914
Oklahoma City Thunder* West 1.000
Orlando Magic East 0.912
Philadelphia 76ers East 0.926
Phoenix Suns West 1.000
Portland Trailblazers* West 0.997
Sacramento Kings West 0.997
San Antonio Spurs* West 1.000
Toronto Raptors* East 0.901
Utah Jazz* West 1.000
Washington Wizards* East 0.886
2017 Atlanta Hawks East 0.990
Boston Celtics* East 0.990
Brooklyn Nets East 0.990
Charlotte Hornets East 0.989
Chicago Bulls East 0.991
Cleveland Cavaliers* East 0.988
98 Table C.1 continued.
Season Team Conference Technology Gap
Dallas Mavericks West 0.980
Denver Nuggets West 0.997
Detroit Pistons East 0.988
Golden State Warriors** West 0.991
Houston Rockets* West 1.000
Indiana Pacers* East 0.989
Los Angeles Clippers West 0.999
Los Angeles Lakers West 0.988
Memphis Grizzlies West 0.981
Miami Heat* East 0.988
Milwaukee Bucks* East 0.989
Minnesota Timberwolves* West 0.995
New Orleans Pelicans* West 0.992
New York Knicks East 0.990
Oklahoma City Thunder* West 0.997
Orlando Magic East 0.991
Philadelphia 76ers* East 0.989
Phoenix Suns West 0.980
Portland Trailblazers* West 1.000
Sacramento Kings West 0.983
San Antonio Spurs* West 0.999
Toronto Raptors* East 0.989
Utah Jazz* West 0.996
Washington Wizards* East 0.988
2018 Atlanta Hawks East 1.000
Boston Celtics* East 1.000
Brooklyn Nets* East 1.000
Charlotte Hornets East 1.000
Chicago Bulls East 1.000
99 Table C.1 continued.
Season Team Conference Technology Gap
Cleveland Cavaliers East 1.000
Dallas Mavericks West 0.915
Denver Nuggets* West 0.911
Detroit Pistons* East 1.000
Golden State Warriors* West 0.915
Houston Rockets* West 0.911
Indiana Pacers* East 1.000
Los Angeles Clippers* West 0.912
Los Angeles Lakers West 0.912
Memphis Grizzlies West 0.910
Miami Heat East 1.000
Milwaukee Bucks* East 1.000
Minnesota Timberwolves West 0.914
New Orleans Pelicans West 0.916
New York Knicks East 1.000
Oklahoma City Thunder* West 0.914
Orlando Magic* East 1.000
Philadelphia 76ers* East 1.000
Phoenix Suns West 0.907
Portland Trailblazers* West 0.916
Sacramento Kings West 0.916
San Antonio Spurs* West 0.917
Toronto Raptors** East 1.000
Utah Jazz* West 0.918
Washington Wizards East 1.000
Notes: *Playof teams, **League Champion
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