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

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

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.

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

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

Table 5.1

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

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

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

Figure 5.1

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

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

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

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

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

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

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

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

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

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

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

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

Table 5.3

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

Table 5.4

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?

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

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

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

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

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

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

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

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

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

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

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

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%

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 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

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

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

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

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.”

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

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