Oberly; Elitics - Football Analytics to Reach NFL Ascendency

7/30/2019 Oberly; Elitics - Football Analytics to Reach NFL Ascendency

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MIT Sloan Sports Analytics Conference 2013

March 1-2, 2013, Boston, MA, USA

Elitics: Using Analytics to reach NFL AscendancyTyler Oberly

College Football Insiders, D.L. Steiner

Bluffton, OH, 45817, USA

Email: [email protected]

Abstract

This review analyzes the historical context of the NFL to determine how similar todays

game is to that of the past. Through statistical analysis, we introduce Elitics (EliteAnalytics), a statistical model that proves the most consistent NFL teams since the start

of the Super Bowl era possessed certain elements that separated themselves from the

rest of the league. After detailing these elements, we propose a new quantitative

method in measuring player performance (by position). We conclude by suggesting how

the Elitics model can become an added component in developing an NFL dynasty.

1 Introduction

Since the start of the Super Bowl era, the game of football has progressed through many stages

and strategies in the NFL. Examples of the progression in the game today include the league office

adjusting rules to enhance player protection, and the popularity shifting towards a more fast-paced

passing offense. In light of these changes, many claim the game is different from what it used to be. [1]

But how drastic have these changes been?

2 Background: Elitics (Elite Analytics Model)

To quantify these changes, we began breaking down season team statistics over the past five

decades. To create a comparative analysis, we started the research by specifically reviewing theprominent teams (dynasties) from each decade. These teams included: 1960s Green Bay Packers,

1970s: Miami Dolphins, Pittsburgh Steelers, 1980s: San Francisco 49ers, 1990s: Dallas Cowboys,

Denver Broncos, 2000s: New England Patriots, Pittsburgh Steelers. To analyze these data sets, we

compared their championship seasons to the years these teams did not win the championship. During

this review, four specific elements stood out among all these teams, no matter the decade.


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Each team:

1) Limited opponents to 16 points per game or less2) Defense allowed no more than 25 touchdowns per season3) Team offense averaged over 21 points per game4) Each team had a quarterback that threw less than 15 interceptions per season (if the

quarterback threw more than 15 INTs, the offense averaged more than 2000 rushing yards -

1970s Steelers are the best example)

Two other elements many of the teams attained also included:

1) Defense forced over 30 turnovers per season2) Offense had over 2,000 rushing yards and over 20 rushing TDs per season (average yards per

attempt is greater than 4.2)

In testing the consistency of these elements, I then broke down a statistical review of every

Super Bowl winner over the past 47 Super Bowls. Of the 47 Super Bowl winners, 36 of them (76%)

contained the four key elements on their journey to a championship. More recently, over the past 10

championships, 7 of the Super Bowl winners contained the four key elements. In short, there is no

empirical evidence that suggests the game has drastically changed throughout the past five decades in

the NFL.

With the foundational elements identified that the past NFL dynasties contained, we introduce

the Elitics Model. The Elitics Model is designed to reveal, quantify, and communicate performance in

guiding an organization to separate themselves apart from the rest of the league. The Elitics Model

integrates database science to reveal players and teams unique rankings; in turn, these rankings

expose important patterns and anomalies in performance that are considerably less evident using

conventional evaluative approaches. The results facilitate efficient answers to important questions

about the NFL such as: How much is each player worth (on a balanced scale throughout the league)?

Does my quarterback contain the critical elements required to win a Super Bowl? The answers to these

types of questions hold obvious strategic advantages, but to this point few known analytical techniques

provide them.

The long-term goals of our research are 1) to advance front office expertise with quantitative

analytics that reveal key variations for evaluating player performance, 2) to design and implement new

models that predict which collegiate players will correlate best into the team's system, and 3) to

translate these results into forms effectively communicated amongst diverse audiences.

3 Case Study: Quarterbacks

As a means to evaluate team and player performance throughout the NFL, we developed a

quantitative method based upon the key elements identified from the background study. Because each

position is statistically and technically different in football, separate analysis is considered for each

position. In this report, we are specifically going to cover what many deem to be the most important

position in football, the quarterback.


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In developing the Elitic Model, one of the key elements identified from each dynasty throughout

the last five decades is the quarterback throws less than 15 interceptions in a season. Diving into this,

we also found that all quarterbacks leading the teams identified in the background study had an

interception rating less than 3, and a touchdown rating greater than 5 (TD%/INT% ratio > 1.66). In short,

there are great statistical values available to measure a quarterback, but the most important value

identified is in limiting turnovers. Based on regression analysis of seasonal statistics for each quarterback

reviewed in the background study, a mathematical model was established as a rating system to evaluate

todays quarterbacks. This model is based on individual season statistics including: Touchdown Rating

(TD%), Interception Rating (INT%), Completion %, Touchdowns, QB Rating (QBR), and Game Winning

Drives.

For the second consecutive season, Aaron Rodgers is ranked the highest overall in our case

study. Surely this is open for discussion, but based on the modeled calculations, Aaron Rodgers has been

the most productive quarterback in the league over the past year. All dynasty quarterbacks modeled in

the background study held a score above 1.75, which we have established as our baseline number for

preferred quarterback scores. As you can see below, the top 10 quarterbacks of the 2012 season were

well above this baseline number.

Player TD%/INT% Elitic Score

1 Aaron Rodgers 7.1/1.4 2.51

2 Peyton Manning 6.3/1.9 2.39

3 Matt Ryan 5.2/2.3 2.33

4 Russell Wilson 6.6/2.5 2.23

5 Tom Brady 5.3/1.3 2.19

6 Drew Brees 6.4/2.8 2.16

7 Ben Roethlisberger 5.8/1.8 2.128 Robert Griffin III 5.1/1.3 2.11

9 Tony Romo 4.3/2.9 2.02

10 Alex Smith 6.0/2.3 1.94

Top 10 players in Elitic Score metric

Although Drew Brees and Tony Romos Elitic Scores measured above a 2.0, both threw over 15

interceptions throughout the season. Of the top ten listing based on the Elitic Model, Ben Roethlisberger

is the only quarterback who threw less than 15 interceptions throughout the season and did not make

the playoffs.

Where do the quarterbacks in this years Super Bowl rank?


12 Joe Flacco 4.1/1.9 1.86

14 Colin Kaepernick 4.6/1.4 1.85

Both Kaepernick and Flacco have Elitic scores exceeding the baseline score of 1.75. Because their

touchdown numbers were low throughout the regular season, it is reflected in the Elitic Score. However,


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both Flacco and Kaepernick are among the top in the league in interception %. This was reflected

throughout the playoffs as Flacco threw zero interceptions and Kaepernick threw only one.

Making the case for Alex Smith

Many fans, writers, and NFL analysts do not believe Alex Smith is a top 10 quarterback in the

NFL. This is a highly debatable topic that has increased with the recent success of Colin Kaepernick for

the 49ers this season. Many of the arguments against Alex Smith may be warranted, but when analyzing

his statistics over the past two seasons, Alex Smith has ranked in the top 10 among the league, with his

Elitic Score rating well above the 1.75 baseline.

Player TD%/INT% Elitic Score Value/Elitic Score[2]

1 Aaron Rodgers 7.1/1.4 2.51 $ 4,316,068.92

2 Peyton Manning 6.3/1.9 2.39 $ 8,033,472.80

3 Matt Ryan 5.2/2.3 2.33 $ 4,721,030.04

4 Russell Wilson 6.6/2.5 2.23 $ 335,201.79

5 Tom Brady 5.3/1.3 2.19 $ 7,168,949.776 Drew Brees 6.4/2.8 2.16 $ 9,259,259.26

7 Ben Roethlisberger 5.8/1.8 2.12 $ 6,014,150.94

8 Robert Griffin III 5.1/1.3 2.11 $ 2,502,263.03

9 Tony Romo 4.3/2.9 2.02 $ 5,561,055.94

10 Alex Smith 6.0/2.3 1.94 $ 4,123,711.34

2012 season - Top 10 players in Elitic Score metric (with calculated $ value)

Player TD%/INT% Elitic Score Value/Elitic Score[2]

1 Aaron Rodgers 9.0/1.2 2.74 $ 3,953,771.17

2 Drew Brees 7.0/2.1 2.62 $ 7,633,587.79

3 Tom Brady 6.4/2.0 2.32 $ 6,767,241.38

4 Tony Romo 5.9/1.9 2.30 $ 4,884,057.83

5 Matt Stafford 6.2/2.4 2.29 $ 5,240,174.67

6 Eli Manning 4.9/2.7 2.10 $ 7,272,109.05

7 Alex Smith 3.8/1.1 2.02 $ 3,960,396.04

8 Matt Ryan 5.1/2.1 2.02 $ 5,445,544.55

9 Matt Schaub 5.1/2.1 1.82 $ 7,269,230.77

10 Andy Dalton 3.9/2.5 1.73 $ 753,497.11

2011 season - Top 10 players in Elitic Score metric (with calculated $ value)

Among all veterans (excluding rookies) ranked in the top 10 over the past two seasons, Alex Smith is alsothe lowest valued quarterback, next to Aaron Rodgers. One of the main reasons to explain Smiths low

value may be because he is not paid at the same level as a Tom Brady or Drew Brees, and we are not

suggesting he should be. However, with the high demand for a consistent quarterback in the NFL, Alex

Smith has proven to be one of the most under-valued quarterbacks in the league over the past two

seasons.


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4 Discussion: Taking the Elitics Model to the next level

Because of the new rookie wage-scale under the current labor agreement with the NFLPA and

the NFL, the NFL draft has become an even more critical element to each team. Teams can now draft

players at a bargain rate and retain the contract for three years before a new contract agreement can be

made. [3] In review of the top 10 quarterbacks ranked over the past two years (previous page), Russell

Wilson, Robert Griffin III, and Andy Dalton are all valued significantly lower to even Alex Smith. While

free agency is an avenue to re-tool a team, the NFL draft is the main avenue to develop a dynasty. To

assist front office evaluations, we have also developed a parallel platform for evaluating rookies by

utilizing the Elitics Model.

We performed a case study utilizing the Elitics Model to review the rookie quarterbacks prior to

the 2012 NFL Draft. According to the model, Russell Wilson, Robert Griffin III, and Andrew Luck were all

predicted to translate immediately into the NFL. Those valued below 1.75 baseline NFL score are players

that were not predicted to make an immediate leap as a starting quarterback in the NFL. We are notdismissing the talents of those predicted below 1.75, but were recommending them to be better suited

in a developmental role. In review of the rookies 2012 season, the Elitic Model successfully predicted

the top three quarterbacks transition into the NFL at nearly a 5% margin of error. Both Wilson and

Griffin III performances this past season exceeded the models predicted score. Among the players

reviewed, Brandon Weeden had the highest margin of error (23.5%) in the prediction model.

Predicted

NFL ScorePlayer TD%/INT% Elitic Score

1 Russell Wilson 11.47/1.38 3.44 2.06

2 Robert Griffin III 9.2/1.5 3.30 1.983 Andrew Luck 9.56/1.8 3.01 1.80

4 Brandon Weeden 7.24/2.1 2.83 1.70

5 Nick Foles 5.0/2.5 2.43 1.46

6 Kirk Cousins 5.41/1.7 2.31 1.39

7 Ryan Tannehill 5.42/2.71 2.20 1.32

2011 Collegiate Score with predicted NFL score


1 Russell Wilson 6.6/2.5 2.23

2 Robert Griffin III 5.1/1.3 2.11

3 Andrew Luck 3.7/2.9 1.78

4 Kirk Cousins 8.3/6.3 1.58

5 Nick Foles 2.3/1.9 1.43

6 Ryan Tannehil 2.5/2.7 1.37

7 Brandon Weeden 2.7/3.3 1.30

2012 Rookies in Elitic Score metric


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5 Conclusion

On the path of answering the simple question to how drastically different the NFL game is today,

we stumbled upon simple, but subtle, elements. These elements (four fundamental, two supplemental)

have proven the consistency of football throughout the decades, regardless of the trends. These

elements also unlocked the Elitics Model, which we have shown, can be utilized to advance front office

expertise with quantitative analytics. These analytics are not the answer to every question, but they can

add an element of expertise to reveal key variations in evaluating player performance, and can also

assist in predicting which collegiate players will correlate best into a team's system. In the end, the

Elitics Model reveals, quantifies, and communicates performance to guide an organization in separating

themselves from the rest of the league.

6 References

[1]http://knowledge.wharton.upenn.edu/article.cfm?articleid=2628

[2] All salary information is media released numbers based fromhttp://www.spotrac.com

[3]http://www.cbssports.com/nfl/story/19608672/teams-getting-great-deals-as-rookie-wage-scale-

keeps-salaries-in-check
http://knowledge.wharton.upenn.edu/article.cfm?articleid=2628http://knowledge.wharton.upenn.edu/article.cfm?articleid=2628http://knowledge.wharton.upenn.edu/article.cfm?articleid=2628http://www.spotrac.com/http://www.spotrac.com/http://www.spotrac.com/http://www.cbssports.com/nfl/story/19608672/teams-getting-great-deals-as-rookie-wage-scale-keeps-salaries-in-checkhttp://www.cbssports.com/nfl/story/19608672/teams-getting-great-deals-as-rookie-wage-scale-keeps-salaries-in-checkhttp://www.cbssports.com/nfl/story/19608672/teams-getting-great-deals-as-rookie-wage-scale-keeps-salaries-in-checkhttp://www.cbssports.com/nfl/story/19608672/teams-getting-great-deals-as-rookie-wage-scale-keeps-salaries-in-checkhttp://www.cbssports.com/nfl/story/19608672/teams-getting-great-deals-as-rookie-wage-scale-keeps-salaries-in-checkhttp://www.cbssports.com/nfl/story/19608672/teams-getting-great-deals-as-rookie-wage-scale-keeps-salaries-in-checkhttp://www.spotrac.com/http://knowledge.wharton.upenn.edu/article.cfm?articleid=2628

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Oberly; Elitics - Football Analytics to Reach NFL Ascendency