Measuring the efficiency of NBA teams: The effect of the change in

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. , , , , and are among the top efficient teams, whereas , , , and 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 (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 (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 (Seattle Supersonics 1967-2008), (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. , Chicago Bulls, , 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, ,

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 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 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 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 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 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 West 0.788** 0.682 0.924 58 0.681* 0.592 0.681 42 West 0.658 0.618 0.658 23 0.690 0.690 0.690 22 East 0.667 0.581 0.667 36 0.765* 0.653 0.765 44 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 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 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 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 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 , 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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