Predicting Success Using the Nfl Scouting Combine ______

Home , NFL Scouting Combine, Skill position

PREDICTING SUCCESS USING THE NFL SCOUTING COMBINE ______

A Thesis

Presented to the

Faculty of

California State University, Fullerton ______

In Partial Fulfillment

of the Requirements for the Degree

Master of Science

Clinical Psychology ______

Andrew James Meil

Thesis Committee Approval:

Melinda Blackman, Department of Psychology, Chair Kristin Beals, Department of Psychology Jack Mearns, Department of Psychology

Spring, 2018

ABSTRACT

Professional sports organizations have been utilizing data-based approaches when selecting potential athletes increasingly over the past couple of decades, as depicted in

Moneyball. The National Football League (NFL) conducts a yearly Scouting Combine in an attempt to examine top prospects’ physical characteristics and attributes that are typically sought after in the game of football. The current study focuses on whether an athlete’s performance at the Combine can predict future success at the professional level.

The study examined 917 athletes that participated in the Combine from 2004 to 2009.

These athletes were categorized into eight different position groups across the National

Football League. Measures for the study included six physical ability tests from the

Combine, height, weight, and three unique success variables. Correlations and multiple regressions were conducted to examine the impact of Combine performance on future success. Only four of the eight position groups had statistically significant predictions in the study. However, the primary finding of whether a player’s performance at the

Combine was able to predict future success in the NFL based on their position is deemed questionable at best. Thus, the study suggests that NFL executives and personnel influence a statistical approach, in combination with professional judgment to account for intangibles and unquantifiable measurements, in order to select an athlete that has the most potential to be a successful player in the National Football League.

TABLE OF CONTENTS

ABSTRACT ...... ii

LIST OF TABLES ...... v

ACKNOWLEDGMENTS ...... vi

Chapter 1. INTRODUCTION ...... 1

Introduction ...... 1 The National Football League ...... 3 NFL Scouting Combine ...... 5 NFL Combine Studies ...... 7 Purpose and Hypotheses ...... 11

2. METHODS ...... 14

Methods ...... 14 Data Collection ...... 14 Participants ...... 14 NFL Combine Physical Ability Tests ...... 15 Forty-Yard Dash ...... 15 Vertical Jump ...... 15 Bench Press ...... 16 Broad Jump ...... 16 Three-Cone Drill ...... 17 Twenty-Yard Shuttle ...... 17 Physical Attributes ...... 18 Success in the NFL ...... 18 Years of Experience ...... 18 Post-Season Accolades ...... 19

3. RESULTS ...... 20

Results ...... 20 Multiple Analysis of Variance ...... 22 Multiple Regressions ...... 22

iii 4. GENERAL DISCUSSION ...... 25

REFERENCES ...... 33

LIST OF TABLES

Table Page

1. Correlations Amongst Physical Ability Tests and Success ...... 21

2. Position-Specific Regressions ...... 24

ACKNOWLEDGMENTS

I would like to thank my parents, family, and friends for the unconditional support, encouragement, and love they continuously show me.

vi 1

CHAPTER 1

INTRODUCTION

Within each type of organization or business, there are unique procedures that are required when selecting potential employees. Selecting a potential employee can either positively or negatively impact the organization; therefore it is of great importance to select personnel that may benefit the organization. A selection system can be evaluated through the accuracy of the predictors being used, specifically by how well a measure correlates with performance-related criteria needed for that organization (Murphy, 2002).

Generally, there are two different approaches that can be implemented within a selection process: the “statistical” approach, which involves an algorithmic combination of data, and the “clinical” approach, which is a broad term applied when a human judge evaluates available information to make a prediction (Ruscio, 2000). The discussion of whether “statistical” methods of data combination or "clinical" methods are more effective when attempting to predict behavior has been relevant for more than half a century (Ayres, 2007; Meehl, 1954). Paul Meehl (1954) tested this question and argued that the debate over whether “statistical” versus “clinical” methods yield better predictions. Meehl believe both approaches needed to be studied thoroughly and independently of the context of the prediction.

Numerous studies suggest that predictions based on human judgment typically do worse than statistical formulas in regard to the efficacy of these two approaches (Ayres,

2007; Dawes, Faust, & Meehl, 1989; Kahneman & Tversky, 1973; Meehl, 1954). In addition, Goldberg (1991) indicates that statistical prediction is superior to clinical prediction due to the desirable properties of statistical techniques and undesirable cognitive biases of human judges. Therefore, statistical equations are seen to be more effective in identifying relationships amongst variables when compared with human judgment; whereas, the cognitive biases associated with human judges lower the accuracy of identifying significant relationships (Ruscio, 2000).

In the context of professional sports, there has been an increasing necessity to incorporate statistical analysis into the decision-making of selecting potential employees, or in this context, athletes. There have been changes over the years in the evaluation of potential talent due to the advancements in technology and improvements in the accuracy of understanding which physical characteristics are measured (Wolfe, Wright, & Smart,

2006). One of the most notable uses of statistics to assist in the assessment and management of players in the business of sport can be found in Major League Baseball with the story of the 2002 Oakland Athletics, depicted in the book Moneyball: The Art of

Winning an Unfair Game (Lewis, 2004).

The Oakland Athletics (A’s) were attempting to break the tradition of heavily relying on talent scouts to predict future performance based on observed potential skills and physical attributes (i.e., clinical approach). In an effort to be salary cost effective, the

A’s implemented a statistical approach to focus on past performance as a predictor of future performance, rather than rely on talent scouts’ “clinical experience” in selecting potential athletes (Wolfe et al., 2006). The use of statistics in the game of baseball brought a new paradigm of addressing how teams manage players by using science to

3 support decisions. This new statistical approach was labeled “Sabermetrics” by combining the acronym for the Society for American Baseball Research (SABR) and the

Latin suffix for measurement.

“Sabermetrics” was spearheaded by Bill James, who pioneered baseball to be researched and analyzed as a type of science, which began a movement towards implementing a statistical approach to decision-making within professional baseball teams (Schwarz, 2004). The evidence-based practice of drafting, retaining, and trading players based on previously obtained statistics drastically improved the A’s’ overall games won, playoff appearances, and fan attendance, propelling them near the top in all three categories. Even though Oakland had one of the smallest markets in the league, they were competing with, and beating, teams that had a much larger team salary. Historically, the higher a team’s salary is the more wins they acquire (Cullen, Myer, & Latessa, 2009).

The implementation of statistical analysis into the decision-making about selecting players by the Oakland Athletics emphasized the benefit of using an evidence-based practice over the subjective, clinical approach that Major League Baseball scouts had been relying on for so long.

The National Football League

The National Football League (NFL) is similar to Major League Baseball when deciding whether to select potential athletes based on prior performance-related criteria or the judgment of personnel with years of experience. However, statistics for football are not as easily quantified as baseball is due to a player’s contribution to team performance.

Football teams largely depend on each other to succeed during game play more than baseball teams do. For example, the need for a center to snap the football and the

4 offensive line to block opposing players versus waiting for a ball to be hit towards an individual defensive player. Therefore, individual statistics will not be as readily available to team executives and personnel within the NFL as they are in baseball. Thus, the NFL should begin to develop its own implementation of “sabermetrics” that best identifies a player’s unique skill set based on the individual position.

The NFL consists of 32 privately owned franchises that compete at the highest level of professional American football in order to be named the league’s Super Bowl

Champion. In an effort to field the very best teams, the NFL conducts an annual draft each spring, giving the 32 franchises an opportunity to select rookie athletes from a pool of collegiate football players (McGee & Burkett, 2003). The NFL draft utilizes a reverse order ranking system based on the previous NFL season’s final standings. The team with the worst overall win-loss record receives the first overall draft pick in the upcoming season’s NFL draft. The second lowest overall win-loss record is allotted the second overall draft pick, and so forth until all the teams that did not make the playoffs the prior season have been allotted their respective draft picks.

For the teams that did make the playoffs the previous season, the remaining draft picks are awarded in order of team playoff record with the teams that lost earlier in the playoffs receiving earlier draft picks, based on in which playoff round they were eliminated. The Super Bowl winning team is allotted the final draft pick of the first round. The reverse-order draft allows the least successful franchises the opportunity to select the best amateur talent with the hopes of enhancing the league’s competitive balance, theoretically lessening the differences between the best and worst teams (Berri

& Simmons, 2009).

The player draft selection process within the NFL is closely tied to financial implications for each team, with the current average NFL team’s value exceeding 2.5 billion dollars, considering ticket prices, merchandise sales, sponsorships, television deals, etc. (Badenhausen, Ozanian, & Settimi, 2008). In terms of the NFL draft, the earlier a player is selected the more money he stands to make, with the average NFL player salary of 2.1 million dollars (Badenhausen, 2016). An NFL Players Association representative in 2000 informed McGee and Burkett (2003) that the average signing bonus and salary for a first-round draft pick in 1999 were $4,490,700 and $1,341,690, respectively. Whereas, a seventh-round draft pick’s average signing bonus and salary were $23,830 and $255,240, respectively [(phone interview with McGee, 2003).]

Therefore, an accurate assessment of prospects before the NFL draft gains importance when considering the amount of money being risked for selecting a rookie player. One study specifically investigated whether teams find the most “value” (i.e., level of NFL performance associated with monetary worth) in the NFL draft when selecting players and suggested that earlier picks in the draft are often not worth the amount of money spent to acquire that player in regard to NFL performance (Massey &

Thaler, 2005).

NFL Scouting Combine

Prior to the NFL draft, the league holds a week-long event, known as the NFL

Scouting Combine, which allows personnel such as coaches, team executives, and franchise owners from the 32 organizations to meet and evaluate approximately 350 of the top prospects in the upcoming NFL draft without National Collegiate Athletic

Association (NCAA) restrictions that prohibit contact with collegiate athletes (McGee &

Burkett, 2003; Robbins, 2010). The NFL Scouting Combine is designed to evaluate the athletic ability, health, and mental acuity of the collegiate players through standardized performance measures under controlled conditions, thereby creating a fair and unbiased assessment in one location (Kuzmits & Adams, 2008; Robbins, 2010). The NFL Scouting

Combine consists of the following six individual physical performance tests: forty-yard dash with times electronically recorded at the ten-yard line and twenty-yard line, vertical jump, 225-pound bench press, broad jump, three-cone drill, and the twenty-yard proagility shuttle.

Multiple studies have concluded that the six individual physical performance tests are valid measures of athletic ability; including upper body strength, lower body strength, speed, lateral quickness, and jumping ability (Arthur & Bailey, 1998; Baechle & Earle,

2000; Beckenholdt & Mayhew, 1983; Berg, Latin, & Baechle, 1990; Black & Roundy

1994; Chapman, Whitehead, & Binkert, 1998; Costill, Miller, Myers, Fry & Kraemer,

1991; Kehoe, & Hoffman, 1968; Madole, Rozenek, Lacourse & Garhammer, 1997;

Mayhew et al., 1995; Mayhew et al., 1999; Robertson & Flemming, 1987; Semenick,

1990).

As an employment selection device, the NFL Scouting Combine has been questioned as not being valid in terms of predicting actual player performance (Kuzmits

& Adams, 2008; McGee & Burkett, 2003). Although the individual performance measures during the Combine may not exactly simulate a player’s potential skill set during game play (i.e., playing with equipment, formations, play calls, etc.), the Combine is still used as a platform to assess players’ physical abilities as a predictor of their success at the professional level (Sierer, Battaglini, Mihalik, Shields, & Tomasini, 2008).

NFL Combine Studies

Multiple studies have been conducted to investigate the relationship between performance at the NFL Scouting Combine and various performance measures (Kuzmits

& Adams, 2008; Lyons, Hoffman, Michel, & Williams, 2011; McGee & Burkett, 2003;

Mulholland & Jensen, 2014; Robbins, 2010; Sierer et al., 2008). Robbins (2010) examined the validity of using Combine performance data as a predictor of draft order selection. The study specifically looked at the predictive ability of NFL Scouting

Combine data in its raw form, compared to when the data had been normalized for 17 different positions on the football field. Robbins’ primary finding was that, whether raw or normed, the ability to predict draft order using the physical performance measures from the NFL Scouting Combine is questionable at best. However, the study did suggest that the forty-yard dash, vertical jump, and broad jump appeared to be the best predictors of draft order selection (Robbins, 2010).

Sierer et al. (2008) examined Scouting Combine player performance differences between drafted and undrafted collegiate players who participated during the 2004-2005

NFL Scouting Combine. The purpose of the study was to determine if drafted collegiate football players differed significantly in height, weight, and six physical performance measures than undrafted players across three separate position categories; skill position

(wide receivers, defensive backs, and running backs), big skill position (linebackers, tight ends, and defensive ends), and linemen (center, offensive guard, offensive tackle, nose tackle, and defensive tackle). Quarterbacks were not included in the study. Independent t- tests from the study suggest that drafted players from the skill positions performed

8 significantly better than undrafted players in the forty-yard dash, vertical jump, twenty- yard shuttle, and three-cone drill.

Sierer et al. (2008) also suggested that drafted players from the big skill positions performed significantly better in the forty-yard dash and three-cone drill than their undrafted counterparts. Likewise, drafted players in the linemen position category performed significantly better in the forty-yard dash, bench press, and three-cone drill than undrafted players. Therefore, Sierer et al. (2008) suggest that, in an effort to increase the chances of being drafted, collegiate players should prepare as much as possible for a greater performance on the NFL Scouting Combine physical performance measures based on the player’s position. However, it should be noted that being drafted does not equate to having success in the NFL.

Similarly, McGee and Burkett (2003) sought to determine whether a relationship exists between a player’s performance on the NFL Scouting Combine measures and draft order across seven different football position categories: quarterbacks, offensive line, defensive line, wide receivers, running backs, linebackers, and defensive backs. The study only included players drafted and derived regression equations to predict in which round a player would most likely be drafted based on his performance on the Combine measures.

Results from the study suggest the most significant predictors for running backs, wide receivers, and defensive backs are the three-cone drill, height, weight, ten-yard dash

(split-time from the forty-yard dash), and vertical jump. Whereas, the most significant predictors from the NFL Scouting Combine for both offensive and defensive linemen are height, weight, bench press, broad jump, and three-cone drill. As for quarterbacks and

9 linebackers, the study suggests that the most significant predictors are three-cone drill for quarterbacks, with weight and forty-yard dash being the most predictive for linebackers.

Ultimately, players selected in the first and second rounds of the NFL draft were collectively taller, heavier, stronger, and faster in all of the Combine performance measures when compared with players drafted in the later rounds (McGee & Burkett,

2003).

Mulholland and Jenson (2014) focused on one specific football position, tight end, in their study to examine the best quantitative factors that predict subsequent NFL draft order and NFL career success. The study used data available to NFL teams before the NFL draft between the years 1999 to 2013, including the height, weight, NFL

Scouting Combine performance results, and collegiate performance. Mulholland and

Jensen (2014) created their own NFL career success variable measured by the total number of games started, total career receptions, total career receiving yards, and total career touchdowns to develop an NFL career score and an NFL career score per game, intended to capture a player’s average productivity.

Mulholland and Jenson (2014) analyzed the data using both linear regression and decision trees to select the variables that best predicted NFL draft order and NFL career success. The results for predicting NFL draft order suggest that NFL scouting personnel seem to focus more on measures of size and performance at the NFL Scouting Combine, with the forty-yard dash being the most significant predictor of draft order. As for predicting NFL performance and career success, the authors suggest that the most predictive measure was the broad jump for the tight end position. Mulholland and Jenson

(2014) write that the pre-draft measures most predictive of NFL draft order are not

10 necessarily most predictive of NFL career success, suggesting that current drafting strategies are erroneous.

Relative to the prior study, one group sought to investigate whether a player’s past performance (in collegiate football) or signs of physical ability (in the NFL Scouting

Combine) best predicts NFL career performance (Lyons et al., 2011). Specifically, the authors examined the validity of past performance and signs of physical ability as accurate predictors of future NFL success. The study included 764 collegiate football players across multiple positions - except punters, kickers, and offensive linemen - over a three-year span. Correlations suggest that a player’s performance in college football is more strongly related to future performance than are the raw physical ability tests at the

Combine. However, in addition, the forty-yard dash was significantly related to player performance in the NFL over the three years observed. Lyons et al. (2011) further expanded past research through their ability to show that past collegiate performance is more valid as a predictor of NFL performance than physical ability tests.

Kuzmits and Adams (2008) investigated the validity of the NFL Scouting

Combine as a predictor of NFL performance, and sought to answer the question of whether performance at the Combine in fact correlates with subsequent success as a professional football player. They studied only quarterbacks, wide receivers, and running backs who attended the Combine and were drafted during a six-year study period. The authors’ objective was to examine whether a relationship existed between NFL Scouting

Combine measures and NFL success. The study’s NFL success measure was derived from ten variables: a player’s draft order, salary in first three years, games played during

11 the first three years, and averages of player performance statistics during the first three years of the NFL.

There were only two significant correlations for quarterbacks: positive relationships of vertical jump and broad jump with draft order, meaning that the better a quarterback did on the vertical jump and broad jump the greater the likelihood of that player being drafter earlier. However, the authors concluded that the Combine failed to show consistent significant relationships with the measures of success.

Similarly, results for wide receivers yielded two significant correlations: positive correlations between both the ten-yard and twenty-yard (split-times derived from the forty-yard dash) with subsequent draft order. Like the quarterback position, the study suggests that the NFL Scouting Combine measures are largely unrelated to wide receiver success measures used in the study (Kuzmits & Adams, 2008).

As for the running backs, strong correlations were observed will all three sprint times (i.e., ten-yard, twenty-yard, and forty-yard dash), which suggests that sprint times are predictive of NFL success. Kuzmits and Adams (2008) found that the majority of the

NFL Scouting Combine measures failed to show significant correlations with measures of NFL success. They suggest the Combine measures lack any meaningful predictive ability of performance in the NFL.

Purpose and Hypotheses

The present study continues to build on prior research by further investigating whether a collegiate player’s performance at the NFL Scouting Combine predicts success while playing at the professional level. The current study focuses on predicting success for eight different position groups across the National Football League over a six-year

12 period. Given that much emphasis is placed on the individual player’s performance at the

Combine, it seems logical to examine the ability of the performance measures to predict future success. Similar to Kuzmits and Adams (2008), the purpose of the study is to answer the question of whether or not performance at the NFL Scouting Combine can statistically predict individual player success in the National Football League. However, the current study utilizes two independent success variables (years of experience and post-season accolades) to account for a player’s success in the NFL throughout their career. The following hypotheses will be tested:

Hypothesis 1. The forty-yard dash and bench press will be significant predictors of NFL success amongst offensive linemen, given the speed and strength required to compete at the professional level.

Hypothesis 2. The forty-yard dash and bench press will be significant predictors of NFL success amongst defensive linemen, given the speed and strength required.

Hypothesis 3. The forty-yard dash and vertical jump will be significant predictors of NFL success amongst wide receivers, given the speed and jumping ability required.

Hypothesis 4. The forty-yard dash and vertical jump will be significant predictors of NFL success amongst defensive backs, given the speed and jumping ability required.

Hypothesis 5. The forty-yard dash and twenty-yard shuttle will be significant predictors of NFL success amongst running backs, given the speed, agility and quickness required.

Hypothesis 6. The forty-yard dash and three-cone drill will be significant predictors of NFL success amongst linebackers, given the agility and quickness required.

Hypothesis 7. The forty-yard dash and broad jump will be significant predictors of NFL success amongst tight ends, given the speed and ability to generate lower body power required.

Hypothesis 8. The forty-yard dash and three-cone drill will be significant predictors of NFL success amongst quarterbacks, given the speed, agility, and quickness required.

CHAPTER 2

METHODS

Methods

Data Collection

This study utilizes secondary data: results of the NFL Scouting Combine performance measures, years played in the NFL, and post-season accolades (awarded by the NFL) for each player. Data from the Combine were collected from pro-football- reference.com, a commercial web site devoted to a wide variety of historical and current data on NFL players, teams, and prospects. Data from the website are deemed accurate.

In addition, the need for the institutional review board is considered a nonissue given that the individual names of players who participated will not be revealed and data used in the study can be found in various public access domains.

Participants

Participants for this study include NFL Scouting Combine invitees who participated at the Combine between the years 2004 and 2009. A total of 1,902 collegiate football players took part of the study. However, only 917 players completed all of the physical ability measures and were included in this study. The players were categorized into eight different football position groups based on the player’s labeled position at the

Combine: offensive linemen (OL, n = 202), defensive linemen (DL, n = 178), wide receiver (WR, n = 49), defensive back (DB, n = 176), running back (RB, n = 97),

15 linebacker (LB, n = 129), tight end (TE, n = 74), and quarterback (QB, n = 12). The offensive linemen position group consists of offensive centers, guards, and tackles. The defensive linemen position group consists of defensive tackles and defensive ends. The defensive back position group consists of cornerbacks, strong safeties, and free safeties.

Kickers and punters were not included in the study.

NFL Combine Physical Ability Tests

Forty-Yard Dash

Electronic timing devices are placed at the starting line, ten-yard line, twenty-yard line, and forty-yard line. The participant begins in a three-point stance, or “sprinter” stance at the starting line. After the participant hears, “You can go” from the Combine drill instructor, he must hold for a two second count before running. The timer will start when the participant’s down-hand separates from the surface. The participant will then sprint forty yards as fast as possible. Each participant will run the forty-yard dash twice with an estimated 10-15 minute wait between attempts. Sprint times are recorded for each participant at the ten-yard line, twenty-yard line, and forty-yard line as the participant passes through the electronic timing devices. The participants’ sprint times are recorded to the nearest one-hundredth of a second. The forty-yard dash is a measure of anaerobic power, acceleration, and speed from a static position (Arnold, Brown, Micheli, & Coker,

1980).

Vertical Jump

Participants begin with both feet flat on the ground in front of a pole with a number of moveable plastic “vanes” or “flags,” typically a Vertec (Sports Imports,

Columbus, Ohio), used to measure height in inches. With their dominant hand,

16 participants will reach straight up in the air as high as possible with the bottom of the plastic “vanes” touching their fingertips to establish the standing reach height. The participant is then instructed to jump straight up from a standing two-footed position and swat the highest “vane” possible on the Vertec with his dominant hand. Prior to the jump, participants are allowed to swing their arms and dip their knees; however, they cannot shuffle their feet before takeoff as this will result in a scratch and the jump will not count.

Each participant is allowed two jump attempts to touch the highest flag-marker on the

Vertec possible. The participant’s vertical jump is measured by subtracting the standing reach height from the height of the highest “vane” hit on the Vertec. The vertical jump performance test is a measure of leg strength and anaerobic power (Barker et al., 1993).

Bench Press

Participants complete as many bench press repetitions at 225-pounds as possible, until they can no longer complete a repetition. To be considered one complete repetition, the participant must lower the 225-pound bar to his chest, with a brief pause once bar is slightly touching the chest, followed by an upward push bringing the bar back to the starting position of arms being fully extended. The 225-pound bench press to fatigue measures an athlete’s upper-body muscular strength (McGee & Burkett, 2003).

Broad Jump

Participants jump horizontally for a maximal distance from a two-footed position.

The participant will start with both feet completely behind the start line, marked “zero inches.” Prior to jumping, the participant may swing arms and bend knees but must have both feet on the ground. When the participant is ready, he will jump horizontally and land as far away from the start line as possible. Upon landing, the participant must maintain

17 control and land balanced with both feet planted. The participant may fall forward, but not backwards. Participants receive two attempts at the standing broad jump. Each participant’s jump is measured from the start line to the heel of the foot nearest to the initial jump line. Jump distances will be measured to the nearest whole inch. The broad jump physical ability test measures leg strength and power (Beckenholdt & Mayhew,

1983).

Three-Cone Drill

Three small, plastic cones are positioned five yards apart in the shape of an upside down “L.” The participant begins by standing behind the starting line at cone one. When the participant is ready he will sprint as fast as possible directly forward five yards to touch the second cone with his hand and immediately return to the first cone. The participant will then sprint towards the second cone and, without stopping, change direction and sprint laterally to the right to touch the third cone. Upon touching the third cone, the participant will circle that cone counter-clockwise and immediately sprint back around cone two as fast as possible past cone one to the starting line. The time is measured from when the participant starts sprinting to when he passes the first cone after completing the drill. Each participant’s three-cone drill time is recorded to the nearest one-hundredth of a second. The three-cone drill measures agility, ability to change direction, and acceleration power (Kuzmits & Adams, 2008).

Twenty-Yard Shuttle

The twenty-yard proagility shuttle begins with the participant in a 3-point stance with legs straddling a line on the field equally. Facing the drill director, the participant starts with having his hand squarely on the line he is straddling, and hold the position for

2 seconds. Once the participant is told, “You can go” by the drill director, he will run 5 yards to the right and touch the line with his right hand. The participant will then change direction and sprint back to the left ten yards, and touch the line with his left hand. After the participant touches the left line, he will again change direction and sprint through the finish line, which is the starting line of the drill. Participants will complete two attempts, one run to the right and one run to the left, with the average time of both being recorded to the nearest one-hundredth of a second. The twenty-yard shuttle measures an athlete’s ability to increase and decrease speed rapidly, ability to change direction quickly, and anaerobic power (McGee & Burkett, 2003; Robbins, 2010).

Physical Attributes

Each participant’s height and weight are obtained at the NFL Scouting Combine and recorded in inches and pounds. Although these measurements may not reflect measures of performance, they can dictate success across the different positions; therefore, height and weight will be included in the current study.

Success in the NFL

The success measure is a combination of the longevity of the participant’s career in the National Football League (i.e., years of experience) and whether or not the participant has been awarded a post-season accolade, as described below:

Years of Experience

Participants must have played for at least six years in the NFL to be included in the success measure. Six years of experience was chosen as the success measure because it is roughly double the average years of experience for an NFL player, which is approximately 3.5 years according to the National Football League Player’s Association

(2017). For the current study, the participant must have been on the field and played in at least one game during that regular season to get credited for the year of experience playing in the NFL rather than simply being on the team.

Post-Season Accolades

The following accolades are included in the study: All-Pro selection, Pro-Bowl selection, Most Valuable Player, Offensive Player of the Year, Defensive Player of the

Year, and winning a Super Bowl (i.e., being on a Super Bowl winning team). Post-season accolades were included in the success measure to represent individual player performance compared to other players’ performance during the same regular season and post-season. The All-Pro, Most Valuable Player, Offensive Player of the Year, and

Defensive Player of the Year accolades have been chosen and voted on by the Associated

Press since the 1950’s and 1960’s. Voting is completed by 50 media members from around the country who cover the NFL regularly and who are independent of the NFL

(Wilner, 2016). Players are awarded a Pro-Bowl selection by votes of other current players, coaches, and fans.

An individual who played on a Super Bowl winning team was included, given that the objective of the NFL is to win the Super Bowl. With the NFL acknowledging players with awards based on their performance during that respective season, the NFL has essentially created their own performance based success measurement. Individual player performance statistics for games played are not available to compare across the different positions chosen for the current study; therefore, substituting player performance accolades for individual statistics gives a more universal success measure.

CHAPTER 3

RESULTS

Results

The data were analyzed using the statistical software SPSS (IBM Corp.,Version

24.0). A correlation matrix was first computed to identify significant relationships between the physical ability measures and success variables. Each of the eight Combine physical ability measures was significantly correlated (p < .05) with each of the other physical ability measures with moderate to large effect sizes. Regarding the success variables, years of experience was the only measure significantly correlated (p < .05) with all of the physical ability measures, except weight. Whereas, both accolades and success in the NFL were significantly correlated (p < .05) with four of the physical ability measures: forty-yard dash, vertical jump, three-cone drill, and twenty-yard shuttle. For complete correlations refer to Table 1.

Table 1. Correlations Amongst Physical Ability Tests and Success

Height Weight 40yd Vertical Bench Broad 3cone Shuttle Years Exp Accolades Success Height 1 Weight .73** 1 40-yard Dash .61** .89** 1 Vertical Jump .43** -.64** -.73** 1 Bench Press .34** .60** .43** -.27** 1 Broad Jump -.45** -.74** -.82** .80** -.35** 1 3-cone Drill .48** .80** .81** -.64** .40** -.73** 1 20-yard Shuttle .46** .73** .75** -.68** .34** -.70** .81** 1 Years Experience .09** .05 -.10** .12** .11** .10** -.10** -.12** 1 Accolades .05 .00 -.07* .10** .01 .07* -.08* -.09** .52** 1 Success .06 .02 -.06* .09** .02 .06 -.07* -.06 .56** .90** 1 M 74.13 254.28 4.81 32.37 21.92 112.49 7.34 4.41 4.06 .18 .15 SD 2.65 44.65 .32 4.42 6.14 9.19 .41 .27 3.5 .38 .36 Range -.01 to 1 -.01 to 1 -.01 to 1 -.01 to 1 -.01 to 1 -.01 to 1 -.01 to 1 -.01 to 1 .1 to 1 .1 to 1 .1 to 1 **. Correlation is significant at the .01 level (2-tailed). *. Correlation is significant at the .05 level (2-tailed).

Depending on the relationship between the different physical ability measures, the interpretation of the sign of the correlation may not be obvious. For example, a player’s weight was positively correlated with their performance on the forty-yard dash but negatively correlated with their performance on the broad jump. Thus the heavier the player, the slower the time on the forty-yard dash and shorter distance measured on the broad jump. Lower scores are preferable for the forty-yard dash, three-cone drill, and twenty-yard shuttle physical ability measures. Conversely, higher scores are preferable for the vertical jump, broad jump, and bench press physical ability measures.

Multivariate Analysis of Variance

A multivariate analysis of variance (MANOVA) was then conducted to identify whether position groups differ from each other in terms of the Scouting Combine physical ability tests and the study’s success variables. The position an athlete played had a significant effect on the results of all the eight Combine physical ability measures, as well as the three success measures used in the study. The MANOVA was significant demonstrating positions differed on the measures, F(77, 5394.63) = 42.01, p < .0001;

Wilks’ Λ = .06.

Multiple Regressions

Given that a player’s position has an effect on performance and success, multiple regressions were then separately conducted for each position to identify statistical significance for different physical ability measures on overall success. Four of the eight football positions had at least one statistically significant predictor of success. For offensive linemen, the regression model was significant, R2 = .12, F(8, 193) = 3.18, p =

.002, with three physical ability measures uniquely predicting success. Specifically, an

23 offensive lineman’s performance on the forty-yard dash, b = -.23, t = -2.41, p = .02, twenty-yard shuttle, b = -.26, t = -2.44, p = .02, and weight, b = .22, t = 2.59, p = .01, were statistically significant predictors of overall success in the NFL.

The multiple regression for the defensive back position was significant, R2 = .13,

F(8, 167) = 3.06, p = .003, with the forty-yard dash, b = -.22, t = -2.42, p = .02, and the three-cone drill, b = -.29, t = -3.39, p = .001, as significant independent predictors of success. The model for the running back position was also significant, R2 = .17, F(8, 88)

= 2.26, p = .03, with only the forty-yard dash, b = -.58, t = -3.8, p = .001, being an independent predictor of success. Similarly, the model for the linebacker position was significant, R2 = .14, F(8, 120) = 2.41, p = .02, with the three-cone drill, b = -.22, t = -

2.22, p = .03, as the only significant independent predictor of success.

With regard to the other four position groups, the regressions were not significant; defensive linemen, R2 = .05, F(8, 169) = 1.17, p = .32, wide receivers, R2 = .11, F(8, 40)

= .61, p = .77, tight ends, R2 = .19, F(8, 65) = 1.89, p = .078, and quarterbacks, R2 = .57,

F(8, 3) = .5, p = .81. However, the lack of significant findings could be due to the small sample size particularly for tight ends and quarterbacks. To see the full results for eight position group regression models refer to Table 2.

Table 2. Position-Specific Regressions

Positions R2 F (df) p Offensive Linemen .12 (8, 193) 3.18 .002 Defensive Linemen .05 (8, 169) 1.17 .32 Wide Receiver .11 (8, 40) .61 .77 Defensive Back .13 (8, 167) 3.06 .003 Running Back .17 (8, 88) .03 .03 Linebacker .05 (8, 120) .02 .02 Tight End .19 (8, 65) 1.89 .08 Quarterback .57 (8, 3) .5 .81

CHAPTER 4

DISCUSSION

The NFL Scouting Combine is held to be the premier event in which potential collegiate football players are able to demonstrate their athletic ability to NFL team executives and personnel before the NFL draft. The physical ability tests conducted at the

Combine are specifically intended to measure a player’s important physical attributes and skills that are needed to be achieve success in the NFL. Therefore, the current study implemented a “statistical” approach to examine the extent to which Combine physical ability tests predict player success in the NFL.

Similar to Kuzmits and Adams (2008), the majority of the NFL Scouting

Combine physical ability measures failed to show large correlations. In the current study, correlations that were found to be statistically significant between overall success and the

Combine’s physical ability tests yielded weak effect sizes (vertical jump and three-cone drill) when analyzed across all eight football positions, rather than analyzing the relationships separately for each football position, such as with the multiple regressions.

Using multiple regressions, it was possible to predict future NFL success differentially by position. Specifically, an offensive lineman’s weight and performance on the forty-yard dash and twenty-yard shuttle directly impacts the player’s chances of being successful at the professional level. Heavier, faster, and more agile linemen were more successful. This finding is different from the hypothesis that the most significant

Combine measures for an offensive lineman would be the forty-yard dash and the bench press. However, the bench press was non-significant, which was surprising given the relative upper body strength needed during position-specific game play, such as pushing and moving the opposing defensive linemen. Although, it is possible there was limited variance in the bench press given the upper body strength needed to compete at the professional level across the position. This finding may indicate that NFL executives and personnel should examine an offensive lineman’s ability to change speed and direction quickly, in combination with their weight, in order to best predict future success at that position when selection a potential player.

The three other position groups that had statistically significant prediction

(defensive backs, running backs, and linebackers) highlight the necessity of a player’s overall speed and lateral agility to be successful in the professional level. For a defensive back, a player’s performance on the forty-yard dash and the three-cone drill are the most foretelling predictors of a player’s future success. A defensive back must be able to run, stop, and change direction rapidly as they attempt to cover offensive players, such as wide receivers, across the playing field. However, the study did not find a defensive back’s ability to jump as a significant predictor of success as hypothesized. This was surprising given the defensive back duties include jumping to catch, or swat, the football out of the air in an attempt to deny the pass catcher the completion of the pass.

Regardless, the study suggests that performance on the forty-yard dash and the three-cone drill at the Combine may directly impact a defensive back’s chances of becoming a successful professional football player.

Likewise, the running back position’s performance on the forty-yard dash was statistically significant, again highlighting the necessity for speed at the professional level. This finding is not surprising given that a running back’s job is to run with the football towards the end zone in order to advance the ball, although the lack of statistical significance amongst the agility measures (i.e., three-cone drill and twenty-yard shuttle) is surprising. Traditionally, a running back is not only supposed to be fast but should be quick and agile as well in order to avoid being tackled and out run defensive players.

Finally, it is not surprising that a linebacker’s performance on the three-cone drill was statistically significant, as the skill set typically needed to be a successful linebacker includes the ability to change direction quickly with powerful acceleration. The linebacker’s duties primarily reside within the first five to ten yards from the line of scrimmage, such as tackling a running back or dropping into pass coverage. Therefore, the study suggests that a linebacker’s performance on the three-cone drill may predict future success in the NFL.

Overall, it was surprising the study failed to find statistical significance for the defensive linemen position given the position demands similar skill sets and performance based characteristics as the offensive linemen. As well, the tight end position failed to achieve statistical significance, although the lack of findings could be explained by the small sample size of 74 players.

As for the wide receiver and quarterback positions, both had extremely small sample sizes of those who completed all of the Combine measures (WR, n = 49 and QB, n = 12), which may have hindered the ability to find statistical significance for these positions. The majority of players amongst these two position groups did not attempt the

28 bench press measure and, therefore, were not included in the study. Although, the regressions run for both the wide receivers and quarterbacks could have been seen as statistically significant had the bench press measure been excluded in the study for their respective positions.

The current study found an overlying importance of the forty-yard dash as a significant predictor of future NFL success, much like previous research has (Kuzmits &

Adams, 2008; Lyons et al., 2011; McGee & Burkett, 2003; Mulholland & Jensen, 2014;

Sierer et al., 2008). The current study differs from past research by offering an in-depth look at the differences between the eight different football positions and which Combine physical ability tests are most predictive of success when potentially selecting a player, based on a player’s position. Although McGee & Burkett (2003) analyzed regression equations for eight different positions, they were only focused on determining which round a player would be drafted rather than their potential success playing at the professional level. In addition, the current study contributes to Meehl’s (1954) ongoing debate over whether a statistical approach yields better predictions than a clinical approach by analyzing pre-draft statistics. These differences between statistical predictions and clinical predictions should be noted and used amongst NFL executives and personnel to better the selection process across relevant position groups.

Limitations

Alas, the findings from this study alone may not hold enough power or support for NFL personnel and executives to select potential athletes based solely on their performance at the NFL Scouting Combine. It is important to note that the Combine physical ability tests used in the study measure only physical capabilities and not actual

29 football-playing ability, which may limit the implications of the current findings. The

Combine assesses a player’s speed, agility, and strength in a non-contact environment without the conditions of playing in an actual game situation. Therefore, the physical ability tests at the Combine are lacking the validity to account for game-like situations.

For example, a running back may perform extremely well in the forty-yard dash but lack the running ability needed in an actual game, such as making instantaneous cuts and reacting to the defense.

An important component of the NFL Scouting Combine that was not analyzed in this study, which may influence the way NFL executives and personnel select potential players, is the additional drills and on-field workouts that players are asked to perform in.

These additional drills have the player display multiple football skills and techniques that are position specific. For instance, wide receivers are asked to run a variety of routes on the field and catch the football in order to showcase their position related ability. Vice versa, quarterbacks are asked to showcase their passing ability by throwing the football to the wide receives as they are running various routes. However, players performing these drills are not wearing the full football equipment (i.e., helmet, shoulder pads, etc.) required during a game situation; nor are they experiencing the physicality of the game by being tackled. These additional drills and workouts are not being quantified based on performance, as the Combine physical ability tests are. Instead, NFL scouts and personnel are clinically judging each player’s skill set while looking for intangibles that cannot be easily measured. One could even argue that the measure of success used is arbitrary given that many psychological variables, such as resiliency, commitment, and self-efficacy, are unmeasured. The need to move toward measuring psychological

30 variables becomes more inevitable, given that the Combine only predicted roughly 5–

19% variance of success and does not include how a player’s mind impacts the game.

Another limitation to the study, which may be overlooked, could be attributed to

Combine specific workouts and regimens that players are able to utilize prior to attending the NFL Scouting Combine. These Combine preparation programs are designed to enhance a player’s performance in the drills and workouts used during the Combine, which could lead to a normalization of the data.

Suggestions for future research would be excluding physical ability tests from the study that are not completed by the majority of the position, in order to garner a larger sample size. For instance, excluding the bench press measure from the wide receiver and quarterback position regressions. By excluding commonly unused Combine physical ability tests for each position the study could better target position specific performances and how those performances vary across positions when predicting future success in the

NFL. It is also possible to enhance the success variable used in the current study by rescoring the measure to be on a continuous scale rather than a binary scale. For instance, allocating a point system in which the post-season accolades can be better accounted for

(i.e., giving more points to players with All-Pro or MVP honors than a player that only played for a Super Bowl winning team). This could allow the success variable to find more statistical significance across all positions for more physical ability measures.

Additionally, a future direction for the study could include the Wonderlic test in the regression models along with the Combine physical ability tests and NFL success measures. The Wonderlic test is a psychological profile test administered to each player,

31 however, scores for the Wonderlic are not publicly available and are often deemed unreliable. For that reason the Wonderlic test was omitted from the current study.

Practical Applications

Much like how the Oakland A’s implemented “sabermetrics,” as described in

Moneyball (Lewis, 2004), the purpose of this study was to utilize a data-based approach to organizational decision making within the National Football League. By using regression equations coaches and personnel are able to identify which physical ability tests most affect an athlete’s potential success in the NFL based on their position and performance at the Combine. Likewise, the regression equations could be used to identify which physical ability tests have the least effect on potential success. For example, the twenty-yard shuttle was found to be the most important test to determine success at the offensive linemen position, whereas the bench press had little to no effect. This approach may change the way that NFL executives and decision makers bring relevant knowledge together to balance the use of available and appropriate information for position specific performance.

The study at hand strictly examined the physiological characteristics of the

Combine without regard to other contributing factors that are often involved in being successful in the NFL, such as an individual’s attitude, willingness to learn, or ability to work with teammates. With all things considered, numerous factors go into being a successful football player at the professional level (i.e., being drafted, having supportive coaches, not sustaining severe injuries, or competing against other players for playing time). Success in the NFL is not achieved easily and requires many of those factors to align for an individual player to be successful depending on their unique situation.

Regardless of a player’s position, football demands multiple physical and mental skills for a successful performance making it a complex sport to measure universally.

The NFL is arguably one of the best-run professional sport leagues in the country and maybe even the world. Given the amount of time, money, and additional resources that each of the 32 teams in the NFL commit to examining potential athletes, it would be logical to further investigate the main event in which player’s are asked to showcase their athleticism through a series of tests, drills, and workouts. Although, these physical ability tests do not fully encapsulate a player’s athletic ability when it comes to playing the game of football and, therefore, should be used in conjunction with a player’s past performance to best select a potentially successful player. The strength of using the statistical approach lies in the ability to be consistent, whereas the strength of human judgment lies in the ability to use information that cannot be easily quantified and analyzed as data. Thus, the study suggests that NFL executives and personnel implement a statistical model, in combination with professional judgment to account for intangibles and unquantifiable measurements, in order to select an athlete that has the most potential to be a successful player in the National Football League based on performance from the NFL Scouting

Combine and collegiate career.

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