2015 NFL Draft Efficiency: A Good Sign of Things to Come for Gator fans?

The first three rounds of the 2015 NFL Draft concluded last night. While there was no Twitter-breaking Manziel event like last year, the event was once again a marketing success for the NFL.

For the past two years, we have examined the NFL draft from a unique perspective.  We analyze 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 first three rounds of 2015 Draft)/(Weighted Recruiting Talent). Weighted Recruiting Talent is determined by summing the recruiting “points” for the relevant eligible class for the 2015 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 in the first three rounds 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 Rivals.com.

2015 nfl draftThe table above shows the results of our analysis of the first three rounds of the draft.  Colorado State had two draft picks in the first three rounds that were both 3-stars or below coming out of high school.  It will intersting to see how Jim McElwain will be able to shape the higher level of talent he will most likely attract at the University of Florida.  Please note that we did not include schools that only had one player drafted in the first three rounds, as that could be considered an aberration. Of course, a similar argument could be made that one draft is too small of a sample to rate the efficiency of a college. Thus, the table below represents results from the last 4 years of drafts (2012-2015).

2012-2015 NFL DraftThe school that really stands out over the last four years with respect to the development of talent is Stanford University.  While Connecticut and Boise State may be rated higher, Stanford has produced more than double the number of draft picks of the other two schools.

Mike Lewis & Manish Tripathi, Emory University, 2015.

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 Rivals.com.

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.

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

Twitter Analysis: Which NFL Markets Are Most and Least Receptive to Michael Sam?

Top Twitter Michael SamMichael Sam’s announcement has engendered several reports in the media regarding how accepting NFL management and players would be to an openly gay player.  We were interested in looking at how the fans in NFL cities feel about Michael Sam.  In order to do this, we collected all tweets mentioning “Michael Sam” in the 31 NFL markets for the past 2 days (2/9 morning – 2/11 morning).  The tweets were sorted by market, and analyzed for positive, negative, or neutral sentiment.  Looking at the ratio of positive, negative, and neutral tweets allowed us to compare Twitter sentiment for Michael Sam across NFL Markets.

We present the top ten and the bottom seven markets in the NFL.  It is interesting to note that a lot of the tweets in St. Louis and Kansas City that mention Michael Sam also reference the University of Missouri.  The most negative Twitter sentiment toward Michael Sam seems to be in the Nashville market. Worst Twitter Michael Sam

Michael Lewis and Manish Tripathi, Emory University 2014

NFL Fan Equity: Maybe the Cowboys are America’s Team?

Note: We have been getting a lot of questions about our study.  Here are the first and second follow-ups to our study.  For an alternative fan ranking using “Social Media Equity,” click here.

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.

We will continue this discussion next week so please check back.

Mike Lewis & Manish Tripathi, Emory University 2013.

2011-2013 NFL Draft Performance by the Non-BCS Conferences FBS: Nevada, Boise State, and Idaho Excel, Notre Dame Disappoints

We have spent the last few days examining the performance of BCS Conferences schools in the 2013 NFL Draft with respect to converting high school talent into NFL draft picks (SEC, Big 10, ACC, PAC 12, Big 12, & Big East).   In this study, we consider the talent conversion ability of Non-BCS Conferences schools over the last three NFL drafts.  We find that the University of Nevada did the best job of converting high school talent into draft picks.  It should be noted that Notre Dame finished near the bottom of the list of Non-BCS schools.  While the Fighting Irish produced only one more pick than Boise State and two more than Nevada, their recruiting classes were better by leaps and bounds.

The FCS schools are excluded from this study because there is very limited recruiting data available.  However, Appalachian State produced six draft picks in the 2011-2013 NFL drafts!  It is not surprising that Appalachian State is moving to the FBS.

(*ARP refers to the average recruiting points as given by Rivals.com for recruiting classes represented in the 2011-2013 NFL Drafts)

 

 

 

 

 

 

 

 

Mike Lewis & Manish Tripathi, Emory University 2013.

2013 NFL Draft Recap Part 7: Rutgers & UConn Beasts of the Big East!

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 conclude our team-level discussion with an analysis of the Big East.

To reiterate from our previous post, this is only an analysis of the 2013 NFL Draft.  We are examining how many picks were produced by each school, relative to their recruiting classes over the relevant corresponding period for the 2013 Draft.  As with any analysis based on essentially a single data point it’s important to remember that these results are more anecdotal than conclusive.  That said, the 2013 draft does produce results that are largely consistent with our multiyear statistical study of recruit conversion.

(Please note that “Winners” are determined by the top quartile of scores, and “Losers” are the bottom quartile)

Winners: Connecticut and Rutgers are not only the big winners of the NFL Draft in the Big East, they were across the country two of the best schools for converting talent into 2013 NFL picks.  UConn produced five draft picks using talent that on average ranked outside of the top 75 during the relevant recruiting period. Rutgers had seven picks using talent that averaged just inside the top 50!  This could mean that the coaching staffs at Rutgers and UConn did a great job developing players and/or Edsall and Schiano had an eye for finding diamonds in the rough.

Middle of the Pack: In other conferences, Syracuse and USF could have been in the top quartile and thus “Winners”, because both schools produced three draft picks using talent on average outside the top 45.

Losers: Pittsburgh, Louisville and Temple all had no draft picks in the 2013 NFL draft.  Pittsburgh is the most disappointing of these schools, since they averaged talent inside the top 40 during the relevant recruiting period.

By Mike Lewis & Manish Tripathi, Emory University 2013

Methodology for the study explained here.

Methodology for Recruiting/NFL Draft Studies

The idea behind the Emory Sports Marketing Analytics initiative is to use statistical methods and marketing concepts to understand the decisions of players, teams and leagues with an eye on how these decisions effect fans.  Our feeling is that we can often generate some additional insights into the world of sports by digging into the data.  By and large we avoid too much discussion of statistics and focus mainly on the meaning of our analyses.  But readers can rest assured that the analyses behind the headlines are carefully executed.*

While we have just started the project, we have had a few requests for more details on the methods used to generate our posts.  In particular, our posts that examine the efficiency by which schools convert recruiting success to NFL draft have generated multiple questions.  The post that started the discussion was based on an analysis of six NFL drafts (2007-2012).  The analysis we reported used the number of draft picks divided by the number of elite (4 and 5 star) recruits who signed with the school.**  This ratio was then used in a linear regression that included data on each school’s investment in the football program, information of the schools recruiting success, winning rates, major bowl participation, conference memberships and other factors.

We do note that one issue in this model was in defining “recruiting success.”  Because there was no clear measure of “recruiting success” we tried multiple specifications.  These included the “recruiting points” as defined by rivals.com, recruiting class rank (averaged across multiple ratings groups) and the number of athletes at each star level.  Similarly, there may also be some debate as to what constitutes draft success.  While our reported analyses use number of picks as the key measure, one could also argue that first round picks or players selected in rounds one through three would also be appropriate.  Given the lack of obvious specification for the dependent measure of draft success and the independent variable of recruiting success, our approach was to estimate a wide variety of specifications and see what results are robust to the design of the specification.

In the case of the NFL draft analysis the finding that recruiting success tends to reduce the rate (NFL output / recruiting input) was amazingly robust.  Whether we predicted the number of day one picks or used recruiting rank the finding that top programs on average don’t produce as many NFL players as we might expect given their recruiting success was consistent.  We should, of course, emphasize that elite programs do produce more picks in absolute terms.  The key is that other programs also produce significant numbers of draft picks.

Following the 2013 NFL Draft, we have produced a series of studies that examine the “success” of colleges in converting recruiting talent into NFL draft picks.  As with any analysis based on essentially a single data point, it’s important to remember that these results are more anecdotal than conclusive.  For these studies, we produce a weighted-average of  “recruiting points” as defined by rivals.com for each school.  The weights are determined by the distribution of entering college class years for the players drafted in 2013.  The classes used are largely 2008, 2009, and 2010.  We divide the number of picks in the 2013 NFL draft by the weighted-average “recruiting points” measure for each school to determine its “success” score in the draft.  “Winners” are essentially the top quartile of scores in the conference, and “Losers” are the bottom quartile.

*Since both members of the team are business school professors we should probably make a distinction between academic publications and our blog posts.  In academic publications, methods tend to be fairly complex and are reported in great (painful?) detail.  In our blog posts we tend to use relatively simple methods such as linear and logistic regression.  In the blog posts we focus on robustness and consistency across multiple model specifications rather than on technical adjustments to the models.

** For example, the reason we used the sum of 4 and 5 star recruits was not because we were looking for a model that gave us the “right” answer but because the number of 4 and 5 star recruits tends to be in the range of about 250 per year.  This 250 number is relatively close to the approximately 220 players taken in the draft.  As such, we viewed these 250 recruits as approximating the set of projected NFL players in a given year.

By Mike Lewis & Manish Tripathi, Emory University 2013

2013 NFL Draft Recap Part 6: ISU, K-State, & TCU on Top of Big 12!

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 continue our team-level discussion with an analysis of the Big 12.

To reiterate from our previous post, this is only an analysis of the 2013 NFL Draft.  We are examining how many picks were produced by each school, relative to their recruiting classes over the relevant corresponding period for the 2013 Draft.  As with any analysis based on essentially a single data point it’s important to remember that these results are more anecdotal than conclusive.  That said, the 2013 draft does produce results that are largely consistent with our multiyear statistical study of recruit conversion.

(Please note that “Winners” are determined by the top quartile of scores, and “Losers” are the bottom quartile)

Winners: Iowa State had the worst average recruited talent during the relevant time period, but still managed to produce more picks in this draft than Baylor, Kansas, Oklahoma State, and Texas Tech.   In Manhattan, they managed to produce three draft picks in this draft despite having an average class ranking just outside of the top 60 during the relevant recruiting period.

Middle of the Pack: While Oklahoma and Texas are both in the “Middle of the Pack,” it should be noted that they represent the two extremes of this segment.  Both schools averaged top 10 recruiting classes, but Oklahoma produced six draft picks, while Texas only produced three.

Losers: Texas Tech had no draft picks in the 2013 NFL draft, however Oklahoma State’s performance seems to be most alarming.  Despite having averaged a recruiting class just outside the top 30, they managed to produce only one draft pick.

By Mike Lewis & Manish Tripathi, Emory University 2013

Methodology for the study explained here.