Documenting the #RedskinsPride Disaster

Yesterday, the Washington Redskins organization asked their fans to tweet @SenatorReid using the hashtag “#RedskinsPride” to tell him what the team meant to them.  There are now numerous examples of how firms should let hashtag campaigns develop organically rather than try to encourage a conversation over which they have no control.  However, the Redskins organization decided to ignore common sense, and the results were predictable.

The chart below tracks the hourly Twitter mentions of “#RedskinsPride” on its primary axis, and the hourly sentiment of all tweets containing the hashtag on its secondary axis (The sentiment is indexed from 1-100, with 100 being the most positive).


While the chart provides a nice overall view of what happened yesterday, it is interesting to see how the hashtag campaign evolved over time and geography.  The table below describes the evolution:

#RedskinsPride Chart

We should note that while a lot of the tweets came from outside of the Metropolitan DC area, even the tweets originating from DC, VA, and MD tended to be more negative than positive.

Manish Tripathi & Mike Lewis, Emory University 2014.

NPR Marketplace: For NBA, courting Steve Ballmer could be a strategic move

NPR Marketplace: For NBA, courting Steve Ballmer could be a strategic move

Going forward, Emory University’s Mike Lewis says the NBA would be psyched to have a deep-pocketed guy own the Clippers.

“You know they are sort of the New York Mets or the Chicago White Sox. They are the second team in that city. I think it’s really attractive to the league to essentially have two really strong franchises in a major city like LA,” he says.

NBA Conference Finals: Spurs & Thunder Dominate Local Twitter Market

Last night, the Oklahoma City Thunder beat the San Antonio Spurs in Game 4 of the Western Conference Finals.  We were interested in examining the Twitter presence of both teams in their respective markets during the game.  Thus, we collected all tweets that included the word “Thunder” originating from the Oklahoma City market and all tweets that included “Spurs” originating from the San Antonio market, that were tweeted during the hours that the game was played.  We then divided the number of collected tweets by the total volume of tweets in the respective markets during the time period of the game.  This essentially gave us the “Twitter Share of Voice” for the Spurs in San Antonio and the Thunder in Oklahoma City.   11.8% of all tweets in Oklahoma City during the game included the term “Thunder”!  9.3% of all tweets in San Antonio included the term “Spurs”.  We performed a similar analysis for all other conference finals games thus far.  The results of the analysis are presented in the chart below.

Local Market Twitter Share NBA Conf Finals 2014

It seems as though tweets that mention the local team in the Western Conference Finals cities tend to have a higher Twitter Share of Voice than the Eastern Confernce Finals cities.  We can also examine the content of the team-related tweets to determine if the sentiment of the tweets is positive, negative or neutral.  The chart below presents the ratio of positive to negative sentiment for the team-related tweets in each market during the playoff games.

Local Market Twitter Sentiment Ratio NBA Conf Finals 2014So far, local market Twitter “happiness” in highest for San Antonio fans during the first game of the series, and for Oklahoma City fans during the third games of the series.  Indiana fans seem to tweeting progressively less about the Pacers, and the positive to negative tweet ratio has been decreasing as the series advances as well.

Manish Tripathi & Mike Lewis, Emory University 2014. – B1G numbers: Building the brand – B1G numbers: Building the brand

“Locally, the support is still there; people are still paying to go watch the team,” Tripathi said, “but on a national level, there has been a bit of a hit on the brand. That’s manifesting in the decline in sales of merchandise.”

Note: Professor Lewis’ wishes that this Kris Kross endorsement from the 90s would have had a bigger impact on the Illini brand:Flying Illini

2014 NFL Draft Efficiency Rankings

The 2014 NFL concluded on Saturday evening.  The three-day event featured Johnny Manziel taking over the Twitterverse on Thursday night, and the St Louis Rams selecting Michael Sam near the end of the draft on Saturday.  A lot of the post-draft analysis was either based on total number of draft picks from a college or draft picks from a college adjusted for when they were picked in the draft.  Of course, there are also a plethora of inane draft grades where clairvoyant “experts” project how well the draft picks will perform on the team.

Our take on the draft is a bit different, as we will examine the process of taking high school talent and converting it into NFL draft picks. In other words, we want to understand how efficient are colleges at transforming their available high school human capital into NFL draft picks?

Our approach is fairly simple.  Each year, every FBS football program has an incoming 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 NFL.  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?

How did you compute the conversion rate?

The conversion rate for each school is defined as (Sum of draft picks for the 2014 Draft)/(Weighted Recruiting Talent).  Weighted Recruiting Talent is determined by summing the recruiting “points” for the relevant eligible class for the 2014 NFL Draft for each program (this can include eligible juniors as well as fifth year seniors).  These “points” are computed by weighting each recruit by the overall population average probability of being drafted for recruits at that corresponding talent level over the last three years.  For example, a five-star recruit is much more likely to get drafted than a four or three-star recruit.  We are using ratings data from

2014 Full NFL Draft Efficiency

The figure above shows the top ten schools in the FBS for converting high school talent into draft picks for the 2014 draft.  We have indexed the efficiency rating based on the leader, Boise State.  It is interesting to note that the team with the most draft picks in the 2014 NFL Draft, LSU, finished 11th in our rankings.

Do the results of one draft really matter?

A fair criticism of this ranking is that it only represents one draft year; what if this draft was an anomaly for Boise State and Wisconsin?  The rankings below consider the 2012, 2013, and 2014 NFL Drafts.  While Boise State and Wisconsin are still on top, schools such as Connecticut, Iowa, and Nevada are now also in the top ten.

2012-2014 Full NFL Draft Efficiency

How can you treat a first-round draft pick the same as a seventh rounder?

Our study is primarily considered with schools that give high school talent the opportunity to play in the NFL.  Thus, the rankings above do not discern between rounds of the draft.  Ostensibly, a player’s initial contract and status in the NFL seems tied to draft order (although Richard Sherman has done real well for a 5th round pick).  Let’s assume that being picked in the first three rounds of the draft is of importance to players.  We can conduct a similar type of analysis, but only consider picks in the first three rounds of the draft, and adjust the weighting to reflect population averages for being picked in the first three rounds.  The rankings below are based on an analysis of only the first three rounds over the last three years.  Boise State is still on top, but schools like LSU, Cincinnati, & North Carolina have moved up the list.

2012-2014 First 3 Rounds NFL Draft Efficiency

 Of course, there are many other ways for trying to understand or rate draft efficiency.  In the past we have also conducted regression-based analyses with additional data such as program investment to better understand the phenomenon of human capital development in both football & basketball.

Mike Lewis & Manish Tripathi, Emory University 2014.

  *We can already hear our friends at places like Alabama & USC explaining how players are rated more highly by services just because these schools are recruiting them.  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 few years, given all of the media exposure for high school athletes, this problem has attenuated. 

Manziel’s Draft Night Twitter Takeover

There was speculation last night during the first round of the 2014 NFL Draft that if Johnny Manziel was drafted by the Dallas Cowboys, the Twitterverse would “explode”.  While the Cowboys passed on Johnny Football, Manziel was still the king of Twitter last night.  We used Topsy Pro to collect all tweets in the United States between 8pm EDT and midnight last night.  In that collection of tweets, we counted up all of the tweets that included the term “Manziel”.  This accounted for 5.2% of all of the tweets in the US.  We performed a similar analysis for all tweets that were geo-coded as originating from Texas.  “Manziel” was included in 9.6% of all tweets in Texas!

Manziel Draft Night Final

The graph above plots the overall volume of tweets in the United States and tweets that included “Manziel”.  It is interesting to note that as the draft progressed and Manziel was still available for the Cowboys, the Manziel tweets started to rise, followed by a drop-off when the Cowboys drafted Zach Martin.  The largest spike in Twitter activity in the US last night was when Cleveland finally drafted Manziel.

Manish Tripathi & Mike Lewis, Emory University 2014.

Richard Sherman: Using Twitter to Build Your Brand

The sports landscape includes a handful of individuals that have transcended being just athletes, and have become brands.  Michael, LeBron, Kobe, Tiger and Peyton are prime examples of athletes that have achieved sufficient celebrity to become part of the culture; and by doing so have become coveted endorsers.  Just as most people know that Peyton Manning is a member of the Denver Broncos, we suspect that a large portion of society also knows his favorite brand of pizza.  Seattle Seahawks CB Richard Sherman is perhaps the athlete that made the biggest move towards becoming his own brand in the last year.

Yesterday, Sherman signed a four-year, $57.4M deal with $40M guaranteed.  This makes him the highest paid CB in the NFL.  Of course, Sherman has also recently signed multiple endorsement deals (Oberto, Campbell Soup, Nike, etc.).  Mr. Sherman announced his new contract deal through Twitter, and this is not surprising, since Sherman actively communicates through Twitter.  His Twitter account, @RSherman_25, has over 925K followers (The official Seattle Seahawks team Twitter account has 529K followers).

We believe Sherman represents an interesting case-study on how to build a brand using social media.  The graph below illustrates the monthly volume of tweets that mention @RSherman_25.  The account was activated in September 2011, but the first time it experienced a significant uptick in volume was in October 2012.  In that month, the virtually “unknown” Sherman called out all-pro QB Tom Brady and needled the great WR Calvin Johnson.  Sherman’s Twitter presence continued to grow with an offseason discussion/”Twitter-Fight” with CB Darrelle Revis regarding who was the best CB in the NFL.  Of course, Sherman’s Twitter mentions exploded following his NFC Championship post-game interview with Erin Andrews.

The other thing is that Sherman provides a great counter-point toward much of the conventional wisdom that infests the marketing world.  Of late we have seen an enormous number of celebrities who have had to apologize for one statement or another.  At times it seems like marketers are more interested in playing it safe at all costs.     Sherman Brand

It seems that the key moments in Sherman’s Twitter timeline were all considered “controversial” by many in the media.  This is not necessarily surprising given the nature of social media; however there are two remarkable aspects here: 1) The overwhelmingly positive Twitter reaction to Sherman’s actions and 2) Sherman’s ability to build on the “controversial” spikes in volume over time.

Sherman Sentiment

The chart above shows the monthly volume of positive and negative tweets that mentioned @RSherman_25.  We used software from to code each tweet as having positive, negative, or neutral sentiment.  Given the press coverage of Sherman’s post-game interview, many would have thought of Sherman as the “villain”, however, the response on Twitter was more positive than negative.  Over time, the post-game “rant” has become thought of as more comical (e.g. President Obama referenced it at the White House Correspondents Dinner this year & Sherman uses it in a commercial for Swedish Hospital).

Sherman’s rise and development as a “brand” highlights several important brand lessons.  Sherman has exploded in popularity because he is smart, interesting and authentic.  This is a much better strategy for building a brand than to relentlessly playing it safe.

Manish Tripathi & Mike Lewis, Emory University 2014.

2013 NFL Draft Efficiency Analysis [Repost]

The 2014 NFL Draft finally begins this Thursday.  Next week, we will be providing our analysis of how well college conferences and teams performed with respect to converting high school talent into NFL draft picks.  Below, we have reposted a similar analysis from the 2013 NFL Draft.

The 2013 NFL Draft has concluded, and we would like to offer our thoughts on the ability of conferences and schools to turn high school talent into NFL Draft Picks.  We start with a conference ranking:

Our methodology for this ranking is quite straightforward.  We examine the average rating points (typically a function of the number of rated high school recruits in a class) by conference over the relevant recruiting periods for the 2013 NFL Draft.  It should be noted that our analysis is only for the 2013 Draft, and that there can be large fluctuations over time, especially on a team-by-team level.  Our previous study was for the six year period before this draft, and it only considered conversion rates for four-star and five star recruits.

Given the tremendous number of picks from the SEC, it is no surprise that the SEC dominated the NFL Draft in terms of converting its high school talent into NFL Draft picks.  What is surprising, however, is the performance of the Big East.  Even though the Big East had fewer picks than the ACC or Pac-12, it ranked higher because of its “input quality”.  Teams in the Big East managed to produce 2013 NFL draft picks with weaker high school talent on average.

Methodology for the study explained here.

For the SEC Breakdown, click here.

For the Big 10 Breakdown, click here.

For the Big East Breakdown, click here.

For the ACC Breakdown, click here.

For the Big 12 Breakdown, click here.

For the PAC-12 Breakdown, click here.

For the best of the Non-BCS Breakdown, click here.

By Mike Lewis & Manish Tripathi, Emory University 2013