Social Media Equity in Major League Baseball: Boston Wins, Cubs Fans Lose and Southern California Baseball is Social Media Challenged

A new way to assess the health of a brand is to examine its social media following.  Social media metrics have an appeal because consumers can show their interests without regard to price.  Of course, this is also the downside of social media, since it’s difficult to tell how consumer interest can be converted to revenue.  In the case of professional sports, social media metrics are of special importance because team revenues are often constrained by finite stadium capacities.  Another equity measurement challenge in sports is that teams are tied to specific metropolitan areas.  If we don’t control for differences in market size, we would almost always find that the New York teams have the best brands and teams in markets like Kansas City and Milwaukee would appear to have weak brands.

To examine social media equity in major league baseball, we developed a model that predicts social media following (in this case the sum of Facebook likes and Twitter followers) as a function of market size, Twitter activity as measured by tweets, and variables that control for short-term variation in winning rates.  We use this statistical model to predict social media following, and then compare our prediction to the team’s actual social media presence.

The number one ranked team in terms of our social media equity measure is the Boston Red Sox.  Boston is followed by the Cubs, Yankees, Cardinals and Houston.  The one surprise in this top 5 is the Astros. Conventional wisdom would suggest that the Astros don’t belong, but the key to our method is that we are controlling for team performance.  The data says that the Astros have a much greater social media following than we would expect for a team that has had back to back 100 game loss seasons.

That the Cubs having a great fan following on social media is not a surprise but this result continues to strengthen the case that Cubs fans are the most abused in baseball.  The fans consistently provide great support on every dimension, and the Cubs’ management continues to fail to produce a decent team.  In an earlier study we even found that the Cubs fan support is basically unrelated to the team’s performance.  We are not sure who should be the most embarrassed: the front office for their amazing lack of ability to build a constant winner or the fans for their relentless support.

The losers on the list are predictable with one exception.  While the Angels and Diamondbacks being near the bottom are unsurprising, the Dodgers at third from the bottom are a shocker.  In a previous study based on economic loyalty, the Dodgers were at the top of the list.  The Dodgers have great fan support as evidenced by the league leading attendance.  But when it comes to social media, the Dodgers struggle for some reason.  For example, while the Dodgers play in the second largest market they have similar social media presences as teams such as the Rangers and Cardinals.  Perhaps it is a Southern California issue, since the Angels finished dead last in our ranking.

Mike Lewis & Manish Tripathi, Emory University 2013.

Red Wings & Bruins Top NHL Social Media Equity Rankings

Last week, we published our ranking of NHL Team Fan Equity.  We have coined the term “Fan Equity” as a sports specific version of customer equity.  This metric is driven by “economic” measures of loyalty.  But, we do realize that a fan base also includes factors such as passion and engagement that may be (to some extent) overlooked in an economically driven ranking.

As a second look at fan base quality in the NHL, we use an approach that removes factors such as non-revenue maximizing pricing policies and capacity constraints that limit our ability to measure the customer equity of a hockey team.  The ranking we present today is based on what we call “Social Media Equity”.  The ranking is developed as follows:  First we collect information on each team’s social media presence such as the number of Twitter followers and Facebook likes.  We then develop a statistical model that quantifies the relationship between these social media metrics and measures of performance such as the team’s winning percentage for the last three years, and market factors including median income and metro area population.  We also include each team’s number of tweets in the model.  We then look at the difference between predicted social media followers and actual social media followers.  This delta between predicted and actual followers is reflective of Social Media Equity.

This social media based rankings has both pluses and minuses.  On the plus side, fan interest is not constraint by either high prices or stadium capacity.  On the negative side, while liking a team on Facebook or following them on Twitter shows fan interest, we can’t economically quantify this interest (these teams are businesses after all).

The number one team in our social media ranking is the Detroit Red Wings.  This is not a surprise, as the common wisdom is that the Red Wings are the number one team in Detroit (at least according to Professor Lewis’ sister in law).  The Red Wings have great social media presence on both Facebook and Twitter.  In positions 2 through 5 we have the Bruins, Devils, Flyers and Avalanche.  These are all big time fan bases with the exception of the Avalanche (actually we are not sure about the Devils but there was an episode of Seinfeld involving face painters so we assume Devils’ fans are indeed very passionate).

The Avalanche is where the story gets interesting.  While the Avalanche rank only 21st in the league in Twitter followers and 12th in terms of Facebook likes, they have achieved these results in a relatively small market, while often struggling on the ice (16-25 last year).  Our model suggests that Denver is potentially a strong hockey market.

The Social Media Equity results are a bit different than the economically driven results of last week.  Notably, the Canadian teams drop quite a bit.  In the social media rankings, Montreal finishes 6th, Vancouver 8th and Toronto 10th.    We can only speculate as to why the results differ.  Perhaps the previous results overrate the fan bases of the Canadian teams because Canadians are too nice to balk at high prices.

At the bottom of our list we have Tampa Bay in 5th from the bottom, Ottawa in 4th, the Kings in 3rd, Columbus in 2nd and Anaheim in last place.  Later in the year we will combine our various rankings to come up with a list of the best and worst sports cities.  We expect that Tampa Bay will be a front runner for one of those lists.  Ottawa performed similarly poorly in the economics based list so the verdict is in, Ottawa is the worst hockey city in Canada.  LA has a decent social media presence, but when we adjust for team performance and market size the results are not pretty.  Finally, perhaps Columbus should call themselves the “Buckeyes” rather than Blue Jackets.

The Winnipeg Jets are excluded from the rankings because the team moved from Atlanta during the period of the study.

Mike Lewis & Manish Tripathi, Emory University 2013.

Coaching Hot Seat Week 3 – Mack Brown and Lane Kiffen

Periodically, we like to do what we call “Instant Twitter Analyses.”  We do these in situations where consumer opinion is the key to understanding a sports business story.  In the case of “coaches on the hot seat” customer reactions are a critical factor.  While sports are a bit different than most marketing contexts, the basic principle that unhappy customers signal a problematic future remains true.

During this college football season we have been tracking fan base reactions to their coaches.  As we all know, there are two prominent programs (USC and Texas) with coaches in trouble.  The point of today’s post is to show how the Twitterverse has been reacting to these two coaches this season.

In the picture below we see the daily negative and positive posts for these two coaches.  The patterns and levels are remarkably similar.  But it does seem that Brown has a few more defenders at Texas (despite having two losses).   In fact over the first three weeks of the season Brown’s percentage of positive posts is 47.8% while Kiffin’s is 45.7%

This data indicates that in the court of public opinion these coaches are both in about the same shape.  We also suspect that an extended hot streak would save both coaches.  Perhaps the most interesting thing about this data is what it says about each job and fan base.  In the past we have ranked Texas as having the most loyal customer base and Forbes has ranked Texas as the most valuable athletic program.  To add to the Texas advantages, it seems that the fans are also a bit less critical.

 

 

 

Twitter Analysis: College Station Buzzing About Alabama

It’s amazing what a difference a year (or ten months) can make.  Last November, Johnny Manziel was a redshirt freshman leading a two-touchdown underdog team into the hostile environment of Bryant-Denny Stadium.  This weekend, the Heisman-Trophy winning, John Hancock-machine leads the sixth-ranked Aggies into a matchup with Alabama that is undoubtedly one of the most anticipated games of the college football season.  ESPN College GameDay will be in College Station, even though the game is on CBS.

We decided to use Twitter to study (1) how much more chatter is there about the game this year versus last year and (2) how is the chatter different between the two campuses?  Our key findings: (1) The pre-game chatter has increased over 600% in College Station and 350% in Tuscaloosa as compared to last year and (2) The level of pre-game chatter was over 3oo% greater in College Station versus Tuscaloosa in 2012 and over 400% greater in 2013.

The methodology for our study is quite straightforward.  As in our Michigan-Notre Dame “rivalry” study, we used Twitter data from Topsy Pro Analytics.  We essentially collected all of the tweets originating from College Station, TX and Tuscaloosa, AL in the Sunday-Wednesday period before the game in 2012 and before the upcoming game.  In the pool of tweets from College Station, we counted how many of them mentioned a term that was related to Alabama (e.g. “Alabama”, “Bama”, “Tide”, and “Saban”).  We divided this number of tweets by the total number of tweets collected from College Station.  We performed this analysis separately for 2012 and 2013.  This gave us the Twitter Share of Voice for the match-up in 2012 and 2013 in College Station.  We did the exact same thing for the pool of tweets from Tuscaloosa in 2012 and 2013, but we looked for Texas A&M related terms (e.g. “Aggies”, “TAMU”, “Manziel”, and “Johnny Football”).  We believe that the Twitter Share of Voice metric is a good proxy for the level of game related chatter in the two markets.

The results indicate that while both communities seem to care a lot more about the game this year than they did last year, the Texas A&M community cares a lot more about the match-up than the people in Tuscaloosa.  We look forward to performing a similar analysis when Alabama plays Auburn later this year.

Mike Lewis & Manish Tripathi, Emory University, 2013.

Twitter Analysis: Michigan Cares More about Notre Dame “Rivalry”

Last week, Notre Dame Coach Brian Kelly described the Michigan-Notre Dame game as not “one of those historic, traditional Notre Dame rivalries.”  These comments helped invigorate discussions, newspaper columns, and College GameDay signs debating the magnitude of the Michigan & Notre Dame rivalry.

Rather than listen to “experts” tell us about the significance of the game (or fabricate memories of the game), we decided to use Twitter to study how much people cared about the game in South Bend, IN and Ann Arbor, MI.  The setup for our study was fairly simple.  Using data from Topsy Pro Analytics, we were able to examine tweets originating from South Bend and Ann Arbor.  We compiled a list of words that could be used to describe Notre Dame (e.g. “Notre Dame”, “ND”, “Fighting Irish”) and a list of words that could be used to describe Michigan (e.g. “Michigan”, “UM”, “MICH”, “UMICH”).  We then collected all tweets that mentioned any of the Notre Dame related words and originated from Ann Arbor.  We also collected all tweets that mentioned any of the Michigan related words and originated from South Bend.  We believe that these tweets are capturing the level of “rivalry” that each campus has toward the other campus*.

For the game played on September 7, 2013 in Ann Arbor, we looked at tweets on September 5th and 6th (pre-game).  We also examined tweets on September 8th (post-game).   We computed the Twitter Share of Voice for tweets about Notre Dame in Ann Arbor and for tweets about Michigan in South Bend for both Pre and Post-game.  As an illustration, to compute Twitter Share of Voice for Notre Dame related tweets in Ann Arbor, you simply divide the number of tweets that mention Notre Dame in Ann Arbor by the total number of tweets in Ann Arbor.  We believe that this Share of Voice metric helps control for the relative sizes of Twitter bases in the two cities.

The results from the 2013 game are very interesting.  Pre-game, the Twitter Share of Voice in Ann Arbor for Notre Dame related tweets was 60% higher than Twitter Share of Voice in South Bend for Michigan related tweets.  This implies that people in Ann Arbor cared more about the game (at least on Twitter) than people in South Bend.  Post-game, the Twitter Share of Voice went up by 57% in Ann Arbor.  The sentiment (ratio of positive to negative tweets) of the post-game tweets also rose by 40%, whereas there was no change in sentiment in South Bend (Michigan won the game).  We could interpret this as Notre Dame fans were relatively unaffected by the loss.

Perceptive Michigan and Notre Dame fans could argue that these results are skewed because the game was played in Ann Arbor.  We have excluded tweets from the day of the game to try to correct for any game site effects.  However, to get a better understanding of the “rivalry”, we performed a similar study of the 2012 game which was played in South Bend.  Even though the game was played in South Bend, the pre-game Twitter share of voice was 18% higher in Ann Arbor. The Notre Dame victory only created a 14% increase in the post-game share of voice in South Bend, and a 23% increase in tweet sentiment.  Thus, looking at data from the past two years, there seems to be an asymmetry in this “rivalry”.  That is, it seems Michigan cares a lot more than Notre Dame.

Mike Lewis & Manish Tripathi, Emory University 2013.

*Obviously, both of these universities have alumni all over the world.  We are limiting our study to South Bend & Ann Arbor because we believe this (1) captures current students and (2) is the cleanest way to separate out the two fan bases.

Instant Twitter Analysis: USC angrier but Texas Cares More

When teams lose fans get angry and coaches get fired.  Twitter now allows us to get an instant picture of fan anger.  Over the first week and day of the college football season, two coaches have emerged as mostly likely to be run out of town.  According to Topsy, Mack Brown has been the subject of the most negative tweets (2,550) but Lane Kiffen has the highest rate of negative to positive tweets (2 times as many negative as positive tweets).

USC fans are angrier but Texas fans are more involved.