1

DETERMINANTS OF COMPETITIVE BALANCE IN THE NATIONAL HOCKEY LEAGUE

Thomas Preissing

Department of Economics and Business, The Colorado College

Aju J. Fenn*1

Department of Economics and Business, The Colorado College

Economics and Business

Abstract

Abstract: Previous sports studies on competitive balance have focused on the standard deviation of wins, but this paper uses a more sensitive measure of parity. This paper calculates the deviations of the Herfindahl-Hirschman Index of team points (dHHIp) for the years 1942-2002 in hopes of better understanding the determinants of competitive balance for the National Hockey League. This paper finds the three major factors affecting parity in the league are the concentration of goals scored, the concentration of goals allowed, and the major expansion of 1967-1968. Also of note, free agency was found to be insignificant in determining competitive balance using the dHHIp model.

* Corresponding author: Aju J. Fenn, Department of Economics and Business, 14 E Cache La Poudre Street, Colorado Springs, CO 80903. Phone: 719 389 6409 (voice), E-mail: afenn@coloradocollege.edu..

2

I. Introduction

One of the major appeals of professional sports is what is referred to as the

“uncertainty of the outcome”. In other words sports fans prefer to be uncertain of who

will prevail in a given game. This “uncertainty” goes hand-in-hand with competitive

balance. The more unpredictable the outcome of a sporting league’s events are, the more

competitively balanced that particular league is assumed to be. A perfectly competitive

league would be one where every team wins exactly half their games. Recently, a

concern for competitive parity in the National Hockey League has emerged. As

columnist Scott Taylor wrote,

Currently, the NHL has almost a dozen teams that will never win the Stanley Cup. Because of the unworkable economic model, teams such as Nashville, Tampa, and Atlanta can only hope to have the stars align as they did for Carolina last year and, on a rare occasion, get to a final or maybe a conference championship.1 It is not in the National Hockey League’s best interest to have particular teams

winning or losing a disproportionate number of games from year to year. 2

In order for the NHL to develop increased competitiveness, it is important to investigate

the factors that affect the league’s parity. The purpose of this study is to examine the

determinants of competitive balance for the National Hockey League.

This paper will be the first to 3explore the determinants of competitive balance in

the National Hockey League using the Herfindahl-Hirschman Index (HHI). Section two

will examine previous research on competitive balance. Section three will describe the

data and model used, and section four will present the results of the regression analysis.

Finally, section five will discuss any conclusions that can be drawn as well as possible

pitfalls of this study.

3

II. Current Research on Competitive Balance

There have been a number of studies in the recent past that have looked at the

issue of competitive balance. Andrew Zimbalist (2002) recently wrote an article in the

Journal of Sports Economics that focuses not on competitive balance in any one

particular sport but looks at each of the four major professional sports leagues. He asserts

that the optimal level of balance in a sports league is “a function of the distribution of fan

preferences, fan population base, and fan income across host cities”.4 Zimbalist (2002)

discusses some of the more common ways of measuring competitive balance. The

methods include the Gini coefficient, the Herfindahl-Hirschman Index, the range of

winning percentages within a league, and standard deviation of winning percentage

within a league. Zimbalist (2002) suggests that factors like technology, playing

conditions, and playing rules are all influences on competitive balance yet almost

impossible to quantify.5 One of Zimbalist’s (2002) final points was that competitive

balance should be closely scrutinized due to the difficulty in assessing it.6

In the past few decades, there have been a number of more empirical studies done

involving competitive balance in Major League Baseball. Balfour and Porter (1991)

compare the variation of winning percentages of teams before and after free agency in

hopes of finding whether the reserve clause is necessary in professional sports to achieve

competitive balance.7 Their study finds that during free agency the variance of winning

percentages was actually lower than before free agency. Therefore, Balfour and Porter

(1991) reject the hypothesis that “the dispersion of winning percentage is higher with free

agency” and conclude that it “is indeed lower (i.e. that divisional races are closer) during

the period of free agency. It appears free agency promotes competitive balance.”8

4

In response to previous articles looking at competitive balance in Major League

Baseball, Michael Butler (1995) uses a regression equation to look at the “standard

deviation of a team’s winning percentage, and the season-to-season correlation of team

winning percentages over the period 1946-92.”9 His aim is to pinpoint the actual cause of

the increase in competitive balance by looking at free agency, a narrowing of team

market sizes, and a compression of baseball talent.10 When he examines competitiveness

within the season (the standard deviation of a team’s winning percentage), he finds only

the rookie draft to be statistically significant.11 However in season-to-season data, all

three of the factors in Butler’s equation are statistically significant.12

Brad Humphreys (2002) applies a novel approach when looking at competitive

balance in baseball using the Competitive Balance Ratio (CBR). He argues that,

although many other measures of competitive balance (like the standard deviation of

yearly win-loss records) are fine to use for specific years, the CBR is a more proficient

indicator of competitive balance.13 This is because CBR is able to pick up variations in

balance over time.14 Humphreys (2002) uses a ratio of average team-specific variation in

won-loss ratio during a number of seasons (over) the average within-season variation in

won-loss percentage during the same period. The ratio is a number between zero and

one, with one being perfect competitive balance over time and zero being no competitive

balance over time.15 Humphreys (2002) also finds that variations in the CBR over time

offer a better explanation than previous models of the variation in the attendance for

Major League Baseball.16

Danielle Carbonneau and Paul Sommers (1997) use the Gini index, normally used

for income or wealth distributions, to look at competitive balance in baseball. Their

5

findings agree with the majority of other baseball studies in that “the absences of

restrictions in baseball such as the reserve clause (does not) have a disruptive effect on

the evenness of the competition in Major League Baseball.”17 Martin B. Schmidt (2001)

also uses the Gini index when looking at competitive balance in MLB. In contrast to a

majority of the other studies on baseball, which have examined factors like the reserve

clause, free agency, or the rookie draft, Schmidt (2001) chose to investigate the effect

expansion has on competitive balance in Major League Baseball. 18 He concludes that the

“rise in competitive balance began with the movement toward expansion.”19

In one of the few articles focusing on the National Football League, Kevin Grier

and Robert Tollison (1994) look specifically at the effect of the rookie draft on

competitive balance. They find “higher draft choices raise winning percentages

significantly over time”20 and concluded that the rookie draft in the National Football

League helps advocate competitive balance.21

Fort and Quirk (1995) examine the effect of revenue distribution, the reserve

clause, salary caps, and the rookie draft on competitive balance for different professional

sports leagues.22 They come to the conclusion that “an enforceable salary cap is the only

one of the cross-subsidization schemes currently in use that can be expected to

accomplish (financial viability for weak-drawing markets) while improving competitive

balance in a league.”23 As with Kesenne (2000), Fort and Quirk (1995) argue that the

problem with a salary cap is proper enforcement because teams are not allowed to

maximize revenues with a salary cap.24 This discrepancy would naturally cause

management to look for loopholes, like deferred payment, in the cap.25

6

David Richardson (2000) is the first to use the National Hockey League as a focus

for exploring competitive balance. He finds the long-term trend leaned towards more

competitive balance in the National Hockey League when looking at winning

percentages, and he finds no significant patterns for playoff games.26 When looking at

the impact the entry draft had on competitive balance in the NHL, Richardson (2000)

finds some support that the draft helps maintain competitive balance in the league.27

The most relevant journal article for this paper is Craig A. Depken’s (1999)

study on the competitiveness of Major League Baseball. He uses a deviation of the

Herfindahl-Hirschman Index (HHI), which has previously been used to find the market

share of a firm in an industry, to account for competitive balance. 28 If the HHI measures

1/N (where N is the number of firms), then it can be assumed the league is perfectly

competitive.29 On the other hand, if the HHI equals one, it can be assumed there is no

competitive balance in the league.30

In Depken’s (1999) article, however, he points out that the number of firms in the

industry can skew the actual HHI.31 In other words, as the number of firms in the market

grows, the HHI will decline. Since there are expansion waves, the HHI will tend to

decrease. To fix this problem, Depken (1999) uses the dHHI.32 He finds that the

variation in parity has been decreasing over time.33 Depken (1999) also looks at the

effects of free agency in baseball, finding statistical evidence that free agency has

reduced equality in the American League, while having no significance in the National

League.34

In the studies on competitive balance in professional sports, the findings of the

reviewed material are not consistent. The conflicting conclusions probably stem from the

7

lack of a universal system for gauging competitive balance. The literature has different

findings for all sports regarding free agency, the amateur draft, and expansion of the

league. The next section will describe the adaptation of Depken’s model, which this

study will employ to examine the NHL.

III. The Empirical Model and Data

As its primary model, this study uses the deviation of Herfindahl-Hirschman

Index of points (dHHIp) to look at the competitiveness of the National Hockey League.

dHHIp = f(HHIgf, HHIga, Amateur Draft, Racial Integration, European

Influence, Expansion, World Hockey Association, Free Agency, Special Expansion) (3.1)

The dependent variable, dHHIp, is the deviation of the Herfindahl-Hirschman

Index of team points from the ideal distribution of points in any given time period. 35

Equations 3.2-3.4 are mathematical representations of the dHHIp.

NHHIpdHHIp 1

−= , where (3.2)

( )∑=

=N

iiMSHHIp

1

2 , where (3.3)

POINTSLEAGUETOTAL

TEAMOFPOINTSMS ii = (3.4)

8

where N is the number of teams or firms in the industry. MSi is the market share of the ith

firm, where market share is defined as points gained by a teami divided by the total

league points.

Independent Variables

Goals Scored (HHIgf) and Goals Allowed(HHIga)

HHIgf is the Herfindahl-Hirschman Index for goals scored, or the distribution of

goals scored. Equations 3.5-3.6 are mathematical representations of the HHIgf.

( )∑=

=N

iiMSHHIgf

1

2 (3.5)

GOALSLEAGUETOTALTEAMBYSCOREDGOALS

MS ii = (3.6)

On the other hand, HHIga is the Herfindahl Hirschman Index for goals allowed, or the

distribution of goals allowed . Equations 3.7-3.8 are mathematical representations of the

HHIga.

( )∑=

=N

iiMSHHIga

1

2 (3.7)

GOALSLEAGUETOTALTEAMBYALLOWEDGOALS

MS ii = (3.8)

One would expect that the more concentrated goals scored become over time, the more

evenly distributed offensive talent in the league becomes, and the lower the HHIgf value

9

should be. It is expected, then, that as the HHIgf decreases, the dHHIp will become

smaller. In other words, the predicted sign of the coefficient for HHIgf is positive.

Similarly, one would expect that the more concentrated goals allowed becomes, the more

evenly distributed defensive talent is in the league, and as such will cause the HHIga

approach zero. Therefore, the predicted sign of the coefficient for HHIga is positive.

Amateur Draft (AD)

The dummy variable AD begins in 1963, when the inception of a rudimentary

form of the current Entry Draft was introduced.36 Years 1963 and after have a value of

one. Years before 1963 have a value of zero. The launch of the amateur draft in 1963

may have had a positive effect on competitive balance. Before the draft, NHL teams

could sponsor entire amateur teams and could sign any player from that team to a

contract.37 After the onset of the draft, teams were only allowed to pick individual

players, e.g. if the two best available players played on the same amateur team, two

different National Hockey League teams could draft these players (whereas in the old

system both players would have ended up playing for the same team). A testable

hypothesis is that the amateur draft would increase the level of competitive balance in the

National Hockey League. In other words, the expected sign of the coefficient for the

amateur draft is negative.

⎩⎨⎧

=≥

=otherwiseyearif

yearifAD

019631

(3.9)

10

Racial Integration (RI)

In 1958, the first non-white hockey player entered the National Hockey League.38

The dummy variable RI equals one for every year after 1957 and zero for 1957 and

before. With the establishment of a racially integrated league, a larger labor pool would

theoretically be available for teams. Although it cannot be assumed that all teams would

necessarily integrate at the same time or rate, it can be expected that integration by all

teams would improve the overall quality of play. As Depken (1999) notes in his work,

“if all teams improved at the same absolute rate, then the poor quality teams (those with

lower winning percentages) would improve at a greater percentage rate than the pre-

integration teams of high quality.”39 Integration can therefore be expected to improve

parity, or decrease the dHHIp. Consequently the predicted sign of the coefficient for

racial integration is negative.

⎩⎨⎧

=≥

=otherwiseyearif

yearifRI

019581

(3.10)

European Influence (EURO)

The European influence on the National Hockey League has been enormous in the

past few decades. The dummy variable EURO equals zero for every year through 1989,

and one for every year after. In the 1940’s and 1950’s there were only a handful of

European born and trained players in the National Hockey League. Although always

increasing slightly, the percentage of Europeans in the NHL stayed below 10 until 1990.

It was finally in 1990 that the percentage of Europeans in the NHL increased to over 10

percent. 31.6 percent of the National Hockey League is currently European and that

11

number continues to rise.40 The influx of Europeans has caused a major rise in the talent

pool, hopefully bringing more balance to the league (in form of more top-level players).

The anticipated sign of the coefficient for EURO is negative.

⎩⎨⎧

=≥

=otherwiseyearif

yearifEURO

019901

(3.11)

Expansion (EXPAN)

As Depken (1999) points out in his Major League Baseball paper on competitive

balance,

Although the parity measure dHHI arithmetically accounts for the expansion of a league, it does not control for any statistical influences of expansion on the league’s competitive balance. Expansion teams are staffed with players drafted from existing teams which are able to protect (supposedly high-quality) players from being drafted. Thus, one may suspect expansion teams to be at a competitive disadvantage.41

The disadvantage created by expansion may have more of an effect on parity than by just

calculating the dHHIp. In order to account for this, a dummy variable for expansion has

been added.42 In any year that a new NHL team starts play the dummy variable EXPAN

equals one; for all other years EXPAN is equal to zero. The predicted sign of the

coefficient for EXPAN is positive.

⎩⎨⎧

==

=otherwiseyearif

yearifEXPAN

02001,2000,1999,1994,1993,1992,1980,1975,1973,1971,19681

(3.12)

12

World Hockey Association (WHA)

In 1972-73, the World Hockey Association (WHA) was established. It was the

first and only direct competition in North America that the National Hockey League

faced in the 20th century. The league lasted through the 1978-79 season before folding.43

Drawing upon the reasoning from the dummy variables for Europeans and racial

integration, the WHA took away from the talent pool in the National Hockey League.

WHA equals one for seasons 1972-73 to 1978-79 and zero for all other seasons. It is

expected that the inception of the World Hockey Association will cause a decrease in

parity. Therefore, the predicted sign of the coefficient for the WHA variable is positive.

⎩⎨⎧

=−=

=otherwiseyearif

yearifWHA

07919731

(3.13)

Special Expansion (D68)

From 1942-43 until 1967-68, there were only six teams in the National Hockey

League.44 The league experienced its largest expansion ever during the 1967-68 season,

when six more teams were added to the league.45 Special consideration should be given

to this expansion, as the league doubled in size in one year. The dummy variable D68 is

equal to zero before the 1967-68 season and one thereafter. For reasons similar to the

expected effect of other expansionary years (in which the dummy variable EXPAN is

used), the expansion of 1967-1968 can be projected to have the same effect on parity. As

such, it is predicted that the major expansion in the 1967-68 season will cause an increase

in the dHHIp, which will make the league less competitive. Hence, the predicted sign of

the coefficient of D68 is positive.

13

⎩⎨⎧

=≥

=otherwiseyearif

yearifD

019681

68 (3.14)

In some regression equations, D68 integrated with HHIgf and HHIga. The D68

variable is multiplied by HHIgf and HHIga, respectively, to account for a gap that

occurred in the two independent variables when the league expanded in 1967-68.

Combining D68 with HHIgf and HHIga allows for changes in the slope of the

independent variables. Examples of the dHHIp with the integrated D68 variable are

given in equation 3.15.

)68*()68*(... 21210 DHHIgaDHHIgfHHIgaHHIgfdHHIp γγβββ +++++= (3.15)

Free Agency (FA)

The dummy variable FA controls for the system of free agency currently in use by

the National Hockey League. FA equals one for years after the CBA (see footnote 14)

was ratified, and zero otherwise. With increased restriction on movement, it is assumed

that teams will be able to retain their top end players more easily. Hence, it will be more

challenging for the better teams to lure talent away from the bottom place teams,

hopefully increasing competitive balance. Therefore, the predicted sign of the coefficient

for free agency is negative.

14

⎩⎨⎧

=≥

=otherwiseyearif

yearifFA

019951

(3.16)

IV. Results

Table 4.1 is a summary of the OLS regression results for various regression runs

based on model one. The name of the variable is followed by a brief definition of it. A

dash through the cell indicates a variable that has been left out of that particular

regression.

15

Table 4.1

Variable Definition Model 1

Equation 1 Equation 2 Equation 3 Equation 4

0.2307 0.0081 - -0.5294

(1.0464) (0.0448) - (-3.5633)*

-0.1831 - - -

(-1.4266) - - -

-1.1702 -0.9537 -0.1582 1.7547

(-5.5687)* (-5.4748)* (-1.1163) (5.0122)

1.1776 0.9769 1.1688 1.3047

(5.7103)* (5.6085)* (8.4518)* (10.6375)*

0.00001 -0.0004 -0.0004 -0.0001

(0.00176) (-0.2417) (-0.3434) (-0.1136)

-0.0018 -0.0006 -0.0011 0.0019

(-0.9876) (-0.3800) (-0.8155) (1.3703)

0.00003 -0.0009 -0.0005 -0.0003

(0.0140) (-0.4734) (-0.4396) (-0.2618)

0.0028 - 0.0017 -

(1.4593) - (1.3969) -

0.0014 0.0016 0.0011 0.0016

(1.0090) (1.2061) (1.0639) (1.7741)

0.0003 0.0003 -0.00001 0.0001

(0.2355) (0.3083) (-0.0140) (0.1387)

- - - 0.5097

- - - (8.494

-0.0001 -0.000003 0.0000003 0.000008

(-1.0360) (-0.0325) (0.3762) (0.1141)

- - - -2.18

- - - (-1.80

- - - -0.79- - - (-0.67

R-squared 0.7109 0.6953 0.9989 0.8861

Adjusted R-squared 0.6507 0.6475 0.9987 0.8600F-statistic 11.8051 14.5457 5789.080 33.9347

HHIga*D68

EXPAN

D68

YEAR

HHIgf*D68

allows changes in the slope of HHIga

C

dHHIp(-1)

HHIgf

HHIga

FA

AD

EURO

RI

W HA

Dummy for expansion

Dummy for expansion of 1967-1968

Time trend

Allows changes in the slope of HHIgf

Dummy for W orld Hockey Association

Constant

Lag variable for effects on parity

Concentration of offensive talent

Concentration of defensive talent

Dummy for free agency

Dummy for amateur draft

Dummy for European Influx

Dummy for Racial Integration

8)*

60

60)

9317)

16

Table 4.1 (continued)

Variable Definition Model 1

Equation 5 Equation 6 Equation 7

-0.5047 -0.5139 -0.5294

(-3.3626)* (-8.76580)* (-3.5633)*

-0.1114 - -

(-1.3848) - -

1.6262 1.7664 1.7547

(4.4880)* (5.3305)* (5.0123)*

1.3894 1.2987 1.3049

(10.1411)* (11.9200)* (10.6375)*

-0.0008 -0.0001 -0.0001

(-0.0691) (-0.0943) (-0.1136)

0.0017 0.0020 0.0019

(1.2164) (2.0354)* (1.3703)

-0.0003 -0.0003 -0.0003

(-0.2292) (-0.2383) (-0.2618)

- - -

- - -

0.0017 0.0016 0.0016

(1.8621) (1.8215) (1.7741)

0.0001 0.00009 0.0001

(0.1851) (0.1288) (0.1387)

0.5018 0.5109 0.5097

(8.3220)* (8.7530)* (8.4948)*

0.00000005 - 0.000008

(0.00005) - (0.1141)

-2.0905 -2.1912 -2.1860

(-1.7137) (-1.8300) (-1.8060)

-0.8442 -0.8035 -0.7993(-0.7046) (-0.6825) (-0.6717)

R-squared 0.8888 0.8860 0.8861

Adjusted R-squared 0.8598 0.8628 0.8600F-statistic 30.6485 38.0942 33.9347

HHIga

HHIgf

dHHIp(-1)

C

RI

EURO

AD

FA

YEAR

D68

EXPAN

WHA

Allows changes in the slope of HHIgf

Allows changes in the slope of HHIgaHHIga*D68

HHIgf*D68

Dummy for World Hockey Association

Dummy for expansion

Dummy for expansion of 1967-1968

Time Trend

Dummy for free agency

Dummy for amateur draft

Dummy for European Influx

Dummy for Racial Integration

Constant

Lag variable for effects on parity

Concentration of offensive talent

Concentration of defensive talent

Offensive Talent

In the first three equations, the results show the Herfindahl-Hirschman Index for

goals scored (HHIgf) has a negative impact on the model. In equations one and two,

HHIgf is significant at the 95% confidence level. The regression coefficient for equation

one is –1.1702 with a t-statistic of –5.5687. This result was puzzling, since the predicted

relationship between HHIgf and dHHIp is a positive one. However, once the structural

17

break due to the 1967-68 expansion is accounted for by multiplying HHIgf with the D68

variable, the coefficient value changes to positive. The HHIgf and D68 variables are

multiplied together to allow for changes in the slope of HHIgf. In the last four equations,

the HHIgf is significant at the 95% confidence level, and it exhibits a positive

relationship with dHHIp. These findings suggest that the concentration of offensive

talent in the National Hockey League has an effect on parity. However, HHIgf*D68 is

insignificant.

Defensive Talent

In all seven equations, the Herfindahl-Hirschman Index of goals allowed is

significant at the 95% confidence level. In addition, all seven coefficients possess a

positive relationship with the dHHIp. Using equation one as an example, the regression

coefficient for HHIga is 1.1776. Equation one also has a t-statistic of 5.7103. Similar

logic can be used for the other six model one equations in the same manner. These

findings imply that the defensive concentration of talent has an effect on parity in the

National Hockey League.

Player Mobility

The influence of free agency and the amateur draft on parity is also examined.

The current collective bargaining agreement deals a great amount with free agency and is

supposed to help alleviate some of the perceptions of the lack of competitive balance in

the league. This study has found free agency to be insignificant at the 95% confidence

level as a factor in determining the deviation from the ideal distribution of points

(dHHIp). Similar to free agency, the amateur draft is insignificant in six of seven

equations.

18

Talent Pool

Three dummy variables were added to help account for large or potentially large

changes in the overall talent pool teams have to draw from. Accounting for the infusion

of Europeans (EURO) into the National Hockey League is one of the talent pool dummy

variables. Six of the regressions have a negative regression coefficient, meaning that

since the number of Europeans in the National Hockey League has grown to over 10

percent, the dHHIp has decreased. Even though the coefficients are as predicted for the

EURO variable, all of them are insignificant. These findings suggest that the increased

participation by Europeans in the National Hockey League has not significantly affected

the equality level in the league.

A second dummy variable that accounts for a change in the talent pool is racial

integration (RI). Racial integration is used only in equation 1 and equation 3, and in both

cases their t-statistic is insignificant (at t-stat=1.4593 and t-stat=1.3969). The racial

integration variable is therefore dropped in the rest of the regressions. Compared to other

professional sports, hockey still has a very limited amount of integration.46 The

regression results for racial integration suggest that it has not had a major impact on

balance in the National Hockey League.

A dummy variable for the World Hockey Association (WHA) is the final variable

to account for a major change in the National Hockey League’s talent pool. For (WHA),

the regression coefficient matches the predicted sign, but again none of the equations

exhibit a significant t-statistic. Therefore, the WHA variable does not affect the parity in

the National Hockey League enough to be a noteworthy factor.

19

Number of Teams

Two dummy variables have been added to help account for the expansion in the

number of teams in the National Hockey League. The EXPAN variable is used in normal

years of expansion. 47 In six of the equations the regression coefficient for EXPAN

displays a positive relationship with the dependent variable, but they are all insignificant.

The insignificant t-statistics for EXPAN suggest that expansion is an insignificant factor

in determining parity in the National Hockey League.

The second variable used to account for the expansion of the league is D68.48 In

each of the four equations that included D68, all were significant at the 95 percent

confidence level. In addition, the predicted positive relationship between D68 and

dHHIp exists. In equation 5, for example, the regression coefficient is 0.5018 with a t-

statistic of 8.322. This suggests that the expansion of the 1967-68 season has helped

cause a decrease in the parity of the National Hockey League.

Non-game Related Dummy Variables

In equations one and five, the lag variable dHHIp(-1) is included in the

regressions. This is done to show that lag effects for parity have been taken into account.

Neither of the two t-statistics is found to be significant, however, so the lag is dropped

from the other equations. A variable for year (YEAR) is also present in six of seven

model one equations. This precaution is added to account for certain things affecting

competitive balance that are not represented in the model. YEAR proves to be

insignificant in all six equations that it is represented in.

20

In the interest of being thorough, a second set of regressions was done using the

standard deviation for points as the dependent variable instead of the Herfindahl-

Hirschman Index. A similar set of explanatory variables was employed, with the

difference being standard deviations for goals scored and allowed were substituted for the

HHI here as well. Results for the standard deviation model are presented in Table 4.2.

Table 4.2

Variable Definition Model 2

Equation 1 Equation 2 Equation 3 Equation 4

1.5877 - -177.0445 1.4171

(0.8653) - (-1.3858) (0.9332)

0.2737 0.2896 0.2764 0.2691

(5.3897)* (6.4740)* (5.4178)* (5.7515)*

0.2134 0.2298 0.2107 0.2151

(5.9830)* (8.3899)* (5.8959)* (6.5677)*

-0.0245 - -0.0015 -

(-0.2961) - (-0.0173) -

2.3419 2.8482 2.0695 2.0548

(2.1216)* (2.2976)* (1.4872) (1.5536)

1.1485 1.2008 0.7361 0.4497

(0.8045) (0.8523) (0.5056) (0.3597)

- -0.1847 -1.4527 -1.2879

- (-0.1625) (-1.0204) (-0.9655)

0.3595 0.5512 -0.5902 -

(0.3021) (0.4770) (-0.4297) -

0.8458 0.3640 0.9930 0.9620

(0.7738) (0.3672) (0.8881) (0.8993)

-0.1893 -0.2231 0.0413 0.0528

(-0.2375) (-0.2762) (0.0487) (0.0651)

-2.7365 -3.0250 -4.1592 -3.8596

(-2.1137)* (-2.4165)* (-2.4261)* (-2.6051)*

- - 0.0914 0.0773- - (1.3991) (1.4340)

R-squared 0.7885 0.7877 0.7973 0.7986

Adjusted R-squared 0.7497 0.7544 0.7497 0.7623F-statistic 20.3016 23.6533 16.8070 22.0279

DEVp(-1)

DEVga

DEVgf

C

RI

EURO

AD

FA

YEAR

D68

EXPAN

W HA Dummy for W HA

Dummy for expansion

Dummy for expansion of 1967-1968

Time trend

Dummy for free agency

Dummy for amateur draft

Dummy for European Influx

Dummy for Racial Integration

Constant

Concentration of offensive talent

Concentration of defensive talent

Lag variable for effects on parity

In stark contrast to the model one equations, two of the four model two equations

find free agency to be statistically significant at a 95 percent confidence level. Moreover,

model two finds that free agency actually decreases the parity in the league. Although

21

the decrease in parity was not predicted, it is not entirely shocking. There seems to be no

continuity in the findings of the studies that look at the effect of free agency in

professional sports.

V. Conclusions

After analyzing the regression equations pertaining to the deviation from the ideal

distribution of points for the Herfindahl-Hirschman Index, some conclusions can be

made. In observing the regression equations, it is very apparent that the three variables

most affecting the dHHIp are the HHIgf, HHIga, and D68. Offensive and defensive

talent distribution are expected to be major factors in determining competitive balance.

As National Hockey League player agent Ben Hankinson stated, “The two most

important general game aspects of hockey are offense and defense.”49 Hankinson’s

statement seems to point out the obvious, since few would argue that defense and offense

are the two most important facets of the game of hockey. It therefore seems logical that

the more even the distribution of offensive or defensive talent is, the lower the dHHIp

will be. Hence, by creating more evenly distributed offense and more evenly distributed

defense the league will create better parity.

It also seems logical that when the National Hockey League doubled in size (D68)

in 1967-68, this would cause a decrease in league parity. The new expansion teams

would not have same resources as the original teams. Doubling the number of teams at

such a high level would also factor in the talent pool drying up, meaning that these new

teams would not get the same caliber players as the existing teams.

With regards to the unexpected results, the free agency (FA) variable was

surprising. Free agency has been the focus of many studies looking at competitive

22

balance. As previously stated, conclusions on the effects of free agency with regard to

competitive balance have been inconsistent. Similar to Fort and Quirk’s (1995) finding

for Major League Baseball,50 this study has shown that the current system of free agency

does not have an impact on competitive balance in the NHL. This information could

potentially be a used by the National Hockey League Players’ Association as leverage for

fewer player restrictions when the current collective bargaining agreement expires at the

end of the 2003-04 season.

In order to help determine factors in competitive balance within the National

Hockey League, the following should be analyzed: the offensive concentration of talent,

the defensive concentration of talent, and major expansion. Although free agency was

found to be insignificant in this study using the Herfindahl-Hirschman Index, a possible

combination of measures of competitive balance could potentially make free agency a

significant factor in competitive balance.

The National Hockey League and the National Hockey League Players’

Association would both benefit greatly if they were able to make the league more

competitively balanced. It would not only help the overall product of the game but also

create more interest in National Hockey League cities that currently have perpetually

losing teams. In the end, a more balanced league would also help generate more revenue

for NHL teams and, in turn, its players.

This research helps distinguish the determinants of competitive balance in the

National Hockey League. This is the first competitive balance study for the National

Hockey League that uses the Herfindahl-Hirschman Index as its basis for determining

parity. This study will hopefully act as a stepping-stone for future studies of the

23

determinants of competitive balance in the National Hockey League. Armed with the

knowledge of knowing how to improve parity, the league and its players could potentially

offer the public a superior National Hockey League product.

1 Scott Taylor, “New CBA era is crucial,” The Hockey News, 21 February 2003, 7.

2 The Stanley Cup is awarded to the National Hockey League’s playoff champion on a

yearly basis. 3

4 Andrew Zimbalist, “Competitive Balance in Sports Leagues: An Introduction,” Journal of Sports Economics 3, no. 2 (May 2002): 111.

5 Allen Sanderson, quoted in Andrew Zimbalist, “Competitive Balance in Sports Leagues: An Introduction,” Journal of Sports Economics 3, no. 2 (May 2002): 119.

6 Ibid., 120.

7 Alan Balfour and Philip K. Porter, “The Reserve Clause in Professional Sports: Legality

and Effect on Competitive Balance,” Labor Law Journal 41, no. 1 (1991): 8-18. 8 Ibid., 16. 9 Michael Butler, “Competitive Balance in Major League Baseball,” American Economist 39,

no. 2 (1995): 46-53.

10 Ibid. 11 Ibid., 49.

12 Ibid.

13 Brad R. Humphreys, “Alternative Measures of Competitive Balance in Sports

Leagues,” Journal of Sports Economics 3, no. 2 (May 2002): 133-148. 14Ibid., 133. 15 Ibid., 147. 16 Ibid.

17 Ibid., 165. 18 Martin Schmidt, “Competition in Major League Baseball: the Impact Expansion,”

Applied Economics Letters 8, no. 1 (2001): 21-27.

19 Ibid., 26.

20 Ibid., 298.

24

21 Ibid. 22 Rodney Fort and James Quirk, “Cross-Subsidization, Incentives, and Outcomes in

Professional Team Sports Leagues,” Journal of Economic Literature 33, no. 3 (1995): 1265-1300.

23 Ibid., 1282.

24 Ibid., 1266

25 Ibid. 26 Ibid., 405. 27 Ibid. 28 David Richardson, “Pay, Performance, and Competitive Balance in the National

Hockey League,” Eastern Economic Journal 26, no. 4 (Fall 2000): 393-418. 29 Ibid., 208. 30 Ibid. 31 David R. Kamerschen and Nelson Lam, “A Survey of Measures of Market Power,”

Rivista Internazionale di Scienze Economiche e Commerciali 22 (1975): 1131-1156, quoted in Craig A. Depken. II, “Free-Agency and the Competitiveness of Major League Baseball,” Review of Industrial Organization 14 (1999): 205-217.

32 dHHI = HHI – 1/N, where N is the number of firms (or teams) in the industry. This, he says, measures the deviation from the ideal distribution of wins in any given time period.

33 Craig A. Depken II, “Free-Agency and the Competitiveness of Major League Baseball,” Review of Industrial Organization 14 (1999): 209.

34 Ibid., 215.

35 As referred to in Chapter II, the dHHIp is used (as opposed to the HHIp) because as a

measure of concentration, the HHI will always decrease as the number of firms in the market increase. It is therefore necessary to account for the influence of a change in the number of firms. As such, the dHHIp = HHI – 1/N where n is equal to the number of NHL teams in the league. 36

36 Prior to 1963, NHL teams acquired player by sponsoring amateur players or teams. In 1963 the amateur draft was introduced to replace this system. Teams could select any amateur player who would reach his 17th birthday between August 1st, 1963 and July 31st, 1964. Players would then remain on the team reserve list until their 18th birthday, when contract negotiations would begin. The name of the draft was changed to the NHL Entry Draft in 1979, and has retained the name since. Under the current draft rules, a player must be 18 years of age by September 15th of his draft year to be eligible.

37 An NHL team would pay an amateur team to become the amateur team’s sponsor. The NHL team would then have the right to sign any player they wanted to off of that particular team.

38 Willie O'Ree became the first black player in the history of the NHL when he played for the Boston Bruins on January 18, 1958.

25

39 Craig A. Depken II, “Free-Agency and the Competitiveness of Major League Baseball,”

Review of Industrial Organization 14 (1999): 212. 40 Steve Hirdt, “Do the Math,” ESPN The Magazine, 17 February 2003, 16. 41 Craig A. Depken II, “Free-Agency and the Competitiveness of Major League Baseball,”

Review of Industrial Organization 14 (1999): 212.

42 Other than the original expansion in 1967-68, there have been 9 years of expansion. In 1970-71 franchises were established in Buffalo and Vancouver. In 1972-1973 franchises in Atlanta (which moved to Calgary in 1980-1981) and New York (Islanders) were started. In 1974-1975 Washington and Kansas City (which moved to Colorado in 1976-1977 then to New Jersey in 1982-1983) were established. In 1991-1992 San Jose was established. In 1992-1993 franchises in Ottawa and Tampa Bay were started. In 1993-1994 Anaheim and Florida were established. In 1998-1999 the Nashville Predators entered the league. In 1999-2000 a franchise in Atlanta was started. The last expansion took place in 2000-2001, when franchises in Minnesota and Columbus were established.

43 Upon the folding of the WHA in 1978-79, four franchises moved to the National

Hockey League, which was considered another year of expansion. Edmonton, Winnipeg (who moved to Phoenix in the 1996-97 season), Quebec (who moved to Denver, Colorado in the 1995-96 season), and Hartford (who moved to North Carolina in the 1997-98 season) are all now members of the National Hockey League.

44 The ‘original six’ as they are commonly called, are the Boston Bruins, Detroit Red Wings, Montreal Canadians, Toronto Maple Leafs, New York Rangers, and Chicago Blackhawks.

45 Franchises were awarded for the 1967-68 season in Los Angeles, Philadelphia, Pittsburgh, Saint Louis, Minnesota (who moved to Dallas in 1993-94), and Oakland (which became defunct prior to the 1978-79 season, when they merged with the Minnesota franchise).

46 From “Pro Hockey and African Heritage, a Story,” available from http://www.aaregistry.com; Internet; accessed on March 23, 2003. There are around 29 minority hockey players in the National Hockey League (depending on the date as players can be transferred to minor league affiliates at any time). This constitutes roughly 3.9% of the total NHL population.

47 In this model, “normal” expansion is defined as years where only one, two, or three teams were added to the National Hockey League.

48 As opposed to normal expansion, for the 1967-1968 season the NHL doubled in size,

going from six to twelve teams. 49 Vice President of SPS Hockey, Ben Hankinson, phone interview by author, 10 January

2003.

50 Rodney Fort and James Quirk, “Cross-Subsidization, Incentives, and Outcomes in Professional Team Sports Leagues,” Journal of Economic Literature 33, no. 3 (1995): 1265-1300.