Competitive Balance

1. The Economics of Sports FIFTH EDITION Chapter 5 Competitive Balance Michael A. Leeds | Peter von Allmen

2. Competitive Balance • The term means different things to different people • Close competition every year, with the difference between the best and worst teams being relatively small • Regular turnover in the winner of the league’s championship • More generally, it means degree of parity within a league

3. Learning Objectives • Understand why owners and fans care about competitive balance • Be able to use and interpret the different measures of competitive balance • Describe and compare the tools that leagues use to promote competitive balance and the limitations of those tools.

4. 5.1 Desire for Competitive Balance • Fans and owners alike have a conflicted relationship with competitive balance • On any given day, seeing one’s team win is preferable to seeing it lose • But an uninterrupted string of wins is dull

5. The Fans’ Perspective • A game with an uncertain outcome is much more exciting than a foregone conclusion • Table 5.1 shows that from 1950 to 1958 attendance for both the Yankees and the entire American League either stagnated or fell because of Yankees dominance • Evidence suggests that in many sports, fans prefer a game where the home team has a 60-70% chance of winning

6. Table 5.1

7. The Owners’ Perspective • Competitive balance matters to owners because it matters to fans • Leagues adopt policies to promote competitive balance because they enhance fan demand • Leagues restrict team behavior if it leads to teams that are too strong or too weak (see Table 5.1) • Balance is hard to achieve if some teams maximize wins while others maximize profits

8. Effect of Market Size • There is considerable debate over the impact of market size on competitive balance • There are three primary sources of disagreement • How to measure of success • During playoffs or regular season? • How to characterize market size • Market size has become more important with the advent of broadcasting

9. Effect of Market Size (cont.) • The third point of disagreement is how to measure the impact of policies, such as revenue sharing • Profit-maximizing leagues do not want total balance – they want big-market teams to win more • At minimum, more populous locations will win the league championship more frequently • Figure 5.1 shows an additional win is more valuable in a larger market, so the optimum number of wins is greater

10. Figure 5.1

11. The Effect of Diminishing Returns • The impact of another unit of a variable input (when added to a fixed input) eventually falls • This effect limits the desire of teams to stockpile – and pay – star players • And promotes competitive balance • Drew Brees has limited value to a team that has Tom Brady • Brees adds little to wins, attendance, or revenue • The added cost exceeds the added benefit • Other teams can use him more effectively

12. Is Perfect Balance Profit Maximizing? • Winning has a bigger impact in a larger market • It adds more to gate, media, and venue revenue • MRwins higher in big cities • Profit-maximizing leagues and competitive balance may be incompatible • Big cities will win more unless MCwins is also higher MR, MC MRlarge MRsmall MC Wins

13. A History of Competitive Balance • Yankee dominance of MLB is not new • Appeared in 15 World Series between 1947 and 1964 • The LA Lakers and San Antonio Spurs won 9 of 13 NBA championships between 1999 and 2011 • The Montreal Canadiens won 10 Stanley Cups in the NHL between 1965 and 1979 • They were succeeded by NY Islander and Edmonton Oiler dynasties in the 1980s • The NFL is more balanced, but the Browns and Lions have never been in a Super Bowl

14. Competitive Balance in Soccer from 2000-01 to 2011-12 • In England’s Premier League • Manchester United, Chelsea, and Arsenal have won 11 times • In Germany’s Bundesliga • Bayern Munich and Borussia Dortmund have won 9 times • In Italy’s Serie A • AC Milan, Inter Milan, and Juventus have won 11 times • In Spain’s La Liga • FC Barcelona and Real Madrid have won 10 times

15. 5.2 Measuring Competitive Balance • Within-Season Balance (Variation) • Compares teams within a season—across a league • A low dispersion of team winning percentages means that the teams are evenly matched • Between-Season Balance (Variation) • Compares winners (champions) across time • Some leagues have the same champions year after year • Regular turnover is preferred

16. Within-Season Variation (1) • We could use the standard deviation of winning percentage • The standard deviation gives the dispersion of performance by teams • It is the square root of the average squared deviation from the mean • See formula on p. 159 • The mean performance is always .5 as there are a winner and a loser in every game

17. Application • In 2011, the standard deviation in the American League was 0.067 • The typical winning percentage varies by 0.067 from the mean • The standard deviation in the National League was 0.054, about three-fourths that of the American League. • The National Leagues was more balanced

18. Within-Season Variation (cont.) • We cannot compare the standard deviation across leagues or across seasons with a different number of games • As the number of matches rises, winning percentages cluster around the mean • If teams are evenly matched, then the probability of success in any game is close to .5 • We can apply the binomial distribution • In a short season, a lucky team can have all wins and an unlucky team no wins • The league can look unbalanced in a short season

19. Within-Season Variation (cont.) • We need a better measure • We compare a league’s standard deviation to the standard deviation that would result if teams were evenly matched • The “ideal” standard deviation occurs when each team has a 50% chance of winning a given game • The better measure is the ratio of the actual to the ideal standard deviation • R = sA/sI

20. Computing Within-Season Balance • The ratio of actual to ideal standard deviation • N = # Teams • G = # Games • WPCTi,t =Winning percentage of team i at time t

21. Interpreting the Ratio • The ratio R gives a standardized measure • Actual and ideal standard deviation fall as G rises • We can now compare leagues and seasons with a different number of games • The formula appears on p. 161 • As a rule, R > 1 • If R = 1, the league is completely balanced • Outcomes are effectively randomly determined • As R rises, balance worsens

22. How Do Leagues Compare? • English Premier League was the most balanced in 2011-2012 • The NFL, NHL and MLB have similar balance • NBA is by far the least balanced • This has been true in most years • See Table 5.3 for the actual statistics

23. Table 5.3

24. Between-Season Balance • We can use the standard deviation of each team’s winning percentage • Unlike the within-season measure, there is no “ideal” measure • It is unclear what is a good or bad value • We can use the frequency of championships • It is hard to compare this across leagues • See Table 5.4

25. Table 5.4

26. The Herfindahl-Hirschman Index • HHI measures the concentration of championships • In industrial organization, it measures monopoly power • Let ci= #championships by team i • T = #teams; N = #Years • If HHI=1, one team always wins • If HHI=1/N and N>T, complete competitive balance • If HHI=1/T and N<T, complete competitive balance • See p. 164 for computations; What if the league had 10 teams?

27. Applying the HHI to Sports • See Table 5.4 • the HHI for the Premier League is far greater than for any other league • the HHI for the NBA is also large • the HHI for the NHL, NFL, and MLB are substantially smaller • the HHI for the NHL is the smallest, indicating that the league was most balanced in the first decade of the 21st century

28. Illustrating Competitive Imbalance • The Lorenz Curve measures inequality in a population • It is typically used to measure income inequality • We use it to measure inequality in winning • Line up NBA teams by wins in 2010-2011 (p. 164) • 1230 games were played, so population = 1230 • The 3 weakest teams (the lowest decile) won 58 games • 58 games correspond to 4.7 % of 1230 • Thus, the bottom 10% accounted for 4.7% of wins • The next 10% accounted for 5.8% and so on • The top 10% accounted for 14.7% of wins • Figure 5.2 presents the results

29. The Lorenz Curve for the NBA • Red line shows perfect balance • Adding 10% more teams adds 10% more wins • Blue line shows reality • Bottom 10% wins less than 10% • Sags below red line • As we add better teams, blue curve catches up • At 100% of teams, we account for 100% of wins • The farther the blue line sags, the greater the inequality

30. 5.3 Altering Competitive Balance • All the major North American sports leagues have developed policies to promote competitive balance • Revenue sharing • Salary caps and luxury taxes • Reverse-order draft • Players claim that the policies merely depress overall salaries • This section explores the policies’ effect on competitive balance

31. The Invariance Principle • Free agency allows a player to go to the team that offers the best employment terms • Players sell their services to the highest bidder • Owners claim that free agency is incompatible with competitive balance • Economic theory suggests otherwise • Markets direct resources to the most productive uses • Property rights do not affect the flow of resources • They affect only who gets paid for them • Simon Rottenberg (1956) first applied the principle to sports

32. How the Invariance Theorem Works • In 2012 Albert Pujols was more valuable to the LA Angels than to the St. Louis Cardinals in terms of revenue • With free agency • The Angels paid Pujols to move to LA • Without free agency • The Angels would pay the Cardinals for the “rights” to Pujols • Pujols moves in both cases—the use of the resource is unaffected • The only difference is who gets paid • The reserve clause did not prevent player movement • In 1920 Red Sox sold Babe Ruth to Yankees • Connie Mack twice sold off championship teams in Philadelphia

33. With Transaction Costs… • The Invariance principle breaks down if there are large costs to making transactions • Benefits that do not exceed transaction costs are not realized • Transactions costs could have prevented the Angels from pursuing Pujols

34. Revenue Sharing • MLB, NBA, NFL, and NHL share network TV revenue equally • NFL extensively shares all sources of revenue • Teams keep only 60% of home gate revenue • Huge TV package dwarfs other sources • MLB shares 31% of local revenue (minus “expenses”) • Central (non-local) revenue also goes disproportionately to teams in 15 smallest markets • They will have to spend this revenue on players

35. Revenue Sharing (cont.) • The NBA is expected to vastly increase sharing • Teams will share up to 50% of local revenue (minus “expenses”) • The NHL transfers income to teams • In bottom 15 smallest media markets • If the market has a base population under 2 million

36. Revenue Sharing (cont.) • Revenue sharing equalizes revenue across teams • Goal is to reduce incentive of big teams to pursue talent • This will not work if • Sharing shifts down MR of a win for all teams equally – big-market teams still have higher MR • Teams that receive revenue do not spend their added revenue on talent • Some teams might pursue profit over wins

37. Salary Caps • NBA, NFL, and NHL all have salary caps (not MLB) • Salary caps are neither a salary limit nor a cap • They set a band on salaries: both upper and lower limits to payrolls (not individual salaries) • Take qualifying revenue (QR) of league • Not all revenue “qualifies” • Definition varies from league to league • Players get a defined share of the QR • Divide total player share by # of teams • Add & subtract a fudge factor (5-20%) to get the bounds

38. NFL Example • Players receive • 55% of national broadcast revenue • 45% of NFL Ventures (merchandising) revenue • 40% of aggregate local revenues • Each team must spend at least 89% of the cap • Overall, players must receive at least 95%

39. Hard Caps and Soft Caps • The NFL has a hard cap • Sets a firm limit on salaries without exceptions • The NBA has a soft cap with many exceptions • Mid-level exception • Team can sign 1 player to the league average salary • Even if it is over the limit • Rookie exception • Team can sign a rookie to his first contract • Even if it is over the limit • Larry Bird exception • Named for former Celtics great who was its first beneficiary • Team can re-sign a player who is already on its roster • Even if it is over the limit

40. The NBA and Soft Caps • All the exceptions have undermined the cap • This has led to further rules • The NBA now caps individual salaries as well • The NBA has a luxury tax to prevent teams from abusing the exceptions • This has nothing to do with luxury boxes • Teams pay a tax that increases for every $5 million over the cap • A team $15 million over the cap must pay a $37.5 million tax

41. MLB’s Luxury Tax • Tax starts at 17.5% for first-time offenders • Threshold is $178 million in 2011-2013 • Rises to $189 million in 2014 • Tax rises with the number of abuses • NY Yankees have paid the tax every year

42. The Reverse-Order Entry Draft • Ideally, it levels out talent over time • Teams select new players according to their order of finish in the previous season • Weakest teams get the first choice of new talent • Strongest teams get the last choice

43. What Was the Point of the Draft? • Did teams just want to keep salaries low? • Was is a cynical move by weak teams? • Eagles’ owner Bert Bell proposed the draft • The Eagles happened to have the NFL’s worst record • Was it an idealistic move? • The NY Giants & Chicago Bears agreed to the draft • They were the dominant teams & had the most to lose • Tim Mara (Giants owner): “People come to see competition…. We could give [it to] them only if the teams had some sort of equality.”

44. Weaknesses of the Draft • It can lead to “tanking” • Teams lose intentionally to improve draft position • That is why the NBA has a draft “lottery” • Under a lottery • The weakest team has the best chance of choosing first • But it might not • It works only if teams can identify talent

45. Identifying Talent: Moneyball • Billy Beane, the Oakland A’s general manager, found underrated players • He saw that teams • Overrated physical skills • Underrated on-base percentage • Using different criteria in player selection kept his small market team competitive • Other teams eventually caught on • A’s have fallen on hard times as a result