As for Howard, “Tim can make some money in the U.S. I wouldn’t call it a big payday compared to other athletes,” says Paul Danforth, head of global sales at CAA Sports. Manish Tripathi, a marketing professor at Emory University who focuses on sports, advises Howard to “make deals as soon as possible. Once the World Cup ends, the enthusiasm will wane. Think Landon Donovan after he had the big goal against Algeria in the last World Cup.”
This is a statistics thing — at least as the numbers were crunched by the Emory (University) Sports Marketing Analytics team. Not sure if Atlanta, GA.-based Emory has the market cornered on expertise in hockey analytics. But they’re doing it.
And Chicago wound up in sixth place on Emory’s list of cities where hockey fans are most invested (think ticket sales) in their teams — right behind the aforementioned five Canadian cities.
Note: This is Part I of our study of NHL Fan Quality. This week we will be ranking NHL teams/fans on the following dimensions: Fan Equity, Social Media Equity, Fan Equity Growth, Price Elasticity, Win Elasticity, and Social Media based Personality. For more details on our measures of quality, please click here. For Part II, click here. For Part III, click here.
Our goal this week is to give NHL fans something to talk about during the offseason (and by talk about, we mean an opportunity to say awful things about us via Twitter and e-mail). We begin our review of NHL fan bases with our “Fan Equity” rankings. This ranking looks at fans’ willingness to financially support their teams using a model that controls for winning rates, population, income, and other factors. The basic idea is that we look at how teams over or under perform in terms of home ticket revenue to what similar (with respect to market potential and on-ice results) teams produce. More details on the revenue premium model we use to evaluate fan equity and an overview of the various rankings to be published this week may be found here and here respectively.
So where do the best NHL fan bases live? Sorry America, but Canada dominates these rankings. The top six teams in terms of fan equity are Toronto, Montreal, Edmonton, Winnipeg, Vancouver, and Chicago. The top US based teams are Chicago, Philadelphia, New York (Rangers), and Minnesota.
Really? Edmonton has a better fan base than Chicago? Pointy-headed academics should stick topics they know something about, and hockey is obviously not one of those topics. What drives these findings? Let us highlight some of the underlying factors that drive the results. Chicago won 46 games (107 points) and averaged over 22,000 fans last season.
This is great support for the Blackhawks, and this is why they crack the otherwise Canadian top six. So, why does Edmonton beat Chicago? Because Edmonton’s support is stronger once we control for market characteristics and team performance. Last year, Edmonton averaged 16,800 fans per home game while winning only 29 games (67 points). Both teams sell out, but Edmonton does it despite playing well below .500. In addition, the Edmonton market is less than 1/8 the size of the Chicago market. And despite these differences in success and market size, Edmonton is able to charge slightly higher average ticket prices.
The big winner in all this is the Toronto Maple Leafs. The Leafs achieve amazing pricing power and consistent sell-outs despite only average on-ice performance. Toronto is truly Hockeytown North America.
At the bottom of the rankings, we have Columbus, Tampa, Dallas, and Phoenix. This grouping suggests that the key to having a vibrant fan base is locating somewhere where people play hockey. We understand the desire to achieve a broad television footprint, but there is also something to locating where the fans live. For example, last year Dallas drew an average of 14,600 fans despite charging some of the lowest prices and winning 40 games. As a contrast, Winnipeg drew more fans despite winning fewer games. But the kicker is that Winnipeg is able to charge more than twice the average ticket price as Dallas. Also these results occur despite Dallas having a population of about 6.8 million compared around 700,000 in Winnipeg!
Mike Lewis & Manish Tripathi, Emory University 2014.
Over the past year, we have analyzed the impact of American Indian team names and mascots on fan attendance and team revenues in professional and college sports. In college basketball, for example, a number of programs, including those at the University of Illinois, Marquette and Stanford, have jettisoned such mascots. How have they fared financially? #
Who are the best fan bases in Major League Baseball? A quick Google search of “best MLB fan bases” produces more than a million results. Specific rankings are published by entities ranging from news organizations to ticket brokers. In general, these rankings are based more on subjective opinion than data and analysis. In contrast, we take a 100% data-driven approach.
That said, we readily acknowledge that fan base analysis is a complex topic. Our core metric is something we term “fan equity.” This metric is based created using a revenue-premium model of brand equity. This model is driven by the financial support shown by fans conditional on team performance and market characteristics. This approach has significant advantages in that it is based on spending behavior and not driven by short variations in winning. But, the revenue-premium approach is not perfect. Therefore, this year we will be publishing a number of rankings (and providing descriptions of the strengths and weaknesses of each approach). Click here for an overview of each method.
Today, we present three analyses of MLB fan bases. We begin with the fan equity / revenue-premium model (based on the last three years), a trend analysis of fan equity growth over the past 15 seasons, and an analysis of each team’s social media equity.
The winners in the fan equity analysis include the Red Sox, Yankees, Cubs, Phillies, Cardinals and Twins. The Red Sox and Yankees placing at the top of the list is simultaneously unsurprising and interesting. It is unsurprising because these are two of the league’s most prominent teams, and interesting because the two teams are bitter rivals. The intense competition between these two teams provides an added factor that may be lacking for teams like the Cubs or the Phillies. And yes, we do know that Cardinals fans love to beat the Cubs. (Click here for more details on our methodology for fan and social equity)
At the bottom of the list, we have teams in cities with great weather (or maybe summers that are too hot) and teams that are generally regarded as number two in their markets. The bottom five are the White Sox, Angels, A’s, Mets and Rays. As an aside, how about the “Portland A’s”?
We know the winners and the losers, but fan bases are not static entities. As teams win, lose or market themselves, their fan equity evolves. As a second analysis, we examined fan equity trends over the past 15 years. This analysis revealed that MLB’s high equity teams are tending to even greater levels of fan support. In this analysis, the Yankees finished first followed by the Red Sox, Cubs, Nats, Phillies, Dodgers and Giants. This list of teams is overwhelmingly concentrated in the largest markets. At the bottom of the list, we have teams like the Diamondbacks, Indians, Orioles, Padres and Rays.
The last analysis for today is something we term social media equity. This analysis looks at each team’s social media following (again controlling for market size and winning). Social media equity is important because it is unconstrained by stadium size, unaffected by a team’s pricing decisions and provides a measure of national following. It may also be a forward looking indicator if social media participants are younger than those fans who attend games.
The social media ranking is fairly different. While the Yankees are number one, the top five also includes the Padres, Brewers, Rangers and Pirates. Perhaps, the revenue-premium measure is picking up the economics of the big markets while the social media metric is best for identifying current interest. However, the bottom of the social media list is consistent with the bottom of the fan equity list with teams like the Mets, A’s and Angels.
In our next post, we will present analyses of fan base sensitivity to winning and pricing.
Mike Lewis & Manish Tripathi, Emory University 2014.
Evaluating sports brands, or any brands, is a complicated endeavor. The fundamental issue is that a brand is an intangible asset so the analyst must rely on indirect measures of the brand. Last year, we introduced a measure of fan loyalty that we termed “fan equity.” This measure was based on the degree to which fans were willing to support a franchise after controlling for factors such as population and winning percentage. We also explored a social media based metric that used a similar approach to evaluate a team’s success in building a social media footprint.
This summer, we are updating our analyses across the four major sports leagues (NFL, NBA, MLB, & NHL) and the two major college sports (football & basketball). We are also including several additional analyses that further illuminate fan support and brand equity. Shifting to multiple measures of “fan support” provides significant benefits. First, using multiple measures allows for a form of triangulation, since we expect that a great fan base will excel on most or all of the measures. The second benefit is that since each measure has some unique elements, the construction of multiple measures allows for a richer description of each fan base. Next, we provide basic descriptions and critiques of each of the metrics to be published.
Our baseline concept of fan quality is something we term fan equity. This is similar in spirit to “brand equity” but is adapted to focus specifically on the intensity of customer preference (rather than to consider market coverage or awareness). We calculate fan equity using a revenue-premium model. The basic approach is to develop a statistical model of team revenues based on team performance and market characteristics. We then compare the forecasted revenues from this model for each team to actual revenues. When teams actual revenues exceed predicted revenues, we take this as evidence of superior fan support.
The fan equity measure has some significant benefits. First, since it is calculated using revenues, it is based on actual fan spending decisions. In general, measures based on actual purchasing are preferred to survey based data. The other prime benefit is that a statistical model is used to control for factors such as market size, and short variations in team performance. This allows the measure to reflect true preference levels for a team rather than effects due to a team playing in a large market, or because a team is currently a winner. However, the fan equity measure also has a couple of potential issues. First, one of the distinguishing features of sports is capacity constraints. Measures of attendance or revenues may therefore underestimate true consumer demand simply because we do not observe demand above stadium capacity. The second issue relates to owner pricing decisions. An implicit assumption in the revenue-premium model is that teams are revenue maximizers.
Social Media Equity
Our social media equity metric is similar in spirit to our fan equity measure, but rather than focus on revenues we use social community size as the key dependent measure. The calculation of social media equity involves a statistical model that predicts social media community size as a function of market characteristics and current season performance. Social media equity is then based on a comparison of actual versus predicted social media following.
The social media equity metric provides two key advantages relative to the revenue-premium metric. Since social media following is not constrained by stadium size and does not require fans to make a financial sacrifice, this metric provides 1) a measure of unconstrained demand and 2) avoids assumptions about owner’s pricing decisions. On the negative side, the social media equity does not differentiate between passive and engaged fans. Following of a team on Facebook or Twitter requires a minimal, one time effort.
Trend Analysis (Fan Equity Growth)
A key issue in evaluating fan or brand equity is the time horizon used in the analysis. The methods described above produce an estimate of “equity” for each season. The dilemma is in determining how many years should be used to construct rankings. The shorter the time horizon used, the more likely the results are to be biased by random fluctuations or one-time events. On the other hand, using a long time horizon is problematic because fan equity is likely to evolve over time. This year, we present an analysis of each team’s fan equity trajectory.
Price Elasticity and Win Elasticity
This year we are adding analyses that look at the sensitivity of attendance to winning and price at the team-level. This is accomplished by estimating a model of attendance (demand) as a function of various factors such as price, population, and winning rates. The key thing about this model specification is that we include team level dummy variables and interactions between the team dummies and the focal variables of winning and price.
The win elasticity provides a measure of the importance of quality in driving demand. For example, if the statistical model finds that a team’s demand is unrelated to winning rate, then the implication is that fans have so much of a preference for the team that winning and losing don’t matter. For a weaker team (brand) the model would produce a strong relationship between demand and winning.
This benefit of this measure is that the results come directly from data. A possible issue with this analysis is that the results may be driven by omitted variables. For example, prior to conducting the analysis we might speculate that demand for the Chicago Cubs might only be slightly related to the team’s winning percentage. This speculation is based on the fact that the Cubs never seem to win but always seem to have a loyal following. Our finding would, however, need to be evaluated with care since the “Cub” effect is perfectly correlated with a “Wrigleyville Neighborhood” effect.
Social Media Based Personality
This year we are adding another new analysis that uses social media (Twitter) data to evaluate the personality of different fan bases. The foundation for this analysis is information on “sentiment.” Sentiment is basically a measure of the tone of the conversation about a team. To understand fan personality, we examine how Twitter sentiment varies over time. We do comparisons of how much sentiment varies across teams. This tells us if some fan bases are even-keeled while other are more volatile. We can also look at whether some teams tend have higher highs or lower lows. These analyses are based on the distribution of sentiment scores over a multiple year period.
Twitter based sentiment has both positives and negatives. On the positive side, Twitter conversations are useful because they represent the unfiltered opinions of fans. Fans are free to be as happy or as distraught as they want to be. The availability of sentiment over time is also useful as it allows for the capture of how opinion changes over time. On the downside, Twitter sentiment scores are only as good as the algorithm used to evaluate each Tweet. Twitter data may also be a bit biased towards the opinions of younger fans.
Mike Lewis & Manish Tripathi, Emory University 2014.
The continuing debate about whether high-level collegiate basketball and football players should be paid seems to be moving in the direction of these athletes receiving some form of compensation above their scholarship. In the last year we have seen steps towards forming a college athletes’ union, and increased rhetoric from the Big Five conferences about the need to start providing increased compensation to athletes. (Of course, a cynic might view the statements by the Big Five conferences as justification for gaining increased control over lucrative television dollars)
At one extreme, we have folks that advocate for no additional payment beyond the athletic scholarship. An increasingly popular viewpoint is that athletes should be provided an additional living wage type stipend. At the other extreme, we have individuals that advocate the use of a professional sports-type model. For example, Roger Noll used a 50-50 revenue split (similar to that used in the NBA) to value player contributions as part of the Ed O’Bannon lawsuit.
A complicating factor in this debate is that the structure of consumer demand is possibly very different between college and professional sports. Our specific concern is that the affinity between graduates and their colleges may mean that colleges start with more natural and stronger fan bases. As an example, consider the difference between the University of Florida and the city of Jacksonville. A UF graduate is by definition a member of the “Gator Nation”. The graduate belongs to a community of graduates that may tend to use the university’s football team as a natural focal or bonding point. In contrast, a resident of Jacksonville is supposed to root for the Jaguars merely because of where they live. Of course, this is a simplification, but hopefully our point is clear.
One way to test the preceding conjecture regarding natural and stronger fan bases is to analyze the relationship between team winning percentage and team revenues for both college and professional sports. If the relationship between revenues and wins is the same for the professionals and colleges, then it makes more sense to view the college game as essentially a professional league. If there is no relationship between revenues and wins at the college level, then player quality doesn’t matter (and consequently players probably shouldn’t be paid).
In honor of the upcoming NCAA Men’s Basketball Tournament, we modeled the relationship between revenues and win percentage for the NBA and Division 1 Men’s Basketball programs using data from the last decade. The models for each league had similar inputs or specifications. The dependent variable in both models was revenue. In the case of the NCAA, we used the revenue attributed to men’s basketball in each school’s annual Title IX filing. For the NBA, we used an estimate of home ticket revenue: average ticket price multiplied by home attendance. In the case of the NBA, the home box office revenue is a proxy for overall revenues (the correlation between our home revenue estimate and Forbes total revenue estimates is about 0.8). The explanatory variables for each equation included current season winning percentage, past playoff (or NCAA Tournament appearances), past championships, arena capacity, metro area population (or student population), and team level fixed effects (also conference fixed effects for colleges). Finally, we also used log transforms on winning percentage and revenues so that the coefficients could be interpreted as elasticities. An elasticity tells us how much one variable (revenue) changes as a function of another variable (wins percentage).
Our results suggest that NBA revenues are twice as sensitive as college basketball revenues to winning rates. In the case of the NBA, the elasticity of revenues to win percentage was 0.20 and the R-squared for the model was 0.83. At the college level, the elasticity was 0.097 and the R-squared was 0.90. The college model also included an interaction term between winning percentage and membership in a major conference (ACC, SEC, Big 12, Big Ten, Big East and Pac 12).
Where does this leave us in the debate of how much to pay players? We will defer on providing an exact percentage because doing so would require several more analyses and even more assumptions. But, it does appear that the two extreme points of view that we mentioned earlier are misguided. The college players do generate significant revenues, but their degree of responsibility for revenues is far less than the professionals.
One interpretation of our model is that it speaks to the different roles of brand equity in sports revenues. At the pro level, revenues are twice as sensitive to winning rates as at the collegiate level. Our feeling is that college revenues are driven more by the permanent nature of the fan base, and by the brand equity created over time. We have made an earlier argument along these lines, that while Ed O’Bannon should be able to profit from the use of his image, the revenues that would be generated would have as much to do with Kareem Abdul Jabber and Bill Walton as they have to do with Ed O’Bannon. So what should be done? We would like to see a three-way split of revenue. The colleges get their share, the current players get a piece, but the players that built the college brands should also get something. As professors that have seen the difficulties of obtaining an education while playing a major sport, we would like to see some type of program that at a minimum provides educational grants for past players. Furthermore, given that we seem to learn more about the health consequences of big-time football each day, it also seems reasonable to establish a trust fund for future player health issues.
Mike Lewis & Manish Tripathi, Emory University, 2014.
We started the Emory Sports Marketing Analytics blog back in March of last year. Our goal was to bring analytics to the world of sports business. To put a finishing touch on 2013, we are going to present our rankings of the best and worst sports fans by city. These rankings are based on our revenue premium model of fan equity and our analyses of social media equity.
For our rankings, we have divided cities into categories based on how many of the four major sports (NFL, NBA, MLB, & NHL) have franchises representing the city. This categorization does introduce a bit of oddness since Los Angeles becomes a “three-sport” city. Another tough issue is how to treat teams like the Packers. Is Green Bay a one-sport city or is Milwaukee as three-sport city (we decided that we would treat Milwaukee as a three-sport city)?
Today we reveal our rankings of the four-sport cities, and a summary of the best and worst markets in the other categories (one, two, & three-sports cities). Before the actual rankings, a couple of clarifying comments are in order. The key to our rankings is that we are looking at fan support after controlling for short term variations in team quality and market characteristics. Basically we create statistical models of revenues as a function of quality measures like winning percentage and market potential factors like population. This allows our results to speak how much support fans provide as if market size and winning rates were equal.
The number one team on our four-sport city list is Boston; and it wasn’t even all that close. All of the Boston teams have impressive fan followings. The Red Sox ranked 1st in terms of fan equity and 1st in social equity. The Celtics finished 3rd in the NBA in both our fan and social media equity rankings. The Patriots rank 2nd in fan equity and 3rd in social media equity in the NFL. The Bruins rank relatively low in fan equity (perhaps because they could price higher), but very high in social media equity. Number two on the list is Philadelphia. The Eagles, Phillies and Flyers are all very strong fan bases. The Sixers are weak within the NBA, but the three other sports carry Philly to a second place finish.
The city in third place is likely going to generate Twitter complaints about how clueless we are, and how academics should stay away from sports. We rank the Twin Cities of Minneapolis and Saint Paul as having the third most supportive fans among the four-sport cities. Minneapolis/Saint Paul show great support of the Twins and solid support for the Vikings. The Wild also do surprisingly well in the NHL.
How could Minnesota finish in front of New York and Chicago? It’s because these cities don’t do a great job in terms of supporting all their teams. For example, The Brooklyn Nets perform poorly when market size is considered and the White Sox have very poor support on all metrics. We can hardly wait for the semi-literate Twitter attacks to commence.
At the bottom of the list we have Phoenix. We should note that the Suns perform well and finish 7th in terms of fan equity in the NBA. But beyond that, Phoenix sports are a disaster. In terms of fan equity, the Diamondbacks finish 26th in MLB, the Cardinals 30th in the NFL and the Coyotes 28th in the NHL. As we have learned over the past year, it seems that weather and tradition are what creates a strong fan culture. Perhaps the Phoenix teams overall are too new, and the weather is too warm.
Our other winners and losers are given below with linked infographics that summarize raw data and final rankings.
Mike Lewis & Manish Tripathi, Emory University 2014.
The NFL is America’s favorite professional sports league, but which of its teams has the most loyal and supportive fan base? This is not a straightforward question. A ranking based on attendance would be skewed toward teams that play in more populated metropolitan areas, and a ranking based on profitability or revenues would be biased in favor of teams that are currently enjoying more on-field success.
In our series of fan base analyses across leagues, we adjust for these complicating factors using a revenue premium model of fan equity. The key idea is that we look at team box office revenues relative to team on-field success, market population, stadium capacity, median income and other factors. The first step in our procedure involves the creation of a statistical model that predicts box office revenue as a function of the aforementioned variables. We then compare actual revenues to the revenues predicted by the model. Teams with relatively stronger fan support will have revenues that exceed the predicted values, and teams that under perform have relatively less supportive fan bases. We provide more details on the method here and here.
The top fan base was the Dallas Cowboys. Professor Lewis grew up a Steelers fan in the 1970s so this was a bit of a painful result. Professor Tripathi grew up as a Redskins fan, and is terribly disturbed by the results of the study. What are keys to the Cowboys’ ability to create a passionate and supportive fan base? We think it’s a long legacy of success, a football mad Texas culture and a state of the art stadium. Over the last three seasons (the time period used to calculate fan equity) the Cowboys have played sub .500 football but generated above capacity attendance (at least according to ESPN).
In positions two and three we have the New England Patriots and the New York Jets. New England has an all-around strong fan base, while the Jets are somewhat similar to the Cowboys in that they draw consistently well, regardless of the on-field product. In fourth and fifth place we have the New Orleans Saints and the New York Giants. The Saints are a more recent success story, but the team’s new success combined with limited professional sports options in New Orleans has created a very strong fan base. Two New York teams in the top five is an interesting result when viewed in relation to our college football fan base analyses. New York is (no surprise here) a pro sports town. As an aside, we will be interested to see how much value the Big Ten gains from acquiring a foothold in the NYC market starting in 2014.
At the more unfortunate end of the scale we have a bottom five of Detroit, Tampa Bay, Arizona, Atlanta and Oakland. Detroit, of course, suffers from a relative lack of on-field success and a struggling local economy. But we should note that our method does explicitly control for these factors. It may well be a matter of the Wolverines & Spartans winning the battle for fans against the Lions. Similarly, teams like Atlanta and Tampa Bay may suffer from being located in SEC territory.
Mike Lewis & Manish Tripathi, Emory University 2013.
Our city ranking series continues today with a look at cities with three professional sports teams. These markets tend to be a bit on the smaller side, but many have significant sports histories. We also fully admit that we struggled a bit with how to classify several of these markets. For example, what is the city of Milwaukee? Is Milwaukee a two sport town with NBA and MLB franchises or should we include the Packers and call it a three sport town? Having lived in Chicago, it always seemed like all the Wisconsin teams should be lumped together. Toronto was another decision. Until now, we have only considered US cities, and avoided one professional team Canadian markets such as Calgary and Edmonton. So before the complaints begin, please realize that we have made some assumptions about markets.
The table on the right provides our ranking of the eight markets with three professional teams. According to the data, St. Louis is the best of these markets. Professor Lewis used to live in St. Louis and the first place ranking was a bit of a surprise to him. While the Cardinals have an amazing following, Lewis’ sense was that the Rams and Blues only had average fan bases. The Cardinals do have an exceptional fan base ranking 4th in MLB in both fan equity and social media equity. The Blues have an above average fan base ranking 14th in the NHL. The Rams do struggle with a fan equity ranking of 22th in the NFL. So it really is the Cardinals that elevate St. Louis to the top of the list.
Following St. Louis, we have Toronto ranked 2nd, Milwaukee 3rd and Pittsburgh 4th. Frankly, we would have predicted Pittsburgh would rank higher. The issue is that our fan equity metric is based on a “revenue premium” model, and the Steelers don’t seem to price nearly as high as they could. But, this was a close competition. Toronto has the best NHL fan base and the Packers and Steelers have devoted followings.
At the bottom of the list we have Tampa Bay. The Lightning ranked 18th in NHL fan equity. The Bucs ranked 29th in the NFL and Rays ranked 22nd in MLB. On a side note, the Atlanta ranking should put to rest any complaints about the Braves relocating. The Braves have delivered phenomenal quality and have only gained an average fan following. Add in a history that includes players like Hank Aaron and Dale Murphy, and you would expect that the Braves would have a monster following. Our expectation is that the move to Cobb County and the building of a mixed use development around the stadium should lead to a stronger fan base in the near future.
Mike Lewis & Manish Tripathi, Emory University 2013.