Social Media Equity: The NBA

A challenge in evaluating fan bases in professional and college sports is how to adjust for capacity constraints.  Unlike most consumer categories, teams have a limited number of seats to sell.  One way to get around this issue is to look at team revenues.  But this approach also has some strong implicit assumptions in that we must assume that teams are trying to price in a manner that maximizes revenue.

The world of social media provides an opportunity to look at fan base support without worrying about capacity or pricing issues.  To look at NBA teams “social media equity” we collected follows and likes from Twitter and Facebook.  We then created a statistical model that predicts these measures of social media engagement as a function of market size, tweeting activity and team performance for this past season and for the season before that.  We then compared each team’s actual follows and likes against the model predictions.  This method attempts to control for short term fluctuations in winning percentage and market differences.

The top team in terms of social media equity is the LA Lakers.  The Lakers crush the competition both in terms of raw numbers and in our model.  In second place, we have the Miami Heat.  This one is interesting, and we suspect that the Heat results may be a bit misleading.  While the Heat does very well currently it is not possible to separate out how much of the social media equity is driven by the team versus by LeBron.  This is something to watch as we collect more social media data over the next few years.  In third place, we have another non-surprising result in the Celtics.

It is the next three teams that are surprising as Golden State ranks 5th, New Orleans ranks 6th, and Charlotte ranks 4th.  The case of Charlotte illustrates the value of our model based approach.  In absolute terms, Charlotte performs relatively poorly in terms of social media metrics.  However, when we adjust for team performance and market size, the team does fairly well.  This indicates that the Charlotte market has fairly resilient fans, and likely speaks to the potential of the market if a consistent winning team is developed.

At the bottom of the list, the most surprising result is the New York Knicks’ 27th place finish.  This is doubly interesting because when we ranked fan bases in terms of “economic” support, the Knicks were number one.  What these two results imply is that the Knicks’ fan base is economically valuable but not engaged (at least in terms of social media).  The Knicks play in the largest market but have only about 20% of the social media activity of the Lakers.

There were a couple of other interesting findings from this study.  First, the number of Twitter followers was uncorrelated with the number of times a team tweeted.  This suggests that fans follow based purely on their feelings for the teams, rather than the entertainment of following an interesting Tweeter.  We also found a very high correlation between the two social media platforms as the social media equity estimates across the two platforms exceeded 0.91. However, when we looked at the correlation between the social media equity and the economics based fan equity the correlation was just 0.3.  We will leave this disconnect between social media and revenues for a future post.

Mike Lewis & Manish Tripathi, Emory University, 2013.

Converting High School Talent into NBA Draft Picks: Ranking the ACC

The NBA Draft can be a time for college basketball fans to cheer about the “success” of their basketball program.  Kentucky, Duke, North Carolina, and Kansas fans can boast about the number of alums currently in the NBA.  This year, ESPN is taking that discussion one step farther by describing the quality of NBA players produced, and ranking the “NBA Pedigree” of colleges.

Our take is a bit different as we will examine the process of taking high school talent and converting it into NBA draft picks. In other words, we want to understand how efficient are colleges at transforming their available high school talent into NBA draft picks? Today, we launch our NBA draft series by ranking the schools in the ACC based on their ability to convert talent into draft picks.

The initial approach is fairly simple.  Each year, (almost) every basketball program has an incoming freshman class.  The players in the class have been evaluated by several national recruiting/ranking companies (e.g. Rivals, Scout, etc…).  In theory, these evaluations provide a measure of the player’s talent or quality*.  Each year, we also observe which players get drafted by the NBA.  Thus, we can measure conversion rates over time for each college.  Conversion rates may be indicative of the school’s ability to coach-up talent, to identify talent, or to invest in players.  These rates may also depend on the talent composition of all of the players on the team.  This last factor is particularly important from a recruiting standpoint.  Should players flock to places that other highly ranked players have selected?  Should they look for places where they have a higher probability of getting on the court quickly? Next week we will present a statistical analysis (logistic regression) that includes multiple factors (quality of other recruits, team winning rates, tournament success, investment in the basketball program, etc…). But for now we will just present simple statistics related to school’s ability to produce output (NBA draft picks) as a function of input (quality of recruits).

Our first set of rankings is for the ACC.  At the top of the list we have Boston College and Georgia Tech.  Boston College has done a good job of converting low-ranked talent into NBA picks (in this time period they had two three-star players and a non-rated player drafted).  Georgia Tech, on the other hand, has converted all of its five-star recruits, and several of its four-star recruits.  A result that may at first glance seem surprising is the placement of UNC and Duke.  However, upon reflection these results make a good deal of sense.  When players choose these “blue blood” programs they face stiff competition for playing time from both current and future teammates.

Here are some questions you probably have about our methodology:

What time period does this represent?

We examined recruiting classes from 2002 to 2011 (this represents the year of graduation from high school).  While the chart above ranks the ACC, we compiled data for over 300 Division 1 colleges (over 12,000 players).

How did you compute the conversion rate?

The conversion rate for each school is defined as (Sum of draft picks for the 2002-2011 recruiting classes)/(Weighted Recruiting Talent).  Weighted Recruiting Talent is determined by summing the recruiting “points” for each class.  These “points” are computed by weighting each recruit by the overall population average probability of being drafted for recruits at that corresponding talent level.  We are using ratings data from Rivals.com.  The weights for each “type” of recruit were 0.51 for each five star recruit, 0.13 for each four star, 0.03 for each three star, 0.008 for each two star, and 0.004 for each not ranked.  

Second-round picks often don’t even make the team.  What if you only considered first round picks?

We have also computed the rates using first round picks only, please see the table below.

NEXT: RANKING THE BIG 10

*We can already hear our friends at Duke explaining how players are rated more highly by services just because they are being recruited by Duke.  We acknowledge that it is very difficult to get a true measure of a high school player’s ability.  However, we also believe that over the last ten years, given all of the media exposure for high school athletes, this problem has attenuated.

Mike Lewis & Manish Tripathi, Emory University 2013.

College Basketball Recruiting and the Best Fan Bases

For Big Ten rankings and a note on our methodology please click here.

For PAC-12 rankings please click here.

For ACC rankings please click here.

For Big 12 rankings please click here.

For SEC rankings please click here.

For Big East rankings please click here.

For the Best of the Rest click here.

While the college basketball season is far away, there are a number of interesting college basketball stories this summer.  Our plan for June is to focus on college basketball issues.  Our main focus will be on topics related to recruiting.

Our starting point, and the subject of today’s post, is a study of college basketball’s best fan bases.  We posted this originally as we launched the site (so very few folks have seen the results).  Fan bases relate to recruiting because they indicate enduring support from the fan base.  We will follow this analysis of fan base quality with more commentary related to the Ed O’Bannon case, and then data on which schools produce the most NBA players after adjusting for recruiting success.

For our College Basketball Fan Equity analysis we use a “Revenue Premium” method.  The intuition of this approach is that fan base quality is reflected in a school’s men’s basketball revenue relative to the team’s performance. To accomplish our analysis, we use a statistical model that predicts team revenues as a function of the team’s performance, as measured by winning rates and post season success.  The key insight is that when a team achieves revenues that greatly exceed what would be expected based on team performance, it is an indication of significant brand equity. The analysis therefore avoids bandwagon effects and gets at the core loyal fan bases.

 

The table provides the top ten overall schools.  Number one on the list also happens to be the most recent NCAA champion Louisville (note these ranking were computed prior to this past tournament).  Louisville scores so well because they have a great tradition, and play in a decent sized metropolitan area that does not have any pro teams.  The list does include many of the usual suspects such as Arizona, Duke and North Carolina.  How does this relate to recruiting?  Simple, strong fan bases equate to strong and high profile programs.  If an athlete wants exposure and opportunities to play on a big stage, then it makes sense to seek out a high brand equity program.  Of course, if the goal is to make it to the NBA, then this may or may not be the best strategy (we will get to this point as the NBA draft approaches).

One possible point of controversy is that Arkansas rates higher than Kentucky.  The key is that while both Arkansas and Kentucky receive outstanding support, Arkansas’ support occurs despite less on-court success.  The other possible interpretation is that Kentucky tends to underprice and may collect less revenues than possible.

Mike Lewis & Manish Tripathi, Emory University 2013

LeBron Saves the Heat (and the NBA?)

We have seen a number of articles and social media activity speculating about the NBA’s desire to have Miami advance to the NBA finals.  It’s a nervous time for the NBA because the other 3 teams in the conference finals are from “small” markets.  In some ways, the success of small market teams is a welcome outcome as all professional leagues tend to be nervous about large market dominance resulting in competitive imbalance, but the overwhelming short-term concern is obviously about how this situation will impact the television ratings for the final.

We have seen speculation about the impact of having small market teams such as Indiana, San Antonio and Memphis in the finals, but not a great deal of analysis.  To fill this gap, we have developed several statistical models that forecast TV ratings as a function of the characteristics of the two teams who are participating.  As a starting point we collected data on market population, winning percentage, home attendance, pricing, road attendance, and the number of All-star game starters and reserves for each team participating in the NBA finals over the last several years.  In this case, we have only a limited number of data points, so the key to the analysis is in identifying which of the variables are the best predictors.

We tried a great many combinations of the previously listed variables and found that the two best predictors were the sum of the two participants’ home box office revenues and the number of All-star game starters participating in the seriesA model with these two variables yielded an R-squared value of 0.53, and both explanatory variables had t-stats with p values of less than .05.

Our speculation is that combined home revenue captures the market size and fan intensity of the two teams.  This metric seems to be much more effective than population simply because not all large market teams are equivalent draws.  For example, in LA, the Lakers are a more powerful brand than the Clippers, and in New York, the Knicks have dominated the Nets (let’s say the New Jersey Nets to avoid any additional angst from the Brooklyn contingent).

We also found that All-star starters was the right metric rather than total All-stars.  In hindsight, this is also an intuitive finding.  The NBA has long been known as a “Star” driven league.  In fact, if you look back in history, the Michael Jordan era had amazingly high ratings compared to the last decade.  Based on the data, it appears that finals ratings are driven by the number of extremely high profile players.

In the tables below, we report actual ratings for the last six finals and our model’s predictions for the possible NBA Finals matchups.  As expected, the most promising matchup is Miami versus San Antonio.  What are really notable are the predicted ratings for the least promising matchup.  We predict that an Indiana – Memphis matchup would result in an epic failure in terms of ratings.

As a reality check for our prediction, consider the most recent finals matchup of small market teams.  In 2007, San Antonio defeated Cleveland, and the finals achieved a 6.2 rating.  While this number is much higher than our prediction, the San Antonio and Cleveland series had a significant advantage relative to an Indiana-Memphis matchup.  The difference was that the Cleveland and San Antonio series featured LeBron James and a Tim Duncan still close to his prime.  These types of stars would be sorely lacking in a Memphis – Indiana series.  This is, however, not a criticism of the Grizzlies or the Pacers, but more an indictment of how the NBA markets itself.  The NBA’s practice of emphasizing a few marquis players means that ratings will suffer when teams without these high brand-equity players make the finals.

The other problem for the NBA is that fans also understand the league’s dilemma.  This means that a meaningful percentage of fans believe that the NBA clearly prefers a series that features Miami.  This is a significant problem if fans believe that marketing considerations influence outcomes.

Mike Lewis & Manish Tripathi, Emory University 2013.

Debunking a Debunking: Our Response to the NetsDaily

If the true purpose of the Emory Sports Marketing Analytics blog is to generate conversation, then our NBA brand equity study has been a success.  The reality is that we are a couple of sports fans that happen to be university professors.  I (Mike) spend most of my time developing dynamic models that predict customer behavior over time.  This blog is an effort to combine our jobs and hobbies.  An example of this is a paper on competitive balance in MLB.

Our blog is intended to present more quick hitting analyses of current issues in the world of sports.  With these studies we rely on publicly available data, and we tend to use relatively straight-forward statistical methods.  We really don’t begin with any agenda; we just let the numbers speak.

In the case of the NBA fan study, the numbers spoke and then the NetsDaily answered.  Given our love of debate, we can’t help but answer back.  Though all kidding aside, to the Nets/NetsDaily guys: we really do like what you guys have done.  You are obviously an exciting franchise with a lot of great marketing.

In what follows we reprint the NetsDaily notes in blue and then give our comments in bold:

Final Note: That Emory University study

We’re not going to devote a whole lot of effort to debunking the silly Emory College attempt at defining passionate fans by analytic means.  It found that the Nets were the worst home fans in the NBA and the Knicks the best.

Okay, we get the idea, the NetsDaily is not happy with the results.  A couple of things come to mind.  One, Emory is a University.  Second, debunking is probably the wrong way to start a discussion.  With almost any study like ours, there will need to be assumptions made.  As we noted in our original post,we are using a revenue premium brand equity model.  One could definitely argue that passion and revenue are different concepts.  It is probably more useful to understand what the study is saying than to claim it is wrong.

We would just like to point out some serious flaws in the study. The original study was so devoid of data that the authors were asked to provide some, which they did in a self-congratulatory addendum.

We are trying to strike a balance in the blog.  We could report all statistical models, but we are trying to keep things interesting so we emphasize intuition and report the interesting findings.  We are more than happy to share additional details.  And as academics, self-congratulation is probably our best hope for some positive feedback.

The authors note that key data they used to derive their conclusions is something called “home revenue.” They attempt to estimate “home revenue,” which is a finite, known but proprietary figure not available to them. Shouldn’t they note that, explain its relevance?

“The analysis begins with a model of box office revenue based on variables that correspond to market potential (capacity and market population), team quality (winning percentage) and entertainment value (number of all stars, payroll). The insight or theory that drives the analysis is that this model can be used to predict the revenue that is due to quality and market potential. Any difference between this predicted value and actual value is due to ‘fan loyalty’.”

So the reality is that they don’t have the finite, known but proprietary information that is the core of the theory so project it based on other data, including things as spurious as number of all-Stars, but ignore other data that might be important, like say MERCHANDISE SALES. Need we go there? The Nets now rank fourth in NBA merchandise sales. In the first several months after the merchandise was introduced, they ranked first.

The NetsDaily does not seem to properly understand the analysis.  We use a really simple estimate of home box office revenue using the popular Fan Cost Index and attendance reported by ESPN.  Is this the ideal way to determine home revenue?  Of course not!  Is it a reasonable way given that teams are private and do not report detailed financials?  Reasonable might even be too strong.  In fact, let’s say that it is a crude way to compute box office revenues. (Point for the Nets)

We then use this revenue measure as a dependent variable in a regression model that uses the previously mentioned factors.  We are not estimating revenue in terms of things like number of all-stars, we are developing a model that explains revenues by these factors that indicate team quality, market size and entertainment value (fans come out to see all-stars).  We then compare the difference between the predicted and the (crude) estimate of actual revenue.

The idea is to look at attendance AFTER controlling for how well the team did.  Does Miami selling out mean much given the quality of the team on the court?  Our goal is to really get at the true core support for a team.

On comparing the attendance between the Knicks and Nets, they use gross numbers of attendance.

“The teams share the largest population metropolitan areas but the Knicks achieve a 10.7% advantage in terms of attendance DESPITE charging much greater prices. It is this greater pricing power that pushes the two teams to opposite ends of the ranking.”

Suppose instead of gross numbers, they used capacity percentage. The original analysis appears to rely on ESPN attendance percentages, that is, the percentage of arena capacity sold out on average each game. We say “appears” because the original article notes, ” A quick look at attendance data from ESPN shows that the Trail Blazers regularly exceed capacity for entire seasons.” Two points: the Trail Blazers attendance last season was 95.4 percent, which did not exceed capacity (or it would have been in excess of 100 percent.)

This is an example of why it’s probably better to ask questions and have a discussion than to go on the attack.  We control for stadium capacity in the revenue prediction model to account for differences in stadium capacity.

But they do make a good point here.  When we talk about “best” fans there really is no obvious metric.  We choose revenue, the Nets suggest capacity utilization.  Also, the Trail Blazers attendance percentage was 102.6 percent of capacity in 2012, 102.7 percent in 2011, and 102.6 percent in 2010.  We believe that this is very consistent with our wording.

However, using ESPN data presents problems. It is inaccurate regarding the Nets. ESPN uses an NBA capacity of 18,000 for Barclays Center. That was the original number for NBA games. As the arena was completed, capacity was reduced to 17,732 (apparently to accommodate loge seating added late in construction.) The number can be found on the Nets website. So the actual percentage of seats sold this season is 96.9 percent, not 94.9. That would put the Nets at tenth (not 16th) in the NBA, just ahead of … drum roll … the Knicks at 96.3 percent and the Blazers.

Again, some good points are raised here by the NetsDaily.  As statisticians, we love to have very accurate data.  In reality, data almost always contains some noise or error.  The Nets would have a valid complaint if the publicly available data was somehow consistently biased against the Nets.  Does Team Marketing Report systematically underestimate the Nets’ prices, and does ESPN systematically underestimate the Nets’ attendance?  We don’t know.  If so, we apologize.

We leave it to the readers to decide whether our measure which includes quantity and prices is preferred to straight capacity utilization.

But let’s put aside the methodology and data and look at the final product, which suggests below average work.  Is there ANYONE in the NBA who believes that fan loyalty to the Dallas Mavericks, Phoenix Suns, and Orlando Magic is on the rise … or that their fans had greater loyalty than the teams that follow them in the Emory rankings: the Miami Heat and San Antonio Spurs??? You want an example of analytics gone wild???

The comment above seems to be a common misinterpretation.  The example of the Orlando Magic is really what is at the core of our study.  We are not saying that the Orlando Magic has more fan support than the Miami Heat this season.  We are saying that after you control for the difference in the quality of the teams it appears that the Orlando Magic have a more devoted fan base.  Over the past season, the Magic had an average home attendance of 17,595, while only winning 24% of their games.  The key question (and what we use the statistical models to get at) is what would Miami have drawn if they didn’t win 80% of their games and have 3 all-stars in the lineup?

If we were petty people we would also point out that the ESPN attendance figures for last season report that the Magic drew 721,414 fans while the Nets operating in the largest metropolitan area and winning about 60% of their games drew 704,702.  We usually aren’t petty, but they did call our study “silly”, and called us “C students” (Manish says thanks for the passing grade) on Twitter.

The study is also a rare, rare instance where Barry Baum, chief communications officer of the Nets, and Norman Oder, the leading critic and chronicler of Atlantic Yards find common ground.

Says Baum, after reading the original article, “With all due respect to Emory University, that is a seriously flawed study.”

Thank you Mr. Baum for getting the school name correct.

Says Oder, after reviewing the article and supporting data, “The Knicks’ attendance edge is magnified by an arena with greater capacity, and the willingness of Knicks fans to pay more. [It] has less to do with passion than a longstanding monopoly position in a large market.”

This is also a good point, and one that we acknowledged.  It seems likely that the Knicks may benefit from locational advantages that translate into greater pricing power.

If there is a continuing dispute on this, we suggest a review by Nate Silver, the New York Times stats guru … and Nets fan. We are sure he will get to the bottom of it.

We would of course very happy to extend the discussion.  We were in fact surprised when we ran the numbers, and found the Nets on the bottom.  And remember we did point out that the Nets were rapidly improving.

Mike Lewis and Manish Tripathi, Emory University 2013.

Follow Up to the NBA Fan Equity Study & Why We Do This

Our post about which NBA teams have the best fan bases has generated a good deal of response.  This response has included insightful questions about the models and variables.  We wanted to use this post to provide some more detail and examples.

Before we get into the NBA study, it is probably useful to give folks a bit more background on what we are trying to accomplish.  Our unofficial mission is to use marketing concepts and statistical methods to understand the behavior of players, teams, and leagues.  We are both sports fans and academics, so our goal is to go beyond opinion, and use data to generate new insights into the world of sports.

When we start an analysis like the NBA fan equity study we really don’t start with an agenda (though Professor Lewis does acknowledge a personal bias against Duke Basketball).  We start with a bunch of data and some concepts (theory) that guide the way we approach the analysis.  In the case of the fan equity study, our guiding theory is that team revenue is based on the loyalty of fans, the size of the team’s market, the quality of the product and the entertainment value of the team.

The analysis begins with a model of box office revenue based on variables that correspond to market potential (capacity and market population), team quality (winning percentage) and entertainment value (number of all stars, payroll).  The insight or theory that drives the analysis is that this model can be used to predict the revenue that is due to quality and market potential.  Any difference between this predicted value and actual value is due to “fan loyalty.”

In their responses to us, readers tended to ask about a few specific teams.  For instance, there was a great deal of interest in comparisons between the Knicks and the Nets.  The table below shows several differences between the two teams that are drivers of the differential fan equity.  The teams share the largest population metropolitan areas but the Knicks achieve a 10.7% advantage in terms of attendance DESPITE charging much greater prices.  It is this greater pricing power that pushes the two teams to opposite ends of the ranking.

Another illuminating comparison could be made between Orlando and Golden State.  Given the excitement surrounding the Warriors the casual fan would likely assume that Golden State enjoyed a stronger fan base.  However, when we look at the numbers we see that Orlando generates almost the same attendance (and charges slightly higher prices) while operating in a market that is half the size and winning fewer than half as many games.  Our analytics driven approach accounts for these differences.  It also makes sense when you consider that Orlando fans provide about the same amount of box office revenue as GSW fans, while the team draws from a smaller market and wins only 24% of their games.

This last point is really the key to our analysis.  As a further example, while Miami is currently a great revenue driving team, we need to realize that their fans are attracted to a team that won 80% of their regular season games and has three all- stars and the likely MVP in the lineup.  The true test of fan loyalty is what happens when a team slumps.  This is why teams like Orlando and Dallas do so well in our rankings.

Mike Lewis & Manish Tripathi, Emory 2013.

Does Seattle deserve an NBA franchise? Yes!

Yesterday, the NBA owners voted to keep the Sacramento Kings from being sold to a group that would have brought the franchise to Seattle.  Yesterday, we also posted an analysis of fan base quality for the NBA.  We reported results for each Team’s “Fan equity” for the past season (and the change from 2012).  We found that the franchises with the best fan bases included the Knicks, Bulls, Celtics and Trail Blazers.  We also found that the worst fan bases were those of the Nets, Hawks and Pistons.

While we focused on this most recent season, our methodology can also be applied to previous seasons.  This morning we have run the numbers for seasons from 2002 to 2006 to see how the Sonics fan base compared to other cities (we excluded the last two years to avoid having the numbers biased by a negative fan reaction due to the planned move to Oklahoma City).

We found that the Seattle market ranked 20th over this time period.  While this is not a great performance it does place the Sonics far from the bottom.  The Sonics fan base was more supportive than fan bases in Denver, Minnesota, Milwaukee, Atlanta, Detroit, Philadelphia and the Clipper side of LA.

The conclusion seems to be that while Seattle isn’t a truly great NBA market it is at least a decent one.  And one that does have something of a history.  Now that the opportunity to grab the Kings is gone, the next question should be what about expansion.  This recent article in Forbes describes an analysis of markets such as Louisville and Seattle as candidates for expansion.  While we don’t have access to the underlying data, we would like to point out that Louisville already has a very strong basketball market.

Mike Lewis & Manish Tripathi, Emory University 2013

 

Which NBA Team has the Best Home Fans? And Who has the Worst? Hint: It’s New York!

Note: We have received a lot of responses to this study.  For more about the specifics of the study and answers to common questions, click here.

One of the core concepts we work with at Emory Sports Marketing Analytics is brand equity.  Brand equity is basically the advantage that a firm has over its competitors due to their brand being better known and having more loyal followers.  In the realm of sports, brand equity can be thought of as capturing the size and intensity of a team’s fan base.  As the NBA playoffs proceed to their climax this year, we decided to examine the brand equity of all 30 NBA franchises (for a similar analysis of NCAA basketball click here).

A quick Google search shows several other rankings of fan base quality (links below).  These rankings are largely based on consumer surveys or opinion.  In contrast, our method uses statistical models of team revenue results to measure which fan base best votes with their wallets.  Basically, what we do is estimate a statistical model of team box office revenues as a function of the team’s winning percentage, team payroll, market population, arena capacity, number of all-stars, and other factors that capture the quality of the team’s product and revenue potential in a given year.

Home Revenue = f(win%, Payroll, Market Population, etc…)

We then compare team’s actual home revenue with predictions from our model to discern teams that out- or under-perform.*  We call this quantity “Fan Equity.”

Fan Equity = Reported Home Revenue – Predicted Home Revenue

For the 2013 regular season, we find that the New York Knicks have the top ranked fan base.  The Knicks are followed by Chicago, Boston, Portland and Dallas.  Of these, Portland is probably the most interesting case.  A quick look at attendance data from ESPN shows that the Trail Blazers regularly exceed capacity for entire seasons.  Portland is a small market, but a market with passionate and supportive fans.  Portland also likely does well because they are the only “pro” game in town.

At the other extreme, we find that the Brooklyn Nets, the Atlanta Hawks and the Detroit Pistons are the greatest underperformers.  To reiterate, our method basically suggests that these teams should be making more revenues based on their markets and on-court performance.  The Brooklyn Nets are a fascinating example, given the hype that surrounded the move to Brooklyn, and Jay-Zs “ownership.”  While the Nets finished dead last in our rankings, if we look at year over year changes we do see signs of life.  In terms of year-to-year changes, the Nets had the 5th greatest improvement from 2012 to 2013 (even though their overall ranking did not change).

On a local level, we find that the Atlanta Hawks have very little fan support.  This comes as little surprise to folks from the South (aka SEC territory).  Atlanta as a city has the reputation of a place where everyone is from somewhere else.  This is probably a critical factor as a great deal of fan loyalty is built as fans grow up watching the home team.

*As with any analysis of this type, it is possible to quibble with assumptions.  For example, our method does not consider television revenues or that some cities have a greater corporate presence.

Links to other rankings of fan base quality:

Ranker.com on Teams with the Best Crowds (Golden State #1)

Forbes Study of Loyal Fans (Miami #1)

Bleacher Report on Best Fan Bases (Chicago #1)

Mike Lewis & Manish Tripathi, Emory University 2013.