Charlotte Business Journal: Panthers Playoffs – Building Brand Loyalty

Charlotte Business Journal: Panthers Playoffs – Building Brand Loyalty

Two marketing professors at the Goizueta Business School at Emory University study sports franchises and fan interest by looking at whether fans are willing to invest financially (tickets, souvenirs and so on) and in terms of social media chatter. In both instances, Carolina ranks in the bottom third (23rd in financial willingness and 30th in social media equity).

“There is an opportunity to get better here,” Manish Tripathi, one of the Emory marketing professors who works on the studies, told me. “Post-season success has a strong impact in the NFL, especially for building the younger fan base.”

Washington Post: Fans starting to dislike Redskins’ Coach Jay Gruden as much as owner Daniel Snyder

Washington Post: Fans starting to dislike Redskins’ Coach Jay Gruden as much as owner Daniel Snyder

Kirk Cousins had a short stint as Redskins quarterback, but it was clear after his four-interception performance against the Giants on Sept. 25 that fans were ready to move on.

However, no matter what the outcome of the game, one thing was certain: fans were most negative about owner Daniel Snyder week by week. Until now.

For the first time this season, the negative sentiment on Twitter was as high for Coach Jay Gruden as it was for the team’s owner.

How Much Do NFL Stadiums Matter?

MLB Ballpark factorsWhere a game takes place hugely impacts performance, without even taking home field advantage into account.  In the MLB, there are “ballpark factors” which provide data as to how much more or less likely an event (e.g. double, home run, etc.) is in a particular ballpark relative to the league average.  These “ballpark factors” are a concept that most die-hard baseball fans know very well, and something all fantasy baseball players should be familiar with (especially for daily sites, like FanDuel).  ESPN provides a table to all its readers like the one shown on the left. The table reads as follows: for every one run scored in a league average MLB park, 1.501 runs will be scored in Colorado and .825 runs will be scored in Seattle. These factors are not the be-all and end-all when it comes to explaining player performance, but it’s another predictive tool to add to your tool belt.

Two recent examples show its application quite nicely: the performance decline of Robinson Cano after he decided to move to Seattle this past season, and the reasoning (or lack thereof) behind the Mets free agent signing of Michael Cuddyer this offseason.  In his seven full seasons with the Yankees, Cano averaged 24 home runs in 160 games per year.  His first year in Seattle he hit 14 in 157 games. Using only ballpark factors we would have predicted that he would hit 16 – not bad for just one calculation.  Michael Cuddyer has played his last three seasons with Colorado, hitting .307 with 15 home runs in only 93 games per year.  Again using only ballpark factors, in 93 games next year he should hit .254 with 12 home runs.

Being the fantasy sports aficionado that I am, I wanted to apply the same idea behind these ballpark factors to NFL data. However, much to my dismay, there was no NFL equivalent to be found. So, I decided to create NFL Stadium factors based on data from 2010 to 2013. The result is the table seen below.

Stadium FactorsExcludes SF & MN

Just as with MLB “ballpark factors”, the numbers in this table are just another piece in the puzzle of football analytics.  Unlike baseball, however, the NFL Stadium Factors are a slightly more effective tool on a team-by-team basis rather than for individual performance. For example, consider the trade rumors hovering around the weeks leading up the NFL draft this past year. “Brady to Houston,” the headlines read. On the surface this looks like a no-doubter for the Texans, but has New England’s stadium been augmenting Tom Brady’s statistics over these many years? In fact, a quick look at the table on the left makes me wonder if the Patriot offensive juggernaut as a whole has benefited by playing in Foxboro.  New England’s passing attack has averaged 276 yards per game and 33 touchdowns in the air over the past five years. If they had been playing in Houston’s stadium over that time span, stadium factors suggest those number would have plummeted to 252 and 29.

It’s easy to take these numbers as they are and just plug them in your statistical analyses; however considering the characteristics of given stadiums in order to understand why certain trends exist in the data is infinitely more useful. The stadium characteristics I looked at are as follows: domes, turf fields, cold weather, noise, and altitude.

  • In stadiums with domes, you see a significant increase in field goals made and a decrease in rush yards gained. This is likely due to the absence of wind and other adverse weather effects, which negatively affects the passing game and field goals. Regardless of whether or not a team has a good rushing attack, if conditions don’t lend themselves to a game plan centered on throwing the ball, then more rush yards will inevitably be gained.
  • On turf fields, the number of successful field goals goes up substantially due to the more consistent footing for kickers. Kickers are much more prone to slipping on the less-secure grass footing of a natural surface.
  • The third characteristic, cold weather, is defined from a list of the 10 coldest and snowiest stadiums in the NFL. From that classification, I found that noticeably fewer points, rush touchdowns, and field goals occur in those stadiums. These outcomes are all fairly logical and can be explained by the unfavorable effects of the cold on the human body. In addition, as the temperature drops the football becomes less elastic. In combination with the dense, cold air inside and outside of the football, this makes field goals a much harder task.
  • In the NFL’s five loudest stadiums, noise was found to lead to fewer points scored per game, most likely because of a two factors – communication and intensity. The louder a stadium gets, the harder it is for an offense to communicate certain blitz protections or other audibles. Secondly, the intensity of a loud crowd leads to more pressure and greater nervousness, which I believe more heavily impacts offensive performance.
  • Finally, altitude is directly and positively correlated to field goals made and rush touchdowns scored. The first part makes perfect sense – things fly further in the lighter air of high altitude. The reason behind the second finding is a little more intricate. Altitude has powerful effects on lung capacity and conditioning levels, so defensive linemen (who aren’t in shape) tend to struggle in places like Mile High Stadium. Rushing touchdown data would specifically reveal this trend, because they often occur at the end of long drives when those in charge of stopping the run (the defensive linemen) are exhausted.

This table is a great starting point in starting to describe the effect that a certain location has on NFL performance. Although the insights behind the aforementioned explanations are my personal opinions, the numbers can be explained logically, and when used in statistical analysis will most definitely lead to improved results.

Michael Byman (@MichaelByman) is a senior at Emory’s Goizueta Business School.  He is a Sport Analytics Research Grant recipient & submarine college pitcher.

Washington Post: Here is when Kirk Cousins lost the Redskins’ fan base

Washington Post: Here is when Kirk Cousins lost the Redskins’ fan base

The Washington Redskins were a team starved for good news, and Sunday’s win over the Tennessee Titans did the trick. It also may have created more questions than answers, which is why the negative sentiment from the Washington area for this team lingers on Twitter.

“Negative is where the action is,” said Manish Tripathi, assistant professor in the practice of marketing at Emory University. “People have a lot more variation into how negative they are about people. This is true in general on Twitter: you always see a lot more variation of negative sentiment. Even when people are doing well you don’t often see spikes in positive, you just just see less negative.”

Too Gay to Play? A Quantitative Analysis of Michael Sam’s Pre-Season Performance

The following is a guest post by Dr. Thomas Smith of the Goizueta Business School, Emory University.

Michael Sam, the first openly gay player drafted into the NFL, was cut by the St. Louis Rams this past weekend. Several analysts, including Mike Freeman of Bleacher Report, identified that cutting a player with performance stats similar to those of Sam is “almost unprecedented… and basically unheard of .” (Freeman’s article)  We know Sam had 11 combined tackles and 3 sacks, but are these the only way to measure Sam’s performance?  Let’s look at the stats of the defensive ends that made the cut this past weekend:

Table 1: Statistics of DEs Making the 53-Man Roster (2014 Pre-Season)

Table1 Source:; (players on IR are not included in this table)

Table 2: Statistics of Michael Sam



According to statistics, the DEs that made the cut had an average of 8 combined tackles and a little less than 1 sack. Sam’s stats better these marks by quite a bit. If these are the only statistics that matter, then the Rams (and most every other team) are missing out. However, if other performance metrics are considered – say those that are captured in the annual NFL Combine, then Sam was a little behind the ball. Sam is 0.14 seconds slower in the 40 yard dash, nearly 0.50 seconds slower in the 3-Cone drill, has a lower vertical leap, smaller broad jump and has a little less upper body strength than his counterparts.

But who is to say which statistic is the ‘silver bullet’, so to speak? If I look at the 40-yard dash and 3-cone performance then Jackson Jeffcoat (4.63 and 6.97) is the standout performer – yet didn’t make the Seahawks. Why? The Seahawks do not need him on defense – they are amazing without him.  Is it possible that Sam didn’t make the Rams because they didn’t need him – they were covered at DE? Absolutely.

Is it unprecedented that a player with Sam’s statistics on tackles and sacks gets left off a team (including the practice squad)? Looking back over the past four seasons (2010 – 2013) it appears that Mr. Freeman is on to something.  Looking at only the defensive ends with combined tackles within 1 and/or sacks within 1 of Michael Sam’s 2014 pre-season performance you see the following:

Table 3: DEs with Pre-Season Statistics Similar to Michael Sam (2010-2013)

Table 3


So, Freeman knows his material. In the last four years, players with tackles and sacks similar to Michael Sam end up on a team (or practice squad in the case of Matt Broha). But, does this mean that the NFL is homophobic? No doubt people in the NFL are. However, this doesn’t prove that he’s not on the Rams because the Rams are homophobic. Several of the players listed above were picked up as free agents – they didn’t all play for the team that drafted them. And, at the moment, rumors are swirling that the Cowboys are interested in Sam for their practice squad (Note: he has since been signed by the Cowboys).

What does this mean? There is more than one statistic out there – we have seen plenty of players with better (and worse) statistics (all statistics) relative to Sam both make the NFL and get cut.

Thomas More Smith, Emory University, 2014.

Pittsburgh Post-Gazette: Steelers fans tops in social media but not in spending on team

Pittsburgh Post-Gazette: Steelers fans tops in social media but not in spending on team

Love is sometimes pursued at all costs, but it’s a little cheaper at Heinz Field.

A recent analysis by Michael Lewis and Manish Tripathi, professors at Emory University’s Goizueta Business School, found that while Steelers fans outpace all the rest in social media engagement, they are only in the middle of the pack in terms of how much they pay to follow their team.

The authors generated two metrics from 13 years of data. The first was “fan equity,” measuring how much fans are willing to pay to support their team through ticket sales and merchandise purchases. The second, “social media equity,” measured fan devotion in the online arena. Both measures were statistically adjusted to control for stadium size, local population, median income and team performance.

The Top 10 “Bandwagon” or Demanding Fans in the NFL

An analysis we have had fun with this summer involves looking at fan response to winning rates. This encompasses looking at how different fan bases respond to variations in winning. If fans only show up when the team wins, does this mean they are bandwagon fans? Or does it mean that they demand quality?  We report, you decide.

Studying which city has the most “bandwagon” or demanding fans is a challenge in the NFL. The issue is that many teams sell-out regardless of the team’s performance. How can we differentiate between the Steelers and the Packers when the stadiums are always full? As such for the NFL, we only present a top ten list of the cities with the most fair weather or discerning fans. (We looked at the last thirteen years of data for our study. For more details on our methodology, please click here.)

2014 NFL Bandwagon

The winner, or maybe that should be the loser, of this ranking is the Arizona Cardinals. These fans are most responsive to winning percentage in the NFL based on our statistical model of attendance. Arizona is followed by New Orleans, Buffalo, Oakland and Washington.

Mike Lewis & Manish Tripathi, Emory University 2014.

Yahoo Sports: Cowboys, Steelers fans rank as NFL’s ‘best,’ new study finds

Yahoo Sports: Cowboys, Steelers fans rank as NFL’s ‘best,’ new study finds

The Sports Marketing Analytics project at Emory University tracks a variety of statistical measures to track fan loyalty. The project, the product of professors Mike Lewis and Manish Tripathi, has determined that the fan bases of Dallas and Pittsburgh rank at the top of two important statistical categories.

Dallas leads the way in “Fan Equity,” a metric designed to track just how much a fanbase supports its team financially. The ranking is an average of the last three years, but even so, Dallas has led in this category for five years. Rounding out the top five are the fan bases of the Patriots, Jets, Giants, and Colts.