On the Relationship Between Attacking Third Passes and Success in the English Premier League

Authors: Bret R. Myers; Brian Q. Coughlin

Corresponding Author:
Bret R. Myers
204 Eagle Glen Drive
Coatesville, PA 19320
bret.myers@villanova.edu
804-357-5876

Bret Myers is an assistant professor of management and operations at Villanova University. He also works as an analytics consultant for Toronto FC of Major League Soccer. Bret’s research and consulting is at the intersection of core sporting knowledge and the leveraging of data analysis to improve decision making for competitive advantage.

Brian Coughlin is a senior data analyst at Decision Resources Group in Exton, PA. He also serves as director of lacrosse operations at Villanova University. His passion lies in the field of analytics with a specific interest in mining data, analyzing statistics, and offering strategic recommendations that help organizations make better decisions.

On the relationship between attacking third passes and success in the English Premier League

ABSTRACT
This research examined how changes in attacking third pass behavior can impact a team’s ability to maintain leads and secure wins based on data collected from the 2011-2012 English Premier League Season. A team’s attacking third behavior is measured by the number of attacking third passes completed per minute. The results of this paper suggest that while teams tend to complete less passes in the final third when they are ahead in a match vs. being behind, there is evidence to suggest that a drop in attacking third pass behavior when ahead in a match will reduce the likelihood of maintaining a lead and securing three points.

Keywords: Soccer Strategy, Coaching Strategy, Sports Analytics, Soccer Analytics, Protecting a Lead, Staying Aggressive throughout a Match

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An Analysis of Weight Management and Motivation of Former and Present High School and College Football Players

 

ABSTRACT

The purpose of this study was to analyze the weight management practices and motivational orientation for participating in the sport of football from former and present high school and college aged football players. The study included an in-depth analysis of the practices of offensive and defensive linemen, because of the likelihood of these individuals having the most abnormal eating practices. The researcher also attempted to determine if there was a significant relationship between the eating patterns of all the players and their motivation to participate in football. The sample for the study consisted of former and present football players (N = 387) from three target populations: high school, college, and former players. The study was conducted over a period of 30 days in the month of June 2011. Surveys were returned at a rate of 95%. The results indicated differences in eating pattern and motivation among the four groups: former players, college players, high school players, and offensive and defensive linemen. Offensive and defensive linemen did not differ from other players on any of the motivation scales. The results also revealed correlations among the eating pattern and sport motivation scales.

Introduction

The research concerning weight management and motivation of former and present high school and college football players is a worthy subject for extensive research analysis. A 2003 study, conducted at the University of North Carolina, found that professional football players have a 52% greater risk of dying of heart disease than the general American population (7); it was noted that offensive and defensive linemen are three times more likely to die from heart disease than teammates who play other positions. Hargrove (6) conducted a study investigating the death of former NFL players (N = 3,850) who had died since 1955. The study reported the following findings:

•The average weight of National Football League (NFL) players had grown10% since 1985.

•The average weight of offensive tackles, the heaviest football players, had increased from 281 pounds in 1985 to 318 pounds in 2005.

•Compared to Major League Baseball (MLB) players, the rate of death before the age of 50 for NFL players was double that of the MLB players.

When college football players’ weights were compared to a cross section of similarly aged males, overweight and obesity were more prevalent amongst players (13). The average varsity high school lineman is expected to gain more than 50 pounds in 3 years to compete on the collegiate level (3). The 300-pound lineman is now common at the high-school level (11). An analysis of a 1985 Indiana State high school football championship game found that 7 players weighed more than 250 pounds; in a follow-up study in 2004, 50 players weighed more than 250 pounds, representing an increase of 43 players (16).

Weight Management

The National Strength and Conditioning Association (12) reported that football players need to increase the number of calories they eat a day to gain muscular mass, aiming for 18 to 20 times their maintenance calorie intake. To increase power and to fuel muscles football players often engage in binge eating behaviors. Binge eating disorder (BED) is exhibited through frequent binge eating episodes, combined with impaired control over eating, followed by remorse about the binge eating episodes within a 2-hour period (1). BED eventually leads to obesity and visceral abdominal fat, which is an essential factor to examine in football players because of its relation to metabolic syndrome, sleep apnea and high blood pressure (5).

Jonnalagadda, Rosenbloom, and Skinner (10) conducted a study to investigate the eating practices, attitudes, and physiology of 31 Division I college freshman football players. Results from the study revealed that players ate 3.6 times per day and ate out 4.8 times per week. Fast food was the most popular choice for eating out (55%). In a study on the prevalence of metabolic syndrome of 69 Division I college football players, the mean BMI of offensive and defensive linemen was categorized as obese, with a significant amount of fat in the abdominal area (13).

Motivation

Researchers have asserted that family members encourage athletes to perform well more than coaches do (2). Thompson and Sherman (21) stated that coaching style along with positive feedback can play a significant role in a player’s weight management practices and motivation player’s weight management behaviors and self-perception. Pressures from teammates, either real or imagined, can cause an athlete to accept the notion that extreme weight management practices as necessary to participate in the sport (41).

The self-determination theory (SDT) is a general theory for assessing an individual’s personality and motivational orientation. The objective of the SDT is to determine if an individual’s motivational behavior is non self-determined or self-determined (4). Non self-determined behavior is behavior that is controlled by external factors in which the individual experiences an obligation to behave in a specific way and feels controlled by a reward or by constraints (10). Self-determined behavior is described as an individual’s understanding and fulfillment of his or her needs by being able to make psychologically free choices (10).

Ryan (38) examined the effects of scholarship on a variety of male and female, scholarship and non scholarship athletes. Results indicated that scholarship football players had lower levels of IM than non scholarship athletes. Conversely, male wrestlers and female athletes on scholarship reported higher IM than non scholarship athletes. Sloan and Wiggins (39)conducted a study using the SMS to assess the motivational differences between61 college football players and 60 professional football players. Results revealed that, overall, players scored higher on IM subscales than on EM subscales (39). Professional football players scored higher on IM subscales than college players (39).

The purpose of this study was to analyze the weight management practices and motivational orientation for participating in the sport of football from former and present high school and college football players. The study included an in-depth analysis of the practices of offensive and defensive linemen, because of the likelihood of these individuals having the most abnormal eating practices. The researcher also attempted to determine if there was a significant relationship between the eating patterns of all the players and their motivation to participate in football.

Methods

Selection of Participants

Participants were selected from a convenience sample of 387 former and present football players. Emphasis was placed on the participation of offensive and defensive linemen because they were more likely to have the most extreme eating behaviors.

Instrumentation

The Yale Eating Pattern Questionnaire (YEPQ) is designed to diagnose a wide variety of eating behaviors of nonclinical populations (23). The scale consists of eight subscales: (a) uninhibited, (b) over snacking, (c) bingeing, (d)dieting, (e) satiation–full, (f) satiation–nausea, (g)satiation– guilty, (h) attributions to physical and emotional causes of weight problems. For the purpose of this study the uninhibited, over snacking,and bingeing scales were used to assess football player eating behaviors.

The Sport Motivation Scale Revised (SMSR) consists of six, 3-item subscales that measure three types of motivation: Intrinsic Motivation (IM), External Motivation, and A motivation (AMO) The IM subscale identifies athletes who practice sport to experience personal pleasure. The scale identifies EM-athletes who participate in sport for external purpose such as a prize (17). AMO identifies athletes who do not know why they practice, sport (17).

Procedures

The researcher obtained permission to conduct the study through a local university’s Institutional Review Board. Upon confirmation the researcher made initial contact with football camp administrators at the college and high school age level to explain the nature of the research and to obtain permission to administer the survey to players. Former football players were contacted by the researcher via telephone to explain the nature of the study and to answer any questions about consent.

Statistical Analysis of Data

Data for this study were analyzed using the Statistical Package for the Social Sciences software program (SPSS) version 17.0. (IBM, Chicago, IL). An alpha level of .05 was used for all statistical analyses. Demographic profile was analyzed through the use of descriptive statistics. The research design included three analyses. A Multivariate Analysis of Variance (MANOVA) was performed with the three eating habits scales from the YEPQ as the dependent variables and player group (high school, college, and former) and position group (linemen versus others) as the independent variables. To follow up a statistically significant main effect for player groups, three one-way Analysis of Variance (ANOVA) were performed (one for each eating habits scale) to determine where the differences between the player groups occurred. A follow-up honest significance test, Tukey’s honestly significant difference (THSD),was used to find which means were significantly different from one another.

MANOVA was used to analyze the differences in motivational orientation among the groups (types of football players and player positions). To follow up a statistically significant main effect for player group, six one-way ANOVAs were conducted: one for each of the six sports motivation dependent variables. These analyses were performed to determine which of the six dependent variables differed as a function of player group. A follow-up THSD was used to find which means were significantly different from one another. Pearson product-moment correlation coefficients were calculated to investigate the relationship between the YEPQ and SMSR subscale.

RESULTS

A total of 387 valid survey questionnaires were collected from former and present football players with a return rate of 95%. The study participants were equally distributed among the three player groups: 35.1% former players, 35.1%college players, and 29.7% high school players. Similarly, there were approximately equal numbers of offensive or defensive line players (50.6%) and players in other positions (49.4%). Most (69.3%) of the participants reported eating to maintain an ideal body weight for their position. The majority(73.4%) of participants also believed that unhealthy weight management practices pose a potential risk for football players. Most (72.9%) of the participants reported that receiving a scholarship or playing professional football was a career goal.

Coaches were the most likely individuals to influence a participant’s current weight management practices (47.3%), with parents and family also representing a significant influence (20.9%). Nearly all (85.3%) of the participants indicated that they would consider a weight management program after completing their football career, and very few (2.1%) had been diagnosed with an eating disorder.

Six of the scores in the SMSR scales had adequate reliability in this sample, whereas three did not. The internal consistency reliability coefficients for the intrinsic regulation (α = .74), extrinsic integrated regulation (α = .70), extrinsic identified regulation(α = .71), and a motivation (α = .72) scales from the SMSR were adequate, as were the reliability coefficients for the over snacking (α = .82) and bingeing (α = .81)scales from the YEPQ. The reliability coefficients for the extrinsic introjected regulation (α = .58) and extrinsic external regulation (α = .54) scales from the SMSR and the uninhibited scale (α = .48) from the YEPQ, however, were lower than the conventional criterion of .70. This finding represents a substantial limitation of this study, and the results related to these scales should be interpreted with caution.

DISCUSSION

Research Discussion One

The first research question asked if there were significant eating pattern differences among all groups of football players. The results indicate significant differences between high school, college, and former players on the eating pattern scales. High school players had higher scores on the uninhibited, over snacking, and bingeing scales than college and former players.The findings suggest that high school football players have more abnormaleating patterns than college and former football players. The findings support Henderson’s (8) examination of California’s Mater Dei high school football championship team in 2006; revealed that their starting offensive line outweighed the 1972 undefeated NFL Miami Dolphins’ Super Bowl championship team by 118 pound.

Descriptive statistics from this study’s demographic information sheet, support findings in the review of literature; statistics reveal that the coach (47.3%) was the most likely individual to influence players current weight management practices, followed by parents (20.9%). In relation, to parent and coach influence on high school football player’s weight management practices, peer pressure from teammates, either real or imagined,can cause athletes to accept the notion that extreme weight management practices as necessary to participate in the sport (21).

The findings also support body dissatisfaction research conducted by Pope(14). Adolescent males often feel pressure from social sources and the media to obtain the low body fat, “cut” or “ripped” muscular body (14). In relation, a significant amount of players from this study (69.3%)reported that they eat to maintain an ideal body weight for their position in football. In this case, high school football players eating patterns may express their desire to obtain the perceived prototype body they see in the media of football players.

Research Discussion Two

The second research question asked if there were significant eating pattern differences between all offensive or defensive linemen and other team players.Offensive and defensive linemen had lower scores on the uninhibited and bingeing scales compared to other players. The results indicate that smaller players who play positions other than offensive or defensive lineman have more abnormal eating patterns. The findings of the research support research conducted by Pope (15) on muscle dysmorphia. Males with muscle dysmorphia are obsessed with the idea that they are not muscular enough and see themselves as”skinny” or “too small” (15). In this case, smaller players who play position other than offensive/defensive line could be emulating perceived eating patterns of offensive/defensive linemen; in an attempt to obtain the prototype body to participate in football.

Research Discussion Three

Research question three asked if there were significant intrinsic or extrinsic motivational differences among all football players. High school and college players scored higher on the EM-introjected regulation and EM-external regulation scale than former players. The findings suggest that football players at the high school and college level have more non self-determined motivation than former players. The findings support research conducted by Hyman (9) on external influence student football players’ encounter in their participation in football. The findings are also supported by statistics in the demographic information sheet which show a large majority of players(72.9%) who reported that receiving a scholarship or playing professional football was a career goal.

A significant finding in the research was that college football players had higher mean scores on the EM-identified regulation, EM-integrated, and the IM-regulation scale than former and high school players. The finding suggests that college football players have more self-determined motivation than former and high school players. The findings are classic and supports Ryan’s(18) SDT which states, that intrinsic motivation can be improved with the introduction of performance-contingent rewards.

Research Discussion Four

The fourth research question asked if there were significant intrinsic or extrinsic motivational difference between all offensive and defensive linemen and other team players. The results indicate that offensive and defensive linemen did not differ from other players on any of the sports motivation scales. The findings suggest offensive/defensive linemen motivation to participate in football is no different in comparison to other team players. In this case, it was the researcher’s hypothesis that offensive/defensive linemen motivation to participate in football would be more non self-determined because they are routinely the heaviest players on a team. The results did not support the researcher’s hypothesis.

Research Discussion Five and Six

The fifth and sixth research questions asked if there was a significant correlation between eating patterns and motivation among all football players and if there was a significant correlation between extrinsic motivation and binge eating patterns among all football players. The results showed that there were significant correlations among the eating patterns and motivation scales.

Players with high scores on the YEPQ: uninhibited, overeating, and bingeing scale also had higher scores on the SMSR: EM-introjected regulation,EM-external regulation, AMO scales. The findings suggest that football players,who participate in football for non-self-determined reasons— to avoid criticism, to win a prize, or for no good reason, are also prone to abnormal eating patterns. Players with high scores on the YEPQ: bingeing scale and overeating scale tended to have lower scores on the SMSR: IM-regulation, EM-integrated regulation, and EM-identified regulation scales. The findings suggest that football players, who participate in football for self-determined reasons-to obtain personal goals, because its apart of you, to experience pleasure, do not show signs of abnormal eating patterns. In this sense performance contingent rewards in the form of food, can be introduced, for consistently adhering to the leisure activity or weight management plan.

CONCLUSION

The results indicate that there were significant eating pattern differences among the four independent groups. The results indicate that high school players had higher scores on the uninhibited, over snacking, and bingeing scales than did former players. College players-scores on all three scales were between high school and former players. Former players-had lower score on all three scales. The results also revealed that offensive/defensive linemen had lower mean scores on the uninhibited and bingeing scale compared to other player groups. Results indicate that high school and college players had higher scores on the EM-external regulation scale than former players. College players had higher IM-regulation, EM-identified regulation mean scores than high school and former players. Former players had lower EM-introjected regulation scores than high school and college players. Offensive and defensive linemen did not differ from other players on any of the sport motivation scales.

To investigate if there were correlations among the eating pattern and motivation scales, results revealed that individuals with higher scores on the uninhibited scale from the YEPQ tended to have higher scores on the SMSR, EM-introjected regulation, EM-external regulation, and the A motivation scale.Participants with higher on the over snacking scale tended to have lower scores on the IM-regulation, EM-integrated regulation, and EM-identified regulation,and higher scores on the EM-external regulation and A motivation scales.Participants with higher scores on the bingeing scale tended to have lower IM-regulation scores and higher EM- introjected regulation, EM-external regulation, and A motivation scores. A limitation is that this was a convenience sample and may not be representative of all players or former players.

APPLICATIONS IN SPORT

Because the coach was reported to have the most influence on players’weight management practices (47.3%); and players reported eating to maintain an ideal body weight for their position (69.3%); and because nearly all participants (85.3%) reported they would consider a reconditioning plan after their playing career is over; future research could investigate the role coaches can play in the establishment of reconditioning plans once a player’s football career ends. Future research also could focus on making players aware that BED is a diagnosed eating disorder.

Tables

Table 4.2. Descriptive Statistics for Demographic and Background Characteristics (N = 387)

Variable Frequency Percentage
Player group    
High school player 115 29.7
College player 136 35.1
Former player 136 35.1
     
Position group    
Not offensive or defensive line 191 49.4
Offensive or defensive line 196 50.6
     
Ethnicity    
African American 289 74.7
Caucasian 74 19.1
Hispanic 10 2.6
Other 14 3.6
     
Do you eat to maintain an ideal body weight for your position?
Yes 268 69.3
No 107 27.6
Missing 12 3.1
     
Do you feel that unhealthy weight management practices are a potential health risk for football players?
Yes 284 73.4
No 95 24.5
Missing 8 2.1
     
Do you have hereditary health issues that contribute to weight gain?
Yes 44 11.4
No 339 87.6
Missing 4 1.0
     
Is earning a scholarship or playing professional football a career goal?
Yes 282 72.9
No 99 25.6
Missing 6 1.6
     
The individual who has influenced your current weight management practices the most:
Teammates 16 4.1
Peers 26 6.7
Parents/Family 81 20.9
Coach 183 47.3
Nobody 77 19.9
Missing 4 1.0
     
Would you consider a weight management program after you football career?
Yes 330 85.3
No 43 11.1
Missing 14 3.6
     
Have you ever been diagnosed with an eating disorder?
Yes 8 2.1
No 373 96.4
Missing 6 1.6
     
Height in inches 71.44 3.36
     
Age in years 25.05 10.49
     
Weight in pounds 214.63 48.31

Table 4.3. Descriptive Statistics for Composite Scores (N = 387)

Variable Items Min. Max. M SD α
Sports Motivation (SMSR)            
Intrinsic regulation 3 1.33 7.00 5.53 1.30 .74
Extrinsic integrated regulation 3 1.00 7.00 5.34 1.29 .70
Extrinsic identified regulation 3 1.33 7.00 5.49 1.28 .71
             
Sports Motivation (SMSR)            
Extrinsic introjected regulation 3 1.00 7.00 4.24 1.53 .58
Extrinsic external regulation 3 1.00 7.00 3.20 1.52 .54
Amotivation 3 1.00 6.67 2.17 1.37 .72
             
Eating Patterns (YEPQ)            
Uninhibited 9 1.44 4.89 2.90 .52 .48
Oversnacking 12 1.17 5.00 2.74 .67 .82
Bingeing 13 1.00 4.54 2.61 .68 .81

Table 4.4. Descriptive Statistics for Eating Patterns Composite Scores as a Function of Player Group and Position Group (N = 387)

Variable High school College Former
  M SD M SD M SD
Uninhibited            
Other than linemen 3.09 .56 3.01 .55 2.83 .54
Linemen 2.87 .46 2.86 .51 2.76 .46
             
Oversnacking            
Other than linemen 2.99 .73 2.82 .69 2.48 .64
Linemen 2.84 .65 2.63 .58 2.68 .62
             
Bingeing            
Other than linemen 2.93 .79 2.65 .69 2.48 .58
Linemen 2.60 .77 2.51 .61 2.52 .56

Table 4.5 Results from ANOVAs for the Eating Habits Dependent Variables (N = 387)

Effect Sum of
squares
df Mean
squares
F p
           
Between groups 2.56 2 1.28 4.77 .009
Within groups 103.05 384 .27    
Total 105.61 386      
           
Oversnacking          
Between groups 6.83 2 3.42 7.98 < .001
Within groups 164.39 384 .43    
Total 171.22 386      
           
Bingeing          
Between groups 4.61 2 2.30 5.12 < .001
Within groups 172.70 384 .45    
Total 177.30 386      

Table 4.6. Descriptive Statistics for Sports Motivation Composite Scores as a Function of Player Group and Position Group (N = 387)

Variable High school College Former
  M SD M SD M SD
Intrinsic regulation            
Other than linemen 5.41 1.36 5.72 1.15 5.23 1.50
Linemen 5.51 1.25 5.88 1.24 5.41 1.24
Extrinsic integrated regulation            
Other than linemen 5.29 1.14 5.39 1.18 5.14 1.47
Linemen 5.22 1.29 5.51 1.26 5.44 1.37
Extrinsic identified regulation            
Other than linemen 5.21 1.32 5.67 1.09 5.08 1.71
Linemen 5.47 1.09 5.84 1.03 5.59 1.22
Extrinsic introjected regulation            
Other than linemen 4.49 1.41 4.45 1.41 3.80 1.57
Linemen 4.23 1.67 4.65 1.65 3.85 1.35
Extrinsic External Regulation
Other than linemen
 
 
3.60
 
 
1.48
 
 
3.60
 
 
1.44
 
 
    
2.40
 
 
1.34
Linemen 3.54 1.55 3.30 1.61 2.84 1.35
Amotivation            
Other than linemen 2.44 1.50 2.19 1.47 2.18 1.31
Linemen 2.39 1.55 2.06 1.34 1.86 1.02

Table 4.7. Results from ANOVAs for the Sports Participation Dependent Variables (N = 387)

Effect Sum of squares df Mean squares F p
Intrinsic regulation          
Between groups 15.56 2 7.78 4.71 .010
Within groups 634.38 384 1.65    
Total 649.94 386      
Extrinsic integrated regulation          
Between groups 2.58 2 1.29 .77 .462
Within groups 639.48 384 1.67    
Total 642.06 386      
Extrinsic identified regulation          
Between groups 14.11 2 7.06 4.41 .013
Within groups 613.88 384 1.60    
Total 628.00 386      
Extrinsic Introjected Regulation          
Between groups 37.57 2 18.78 8.31 < .001
Within groups 867.61 384 2.26    
Total 905.18 386      
Extrinsic External Regulation          
Between groups 67.57 2 33.78 15.79 < .001
Within groups 821.45 384 2.14    
Total 889.01 386      
Amotivation          
Between groups 10.80 2 5.40 2.91 .055
Within groups 711.75 384 1.85    
Total 722.55 386      

Table 4.8. Correlations Among Composite Scores (N = 387)

Variable 1. 2. 3. 4. 5. 6. 7. 8. 9.
Sports motivation (SMSR)                  
1. Intrinsic regulation 1.00                
2. Extrinsic integrated regulation .67*** 1.00              
3. Extrinsic identified regulation .73*** .73*** 1.00            
4. Extrinsic introjected Regulation .47*** .44*** .44*** 1.00          
5. Extrinsic external regulation .09 .11* .15** .46*** 1.00        
6. Amotivation -.29*** -.33*** -.30*** .07 .39*** 1.00      
Eating Patterns (YEPQ)                  
7. Uninhibited .01 .00 -.01 .21*** .23*** .13* 1.00    
8. Oversnacking -.13* -.10* -.10* .06 .29*** .24*** .60** 1.00  
9. Bingeing -.11* -.06 -.09 .13* .25*** .24*** .58** .75*** 1.00

*p < .05, **p < .01, ***p < .001

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