In recent years a wealth of literature has been offered examining the economics of professional team sports. Much of this work follows in the neoclassical tradition, employing the standard assumptions and focusing primarily on the impact of individual decision making. The purpose of this work is to show that the blinders imposed by the narrow focus of the neoclassical tradition on the issue of competitive imbalance may alter the conclusions that a broader view suggests.
Economists from the time of Adam Smith have trumpeted the virtues of competition. From the perspective of individual firms, though, profits are typically increased when competition is eliminated. However, in professional sports, the elimination of competition effectively removes the primary source of revenue. In the words of Walter Neale, "Pure monopoly is a disaster. [Former heavy-weight champion] Joe Louis would have had no one to fight and therefore no income" (1964, 2).
The analysis of Neale extends beyond the obvious case of the boxing champion to any professional sport. As noted by Mohamed El-Hodiri and James Quirk (1971, 1306), "[t]he essential economic fact concerning professional team sports is that gate receipts depend crucially on the uncertainty of outcome of the games played within the league. As the probability of either team winning approaches 1, gate receipts fall substantially. Consequently, every team has an economic motive for not becoming "too" superior in playing talent compared with other teams in the league."
Following the above-cited works, one could conclude that an important element of the economic success of a professional sport is the reduction of competitive imbalance. (1) Whenever one competitor reaches a level of dominance where uncertainty of outcome has been compromised, the demand for the output of this industry is expected to decline. Such a result has been noted empirically by Glenn Knowles, Keith Sherony, and Haupert (1992) and by Daniel Rascher (1999). Each of these authors noted that fan attendance in Major League Baseball is maximized when the probability of the home team winning is approximately 0.6. If the home team has a higher probability of finding success, one can expect fan attendance to decline. Consequently, given the importance of fan attendance to a league's financial success, leagues are expected to implement rules and institutions designed to address the relative strength of combatants on the field of play.
The focus of the literature exploring sports and competitive imbalance is often upon the variety of institutions individual leagues have enacted to improve the distribution of wins within the league. These include the reserve clause, the rookie draft, revenue sharing, and payroll caps. (2) The presumption behind the enactment of each of these institutions is that the level of competition is a factor within the reach of league policy.
Much of this literature focuses upon the investigation of competitive imbalance in a single sport, such as baseball or basketball. If one adopts a broader view, though, the picture one paints differs from much of this prior work. We will begin our "painting" with an analysis of competitive imbalance across a wide array of professional team sports. This will be followed by a discussion of the causes of competitive imbalance, a discussion that will lean heavily upon the works of evolutionary biologist Stephen Jay Gould. From our discussion of Gould we will turn to the specific case of professional basketball. This discussion will center upon the supposed "short supply of tall people," a factor that we believe drives the persistent level of competitive imbalance found in the NBA.
Measuring Competitive Imbalance
To explore the level of competitive imbalance across a variety of professional team sports we require a measure of the dispersion of wins in a league that allows intersport comparisons. (3) As noted, most studies have focused upon one sport. The exception to this trend lies in the work of Quirk and Rodney Fort (1997), who sought to compare the level of competitive imbalance in Major League Baseball, the National Football League, the National Basketball Association, and the National Hockey League. To make comparisons across sports, these authors turned to the earlier work of Roger Noll (1988) and Gerald Scully (1989). Both Noll and Scully argued that the dispersion of wins could be measured by comparing "the actual performance of a league to the performance that would have occurred if the league had the maximum degree of competitive balance in the sense that all teams were equal in playing strengths. The less the deviation of actual league performance from that of the ideal league, the greater is the degree of competitive balance" (Quirk and Fort 1997, 244).
The above intuition suggests the measure of competitive balance ([CB.sub.it]) reported in equation (1).
C[B.sub.it] = [delta][(wp).sup.actual.sub.it]/[delta][(wp).sup.ideal.sub.it] where [[delta].sup.ideal.sub.it] = [mu][(wp).sub.it]/[square root of (N)] (1)
Specifically, [delta][(wp).sub.it] is the standard deviation of winning percentages (or team points for leagues in which ties are possible) within league (i) in period (t). This is compared with the idealized standard deviation, which is defined by Quirk and Fort as the standard deviation of winning percentage if each team in a league has an equal probability of winning. The greater the actual standard deviation is relative to the ideal, the less balance exists within the professional sports league. The calculation of the idealized standard deviation employs both the mean winning percentage (4) in the league [mu][(wp).sub.it] and the total number of regular season games played (N). Quirk and Fort argued that the above measure allows for intersport comparisons because it controls for the differing schedule lengths of professional sports leagues.
Utilizing the Noll-Scully competitive balance measure, we examined a sample of seventeen professional sports leagues in the sports of soccer (or football), American football, hockey, baseball, and basketball. The specific leagues are listed in table 1.
For each of the listed leagues we began with the final regular season standings. We then examined the dispersion of regular season winning percentage, via equation (1), to ascertain the level of competitive balance that existed within the league. (5) With respect to most of the leagues listed in table 1, our sample …