final thesis

A thesis entitled

THE DETRIMENTAL IMPACT OF TURNOVERS IN THE DEFENSIVE HALF AS IT PERTAINS TO WINS, LOSSES, AND DRAWS IN A SOCCER MATCH

Submitted to the Carroll University Library in

partial fulfillment of the expectations

and academic requirement of the

degree of Masters in Education

by

Matthew B. Drago

Research Facilitator, Dr. Sandra Shedivy Date

Program Chair, Dr. Wilma J. Robinson Date

Mentor, Miss Catherine M. Kaiser Date

Graduate Support Library Liason, Susan Hefferon Date

The Detrimental Impact of Turnovers in the Defensive Half as it Pertains to Wins, Losses, and Draws in a Soccer Match

by

Matthew B. Drago

A thesis submitted in partial fulfillment

of the requirements for the degree of

Master of Education

at

Carroll University, Waukesha, Wisconsin

May 2012

iii

TABLE OF CONTENTS

Approval Page Title Page Table of Contents… .............................................................................................. iii Abstract… ............................................................................................................. v List of Tables… ..................................................................................................... vi CHAPTER ONE: INTRODUCTION…. .................................................................. 1 Introduction….. ................................................................................................ 1 Research problem… ....................................................................................... 5 Purpose statement….. .................................................................................. 10 Significance of this study… ........................................................................... 10 Data collection… ........................................................................................... 14 Data analysis… ............................................................................................. 15 Research questions… ................................................................................... 16 Definition of terms… ...................................................................................... 17 Limitations… ................................................................................................. 18 Delimitations… .............................................................................................. 18 Overview of chapters… ................................................................................. 19 CHAPTER TWO: LITERATURE REVIEW…. ..................................................... 21 Introduction………………….. ........................................................................ 21 American football… ................................................................................. 22 Professional basketball…. ....................................................................... 26 College basketball… ................................................................................ 27 Research regarding wins, losses, and draws in soccer… ............................. 29 General soccer… ..................................................................................... 29 Conclusion… ................................................................................................. 38 CHAPTER THREE: METHODOLOGY Introduction… ................................................................................................ 40 Research design… ........................................................................................ 42 Participants… ................................................................................................ 44 NCAA division I athletics… ...................................................................... 44 Schools… ................................................................................................ 46 Bowling Green State University… ....................................................... 46 Indiana University… ............................................................................ 46 Marquette University… ....................................................................... 46 Michigan State University… ................................................................ 47

iv

Northwestern University… .................................................................. 47 The Ohio State University… ............................................................... 47 Pennsylvania State University… ......................................................... 48 University of Akron… .......................................................................... 48 University of Louisville… ..................................................................... 48 University of Michigan… ..................................................................... 48 University of Wisconsin-Green Bay… ................................................. 48 University of Wisconsin-Madison…..................................................... 49 University of Wisconsin-Milwaukee… ................................................. 49 Cases… ........................................................................................................ 49 Data collection… ........................................................................................... 50 Data analysis… ............................................................................................. 52 CHAPTER FOUR: RESULTS Introduction… ................................................................................................ 53 Data findings… .............................................................................................. 54 Case 1: University of Wisconsin-Madison vs. University of Wisconsin Green Bay… ............................................................................................ 54 Case 2: University of Wisconsin-Green Bay vs. University of Wisconsin- Milwaukee… ............................................................................................ 55 Case 3: University of Wisconsin-Madison vs. University of Michigan… ... 57 Case 4: Bowling Green University vs. The Ohio State University… ........ 58 Case 5: Northwestern University vs. The Ohio State University… ........... 59 Case 6: Northwestern University vs. Pennsylvania State University… .... 59 Case 7: Pennsylvania State University vs. Michigan State University… .. 61 Case 8: University of Notre Dame vs. Marquette University… ................. 61 Case 9: Indiana University vs. University of Michigan… .......................... 62 Case 10: University of Akron vs. University of Michigan… ...................... 63 Summary of cases… ..................................................................................... 65 CHAPTER FIVE: CONCLUSIONS….. ................................................................ 68 Introduction… ................................................................................................ 68 Higher skill level has less correlation to turnovers in the defensive half… .... 69 Unexpected significance… ............................................................................ 70 Implications… ................................................................................................ 72 Implementations and recommendations… .................................................... 73 REFERENCES…. .............................................................................................. 75

v

ABSTRACT

The Detrimental Impact of Turnovers in the Defensive Half as it Pertains to Wins,

Losses, and Draws in a Soccer Match

by

Matthew B. Drago

Carroll University, 2012

Under the Supervision of Dr. Sandra Shedivy, Research Facilitator

vi

LIST OF TABLES

Table 1: 2010 NBA Finals ..................................................................................... 4 Table 2: Turnovers in the Defensive Half ........................................................... 14 Table 3: Chart for Keeping Statistics .................................................................. 15 Table 4: Probable Case/Events .......................................................................... 16 Table 5: 2006- 2010 Super Bowls ...................................................................... 23 Table 6: 2010 NCAA Tournament ...................................................................... 32 Table 7: Possession in the 2010 World Cup Final .............................................. 34 Table 8: 1991-2009 Women’s World Cup Statistics ........................................... 36 Table 9: 2010 World Cup Statistics .................................................................... 38 Table 10: Events Compared to Cases ................................................................ 50 Table11: Madison Vs Green Gay ....................................................................... 55 Table 12: Green Bay Vs Milwaukee ................................................................... 56 Table 13: Madison Vs Michigan .......................................................................... 57 Table 14: Bowling Green Vs Ohio State ............................................................. 58 Table 15: Northwestern Vs Ohio State ............................................................... 59 Table 16: Northwestern Vs Penn State .............................................................. 60 Table 17: Penn State Vs Michigan State ............................................................ 61 Table 18: Notre Dame Vs Marquette .................................................................. 62 Table 19: Indiana Vs Michigan ........................................................................... 63 Table 20: Akron Vs Michigan .............................................................................. 64 Table 21: Cumulative Match Totals .................................................................... 65 Table 22: Statistics Averaged ............................................................................. 66

1

Chapter One: Introduction

Introduction

Wins and losses are almost always the barometer used when judging a

team’s effectiveness. But is it the wins and losses that identify the team or the

components that went into building the team’s wins, losses, and draws that is

more important? Athletic competitions have nearly infinite reasons for why teams

win or lose: athletic ability, coaching, and practice hours to name a few. In recent

years, the idea of “10,000 hours” of practice has been noteworthy. Levitin (as

cited in Gladwell, 2008) discusses this phenomenon:

The emerging picture from such studies is that ten thousand hours of

practice is required to achieve the level of mastery associated with being a

world-class expert in anything. In study after study, of composers,

basketball players, fiction writers, ice skaters, concert pianists, chess

players, master criminals, and what have you, this number comes up

again and again. Of course, this doesn’t address why some people get

more out of their practice sessions than others do. But no one has yet

found a case in which true world-class expertise was accomplished in less

time. (p.40)

When studying professional and college level athletics, practice hours and the

quality of the practice exercises begin to take a backseat. At both the college and

professional levels, practice hours, practice quality, and natural ability seem to

move to the background while game tactics and schemes move to the forefront.

Research at these levels is rarely focused on practice quantity, quality, or talent,

2

but rather the statistics associated with the actual games. In discussing athletic

events or contests, one must consider the simple possibility that one team’s

players are merely better than that of the other team. If one is to look a step

further at game statistics to better understand why teams are winning and losing

matches, one usually assumes the two teams competing are of similar talent.

This is generally accurate in professional and college athletics. Further, this

assumes that the amount of practice time and practice quality (intensity) for

players on both teams is similar with regard to the sport in which they are

participating. In this researcher’s opinion, wins, losses, and draws are no longer

a result of one team having more or less practice hours or quality (intensity) but,

rather opponent anticipation, strategy, and team cohesiveness may be much

more important.

Soccer is a sport that has been watched, studied, and dissected by fans,

coaches, and players for many years. Numerous studies have been conducted

which cover, in detail, the tangible statistics associated with soccer matches such

as: shots on goal, shots, corner kicks, goal kicks, free kicks, and in some cases,

consecutive passes. In looking at research conducted for other sports such as

football and basketball, the effects of turnovers on wins or losses have been

studied and discussed in depth. This researcher saw a gap in current and past

soccer research regarding lack of statistics pertaining to turnovers, that is, losing

control of the ball to the other team. The effect of turnovers and more specifically,

the effect of turnovers in the team’s defensive half in soccer, however, has not

been reported. It was this researcher’s goal in this study to study the effect of

3

turnovers in the defensive half of the field relative to the match outcomes.

In sports that are highly popular in the United States, turnovers and their

affect on the games’ outcome have been intensely covered and scrutinized. In

discussing the Packers and Steelers 2011 NFL Super Bowl, author Paul

Newberry (2011) of The Detroit News stated, “The Packers won [the turnover]

category going away. Therefore, they won the game” (p.1). Newberry

emphasized the importance of turnovers as it pertained to the outcome of this

specific football game. Later in Newberry’s article, he quoted Packers’ middle

linebacker Desmond Bishop, “If you win the turnover battle, there’s a direct

correlation to winning” (p.1). Further illustrating his point, Steeler running back,

Rashard Mendenhall was quoted as saying “When you turn the ball over like we

did, you put yourself in a bad position” (p.1).

A similar situation was noted by evaluating the statistics provided by

ESPN.com for the 2010 NBA Finals between the Los Angeles Lakers and the

Boston Celtics. This researcher identified the number of turnovers and rebounds

in the series and specifically looked to correlate the impact of turnovers and

rebounds to winning and losing. In the game of basketball both offensive and

defensive rebounds are similar to turnovers in soccer matches because they can

be considered a new possession for the rebounding (other) team. This

researcher collected and analyzed the data by adding team A's turnovers to team

B's rebounds, since both aspects illustrate positive outcomes for team B.

4

Likewise, team B's turnovers were added to team A's rebounds. Higher

totals equate to more possessions and in this particular best of seven series,

correlated with winning 86% of the time.

Table 1:

2010 NBA Finals Turnover Statistics

Forced Turnovers

Defensive Rebounds

Offensive Rebounds

Total Score

Game 1 Lakers 13 30 12 55 102 Celtics 12 32 8 52 89




Game 5

Lakers 16 18 16 50 86 Celtics 13 28 7 48 92



Totals Lakers 92 205 92 389 634 Celtics 87 203 71 361 610

Taken from: http://www.espn.com

In every game except for game five, the team with more rebounds and

forced turnovers won the game. The total turnovers and rebounds for Game 5

5

were 50 and 48 for the Lakers and Celtics, respectively. It is significant to note

that with such a small difference (two), this was the only instance where the team

with the fewest turnovers and rebounds lost the game. This also correlates well

with the fact that the Lakers had twenty-eight more possessions and outscored

the Celtics by twenty-four points in the seven game series.

Although most dynamics of a soccer match have been studied in great

detail, the subject of turnovers and more importantly, turnovers in the team’s

defensive half, have been largely overlooked. By identifying the number of

turnovers in a team’s defensive half, it is this researcher’s opinion that coaches

and players can now use a new avenue of dissection for their own games with

regard to wins and losses. By identifying and correlating another aspect of play

in this research, and understanding the intricate points of soccer, it may enlighten

teams to take on new strategies that both force their team to create turnovers

against their opponents and possibly more importantly, place their more skilled

players in the back of their formation (defensive side) minimizing turnovers in

their own defensive halves.

Research problem

Presently statistics regarding turnovers goes largely uncollected by

statisticians in soccer matches, largely due to the fact that there is a large

number of instances where teams gain and lose possessions throughout a

soccer match. This can be attributed qualitatively to how one defines a turnover

as opposed to an organized attack that did not result with a goal. It also may be

attributed to an aggressively played ball in the attacking half that did not reach its

6

target. For the purposes of this study, the researcher limited the definition of a

turnover to these specific parameters:

a.) A ball passed to an intended receiver already on the defensive half of

the field at any distance that is intercepted by an opponent.

b.) A player losing the ball in the defensive half to an opponent while

attempting to dribble or hold the ball at their feet.

c.) A player improperly clearing the ball from his/her defensive half, in that

the ball was either completely missed or miss-hit such that the ball

stayed in the general area in which it was being cleared from.

d.) A goal keeper mishandling a catchable shot or cross and being

recovered by the opposing team.

Before a turnover can be identified, the team in the defensive half must have

clear control over the ball. Control of the ball is defined as; having the ball at the

player’s feet in a controlled roll or a complete stop for a period of one second or

longer. In this research, an uncontrollable bouncing ball was not considered to

be a possession. A ball that was cleared by the opposition, arriving with a 50%

chance of retrieval by the defensive team, known throughout this study as “50-50

balls,” was also not considered to be a turnover. It is important to note that throw-

ins were not considered turnovers at any point in this study as well. Pollard and

Reep (2007) define possession as follows:

A team possession starts when a player gains possession of the ball by

any means other than from a player of the same team. The player must

have enough control over the ball to be able to have a deliberate influence

7

on its subsequent direction. The team possession may continue with a

series of passes between players of the same team but ends immediately

when one of the following events occurs: a) the ball goes out of play; b)

the ball touches a player of the opposing team (e.g. by means of a tackle,

an intercepted pass or a shot being saved). A momentary touch that does

not significantly change the direction of the ball is excluded; c) an

infringement of the rules takes place (e.g. a player is offside or a foul is

committed). (p. 1)

This researcher decided to use Pollard and Reep’s definition to qualify and

quantify the data.

Soccer can be looked at through multiple statistical venues. In discussing

their study of game related statistics, Lago-Penas, Lago-Ballesteros, Dellal, and

Gomez (2010) stated:

When analyzing the results overall, the univariate analysis showed that

there are ten variables with statistically significant differences (total shots,

shots on goal, effectiveness, assists, crosses, crosses against, ball

possession, and red cards, and venue). On the other hand, when

applying a multivariate analysis, the number of statistically significant

variables was reduced to six (total shots, shots on goal, crosses, crosses

against, ball possession, and venue). (p. 291)

In data from the 2010-2011 European Premiere League provided by

premiereleague.com; Arsenal, Everton, Chelsea, and Manchester United led the

league in shots per game. Of these four teams, only Everton was not ranked in

8

the top five of the twenty team league. This fact notwithstanding, the three

remaining teams ranked (1) Manchester United, (2) Chelsea, and (3) Arsenal. In

simplistically looking at these statistics one may come to the conclusion that the

quantity of shots highly correlated with more wins. It is well accepted by soccer

professionals, that shots are generated through a multitude of outlets such as,

possession, fast breaks, lost tackles, fouls, and turnovers. One poorly timed

turnover can amount to a game losing goal where ten shots through routine, non-

scoring possessions may lead to nothing (no scores). It is also well known that

soccer is a game that needs to be evaluated over the course of a long season,

not individual matches.

Continuing with the multitude of reasons in which matches are won or lost,

Lago-Penas et al. (2010) further stated:

In the articles reviewed for the present study, there were no studies that

analyze the relationship between performance indicators related to

defence and team results. Probably, this gap is due to problems for

measuring these variables. Further research should address this topic. (p.

291)

By researching the number of turnovers in a team’s defensive half, coaches and

players have a new way in which to analyze their own games in addition to wins

and losses. By providing another facet of research and increasing one’s

understanding of the intricate, finer elements of soccer, it is this researcher’s

opinion that this will enlighten teams to take on new strategies that both force

their team to create turnovers against their opponents and possibly more

9

importantly, place their better skilled players in the back of their formation

allowing for fewer turnovers by their own team in their defensive half.

Other studies have been published with regard to statistics that are not

universally collected. Greevy, Germano, and Luyben (2009) found no statistical

significance in multiple sequenced passes from one game to the next. Greevy et

al. also saw a gap in the research of uncollected data in sequenced passing. In

an effort to close this gap they chose participants from a Division III college in

central New York State. A correct pass was defined as a pass in which:

1. The passer is looking at a teammate

2. The ball is directed to the teammate and not toward the goal (excludes

shots)

3. The teammate is in a position to trap and/or control the ball

4. The ball remains in bounds

5. The pass is not touched by an opposing player

The researchers studied the last eight game tapes over the course of the 2007

soccer season. The data were broken down between two halves, and

demonstrated more variability in the first half than in the second. Single passes

increased in the final three games of the season with two, three, and four pass

sequences ranging from 25%-35%, 10%-20% and 0%-10%, respectively of all

passes completed. Identifying increases or decreases of a team's passes

throughout the eight games, proved to have no statistical significance relative to

wins, losses, and draws. Tenga, Holmes, Tore, Ronglan, and Bahr (2010) stated

that the small sample size in the research was a limitation of the study. They

10

also noted this to be a problem with most soccer related research as well. This

researcher agrees with Greevy et al. (2009) that only reporting the results of

eight games, the conclusions may be suspect and not applicable across the

entire soccer spectrum.

In another study that correlated shots taken and games won, Lago-Penas

et al. (2010) compared their Spanish soccer league results to that of the 2002

World Cup and the Greek Soccer First League and found that the top teams

made more shots than bottom teams.

Purpose statement

The overall purpose of this study was to research a variable that has not

been discussed before (turnovers in the defensive half of the field) and evaluate

how these turnovers contribute to wins, losses, and draws in soccer matches.

In a game with so few statistics available to be followed, it was this

researcher’s opinion that soccer needed to collect more statistics, including the

more difficult (qualitative) statistics, such as turnovers in the defensive half.

Furthermore, if the consequences of turnovers in a team’s defensive half

becomes qualitatively significant, it may result in teams re-thinking their offensive

and defensive strategies relative to building their attacks further from their

defensive goal than was previously accepted.

Significance of the Study

As stated by Bourdieu, as cited in Christensen (2009):

Experts in a given activity such as soccer coaching are considered experts

because their flair for sensing what is going to happen-their “feel for the

11

game” is valued and is assigned capital in the field of soccer. Practical

sense here is not a result of logical thinking or declarative knowledge. It is

founded on practical intuition or habitus, which might be informed by

explicit knowledge, but is primarily based on hands-on and incorporated

knowhow earned through a legitimate and privileged access to the field.

(p. 368)

Regarding player selection, coaches are often making decisions that are largely

based on their “feel for the game,” when it could be a combination of feel and

statistics. The research compiled in this study attempted to close the gap

between qualitative “feel for the game” and quantitative game statistics.

The overall intent of this research project was to fill a perceived void in

statistical analysis of soccer matches. The researcher had seen a gap in major

sports in indicators statisticians viewed as prevalent; the researcher wanted to

close that gap and identify a previously unidentified statistic that could have a

major impact on soccer match results. The researcher noted that in several

major sports, including basketball, football, lacrosse, and rugby, turnovers were

identified and covered in great detail. The researcher has played soccer his

entire life and noted that soccer did not keep track of this statistic, possibly

because of the subjective (qualitative) nature in distinguishing turnovers from the

regular flow of play.

The overall intent of the study was to give another avenue for teams to

evaluate retrospectively relative to wins, losses and draws. The results of this

study could also give credence to the idea of putting a team’s better skilled and

12

athletic players on defense to protect against critical turnovers in the defensive

half.

Research design

The researcher’s goal was to provide data and conclusions on how to

develop teams in terms of player positional placement, attacking styles and

defensive formations. It was hypothesized that the more information a coach or

team has, the more likely teams will gain an advantage on the competition and

be more successful over the course of a season, or a multitude of seasons.

The researcher wanted to identify if there was a direct correlation to

increased number of turnovers in a team’s defensive half, shots surrendered, and

shots on goal surrendered, to losing matches. For this study, the researcher

narrowed the research to turnovers in the defensive half because, in his

experience, those were the plays that tended to result in increased offensive

opportunities and shots for the opposing team.

The researcher viewed ten different NCAA Division I men’s soccer games;

the games were chosen based on games which were being broadcast by The

Big Ten Network or WISN Milwaukee. The statistics were collected personally by

the researcher; all games took place during the fall soccer season of 2011. This

study followed a qualitative design, using correlational case study methods. Data

were obtained and collected using statistics drawn from ten games played by

fourteen NCAA Division I men’s soccer teams.

The researcher will use a case-ordered effects matrix to study the causes

of the wins and losses. As stated in Miles and Huberman (1994), “a case-

13

ordered effects matrix sorts the cases by degrees of the major cause being

studied, and shows the diverse effects for each case” (p. 209). Miles and

Huberman go on to say that “the focus is on outcomes, dependent variables” (p.

209). The researcher viewed ten games for fourteen different NCAA teams:

Bowling Green State University, Indiana University, Marquette University,

Michigan State University, Northwestern University, Notre Dame, The Ohio State

University, Pennsylvania State University, University of Akron, University of

Louisville, University of Michigan, University of Wisconsin-Green Bay, University

of Wisconsin-Madison, and University of Wisconsin-Milwaukee. In order to

reduce any potential bias regarding the researcher inflating the statistics by

choosing particular games that may skew the statistics to prove the hypothesis,

the researcher watched game tapes of teams that were broadcast on one of two

local networks: The Big Ten Network and WISN Milwaukee. At no point did the

researcher view the previously charted game statistics of the matches that were

viewed. All statistics were taken first hand by the researcher.

The research design for this study incorporated qualitative events.

Creswell (2008) defines qualitative research as an in-depth exploration of the

“event” of a bounded system which means it is separated out for research in

terms of time, place or some physical boundaries (p. 465). Whereas Creswell

also defined quantitative research as: "A type of educational research in which

the researcher decides what to study, asks specific, narrow questions, collects

numeric (numbered) data from participants, analyzes these numbers using

statistics, and conducts the inquiry in an unbiased, objective manner" (p. 46). The

14

researcher used qualitative research and looked at one event, turnovers in the

defensive half, as it related to wins, draws, and losses, across ten cases. Table 2

below, illustrates those cases.

Table 2: Turnovers in the Defensive Half

Event Cases

Turnovers in the Defensive Half

Case 1: University of Wisconsin-Madison vs. University of Wisconsin-Green Bay

Case 2: University of Wisconsin-Green Bay vs. University of Wisconsin-Milwaukee

Case 3: University of Wisconsin-Madison vs. University of Michigan

Case 4: Bowling Green University vs. The Ohio State University

Case 5: Northwestern University vs. The Ohio State University

Case 6: Northwestern University vs. Pennsylvania State University

Case 7: Pennsylvania State University vs. Michigan State University

Case 8: University of Notre Dame vs. Marquette University

Case 9: Indiana University vs. University of Michigan

Case 10: University of Akron vs. University of Michigan

The researcher studied how turnovers in one’s defensive half, shots, and

shots on goal reflected changes in wins, losses, and draws.

Data collection

In order to test the correlation between turnovers in the defensive half,

shots, and shots on goal with regard to wins, losses, and draws, the researcher

watched ten game tapes for 14 different NCAA teams: Bowling Green State

15

University, Indiana University, Marquette University, Michigan State University,

Northwestern University, Notre Dame, The Ohio State University, Pennsylvania

State University, University of Akron, University of Louisville, University of

Michigan, University of Wisconsin-Green Bay, University of Wisconsin-Madison,

and University of Wisconsin-Milwaukee. To ensure that the researcher did not

inflate any statistics by choosing particular games that could have skewed the

statistics to prove the hypothesis, the researcher watched game tapes of teams

that were broadcast on one of two local networks: The Big Ten Network and

WISN Milwaukee.

Tally marks were made for the two teams involved in the match using the

following chart:

Table 3: Chart for Keeping Statistics

Turnovers in

Defensive Half

Goals

Goals directly off of a

defensive Turnover

Win/Loss/Draw

Away Team

Home Team

The top teams were the visitors; the bottom teams were the home team.

Data Analysis

Miles and Huberman (1994) stated that,” We all have our preconceptions,

our pet theories about what is happening. The risk is taking them for granted,

imposing these willy nilly, missing the inductive grounding that is needed.” Miles

and Huberman also noted that these principles are naturally abstract and

16

discussed five main methods and four supplementary methods with which to

further clarify the descriptions. They stated that in effects-displays, or examining

diverse results (win, lose, or draw) occurring from a single major variable

(defensive turnovers) are structured as:

Table 4: Probable Cause/Event

Probable Cause/Event

Effect 1

Effect 2

Effect 3

Effect 4

They further stated that when there are several cases where an important or

salient “cause” (in this case, turnovers in the defensive half) is expected to have

a variety of results (win, lose or draw), the question is how to display relevant

data, to see how the effects play out across an array of cases that have a greater

or smaller amount of the basic cause (turnovers in the defensive half).

Research questions

In this study, the researcher addressed the following questions:

1.) What are the contributing factors to game wins and losses across several

sports?

2.) What research has been done regarding, wins, losses, and draws in

soccer?

17

3.) What impact do turnovers in a team’s defensive half, shots, and shots on

goal have on wins, losses, and draws for college level soccer teams?

Definition of terms

For the purposes of this study, the researcher defined the following terms as:

50-50 Ball:

A ball that arrives with a 50% chance of retrieval from either team

Shot:

When a player makes an attempt to score by striking a ball in the direction of the

goal where the ball would or would not have actually scored, hit the goal’s frame,

or necessitated a save by the defensive team or its goal keeper.

Shots on Goal:

When a player makes an attempt to score by striking the ball in the direction of

the goal where the ball would score, or hit one of the posts, unless otherwise

saved by the defensive team or its goal keeper.

Turnover in the Defensive Half:

a.) A ball being passed from a player on the defensive half of the field

being intercepted by an opponent within a twenty yard radius to the

intended receiver on the attacking half of the field.

b.) A ball passed to an intended receiver already on the defensive half of

the field at any distance that is intercepted by an opponent.

c.) A player losing the ball in the defensive half to an opponent while


18

d.) A player improperly clearing the ball from their defensive half, in that

the ball was either completely missed or miss-hit so that the ball stayed

in the general area in which it was being cleared from.

e.) A goal keeper mishandling a catchable shot or cross and being


Limitations of the Study

Limitations of this study include the number of games analyzed, the

number of different teams analyzed, and skill level (based on NCAA division)

used in the study. Due to time constraints, the researcher limited the number of

games analyzed to ten games and fourteen different teams. This contradicts

some of the previous research in asking researchers to use more data and

clearly, having a wider base for games, teams, or even leagues, would give a

fuller understanding of the statistics provided, as is the case with most data

collection.

Delimitations of the Study

Several delimitations were noted for this study. The research was

delimited to fourteen different NCAA teams; Bowling Green State University,

Indiana University, Marquette University, Michigan State University,

Northwestern University, Notre Dame, Ohio State University, Pennsylvania State

University, University of Akron, University of Louisville, University of Michigan,

University of Wisconsin-Green Bay, University of Wisconsin-Madison, and

University of Wisconsin-Milwaukee. To ensure the researcher did not inflate the

statistics by choosing particular games that may skew the statistics to prove the

19

hypothesis, the researcher watched games of teams that were broadcast on one

of two local networks: The Big Ten Network and WISN Milwaukee. At no point

did the researcher view the previously charted game statistics of the matches

that were viewed. All statistics were taken first hand by the researcher.

The number of teams analyzed by the researcher was limited to fourteen.

Skill level was limited to NCAA division I soccer teams, specifically; Bowling

Green State University, Indiana University, Marquette University, Michigan State

University, Northwestern University, Notre Dame, The Ohio State University,

Pennsylvania State University, University of Akron, University of Louisville,

University of Michigan, University of Wisconsin-Green Bay, University of

Wisconsin-Madison, and University of Wisconsin-Milwaukee. Having limited the

research to ten games and fourteen teams necessitates caution in generalizing

to a larger population.

Overview of chapters

Chapter Two of this thesis is a literature review. First, it examines the

contributing factors to game wins and losses across several sports. Professional

basketball, collegiate basketball, professional football, and collegiate football will

be specifically addressed. Next, the researcher will look at research that has

been done regarding wins, losses, and draws in soccer across various skill

levels. Finally, the researcher will specifically examine the impact of turnovers in

a team’s defensive half, shots, and shots on goal with regard to wins, losses, and

draws for college level soccer teams; this being the researcher's main purpose in

the study.

20

Chapter Three focuses on the methods used in this qualitative, collective

case study. It details the process of how the study took place. Included is a

detailed description of the participating teams. Chapter Three also provides a

detailed explanation of game analysis and how it was conducted and analyzed.

Chapter Four reports and interprets the findings of this qualitative study.

Data collected from fourteen teams and ten games are included.

Chapter Five summarizes the implications for the results and findings of

the qualitative study. Chapter Five also discusses recommendations for further

research.

21

Chapter Two: Literature Review

Introduction


coaches, and players alike. Numerous studies have been conducted which

cover, in detail, tangible statistics such as: shots on goal, shots, corner kicks,

goal kicks, free kicks, and in some cases, consecutive passes. In looking at

research conducted for other sports such as football and basketball, the effects

of turnovers on wins or losses have been studied and discussed in depth. The

researcher saw a gap in current and past soccer research regarding a lack in

turnover statistics. The effect of turnovers, and more specifically, the effect of

turnovers in the team’s defensive half in soccer, however, has been limited. It

was the researcher’s goal in this study to help close this gap.

Soccer statistics are taken and presented with no subjectivity, some

subjectivity and a lot of subjectivity. Some statistics will be a part of nearly every

game taking place on the planet. No matter how big or how small, goals will be

noted and by the end of the game, this will be the telling statistic as to which

team wins the game and in most cases, which team is better. In most

competitive matches, shots, shots on goal (that is a shot that is either saved,

scored, or strikes the goal’s post or crossbar), corner kicks, fouls and ejections

will be kept. If these statistics are not kept with a pen and paper they are

generally recalled with relative familiarity by on-lookers. Statistics that are kept in

22

some of the worlds’ more contested matches include; time of possession, saves,

fouls surrendered, free kicks taken, offside calls for and against and the

researcher proposes to add turnovers in the defensive half of the field.

American football.

Sports have been analyzed, and obsessed about throughout the world for

what seems like an eternity. Wins and losses are always at the forefront of any

discussion. In looking at American football, turnovers and their effect on the

games’ outcome have been intensely covered and scrutinized. When the

Packers met the Steelers in the 2011 NFL Super Bowl, the stakes could not have

been higher. When the Packers ended up winning the game, the Steelers were

ridiculed more for their lackluster play than for the Packers’ offensive prowess.

Quarterback, Ben Roethlisburger accepted some of the game’s blame in saying,

"They're a great defense. They got after us [in the first half], and I turned the ball

over, and you can't do that" (McClain, 2011, p.1). Roethlisburger’s teammate,

running back, Rashard Mendenhall, continued the sentiment by saying “When

you turn the ball over like we did, you put yourself in a bad position” (Newberry,

2011, p.1). This information suggests that the multitude of turnovers lost the

game for the Steelers more than their ability to score points. This could be a

small sample size. In looking at the past five Super Bowls, however, the

researcher finds:

23

Table 5: 2006-2010 Super Bowls

Super Bowls Fumbles Interceptions

Total Turnovers

Score

2010

Packers 0 0 0 31

Steelers 2 1 3 25

2009

Saints 0 0 0 31

Colts 0 1 1 17

2008

Steelers 0 1 1 27

Cardinals 1 1 2 23

2007

Giants 0 1 1 17

Patriots 1 0 1 14

2006

Colts 2 1 3 29

Bears 3 2 5 17

Game Totals

Winners 2 3 5 135

Losers 7 5 12 96

Taken from: http//www.espn.com

In the last five Super Bowls, the team that won the game also had fewer

turnovers. This is not to say that it is impossible to win a football game while

committing turnovers, but it does imply a greater difficulty in achieving the sport’s

greatest victory while amassing more turnovers than the competition.

The average margin of victory in these five games was 7.8 points, or, one

touchdown and a two point conversion. Interestingly enough, the average

turnover differential was 1.4 per game, which can be further detrimental when

one considers the fact that turnovers often lead to immediate points by the

defense. In four of the five Super Bowls mentioned, the team that won the game

scored a touchdown on an interception and/or a fumble recovery; these are

24

considered turnovers. Those scores, in the case of the 2010, 2009, and 2008

Super Bowls, were while the attacking team was within 40 yards of scoring points

of their own.

Consider the 2008 Super Bowl. The score was: Steelers 10, Cardinals 7;

the Cardinals were 3 yards from scoring with under a minute to play in the half. If

the Cardinals scored a touchdown, they would take a lead of 14-10 into halftime,

and presumably control of the game. As it happened, the Cardinals threw an

interception that was taken back 100 yards by a Steelers player for a touchdown

with no time remaining; a turnover. The score at halftime was Steelers 17,

Cardinals 7. That was a 14 point swing and proved to be insurmountable for the

Arizona Cardinals. These statistics suggest that not only are turnovers impactful

on the score, but they also usually imply a loss. It could also be argued that when

turnovers lead to a score by the opposing team, it can be a mental backbreaker

for the team’s psyche in how they perceive and continue to play the game.

College football statistics show similar results to professional football with

regard to turnovers. In a 2003 college football game, “Matt Kegel threw three

touchdown passes and steadily guided the No. 21 [Washington State] Cougars,

who took advantage of seven-first half turnovers yesterday to beat the 10th-

ranked Ducks, 55-16” (New York Times, 2003, p. 1). In a 2002 college football

game, “Ronnie Brown ran for two touchdowns and Auburn took advantage of five

turnovers to upset visiting Louisiana State, 31-7. Unranked Auburn intercepted

Marcus Randall four times and held LSU, ranked No. 7 by the New York Times

computer and No. 10 in the Associated Press poll, to 242 yards after giving up 68

25

points in its last two games, both losses” (New York Times, 2002, p. 1). In yet

another instance where turnovers are the headline in college football:

Coming into today's game against Army, the New Mexico State coach,

Tony Samuel, told his players they would have to cut down on turnovers if

they were to end a three-game losing streak. The (New Mexico State)

Aggies had committed four turnovers in losing to Nevada by a touchdown

a week ago, and had fumbled the ball away 10 times in their first six

games, including a 35-7 upset of then 22d-ranked Arizona State on Sept.

8. (Cavanaugh, 1999, p. 1)

In looking at these three games, it is clear that the authors have stressed the

importance of turnovers in each game’s outcome. In another game where the

highly rated West Virginia Mountaineers lost to the University of Connecticut

Huskies, an article by the Associated Press (2010) reported:

Dave Teggart hit a 27-yard field goal in overtime and Connecticut beat

visiting West Virginia, 16-13, giving the Huskies their first win over the

Mountaineers. The winning score was set up when Connecticut linebacker

Lawrence Wilson recovered a fumble inside the 5, the fourth turnover of

the night by West Virginia. (2010, p. 1)

It becomes necessary for the Huskies to win the turnover battle when asked to

beat a seemingly superior team. The Associated Press furthered their point in

discussing turnovers when, “the Mountaineers had 414 yards of offense, but lost

26

four of seven fumbles, and scored just 3 points after the first quarter” (p. 1). The

conclusion may be drawn that without the several turnovers, the Mountaineers

would have had a much greater chance at winning the game.

Professional basketball.

Crossing into other sports, similar trends develop in basketball. The 2010

NBA finals saw two evenly matched teams play seven highly contested matches.

In all but one of the matches (game five), the team with more rebounds and

forced turnovers won the game. In looking at the gross numbers across the

series from the National Basketball Association (www.nba.com), the Lakers saw

the ball seventeen more times than the Celtics did. That is seventeen more

opportunities to score over a series where the difference between a win and a

loss was a mere 3.4 points per game. Could it be possible that instead of

teaching better means of attack and possession, teams should instead be

promoting forced turnovers and high intensity levels on 50-50 balls? A 50-50 ball

is considered a ball that has a fifty percent chance of being won by either team.

Teams that promote more hustle and fundamentals of the game tend to win in

this category. As is stated by Stuart Kantor editor of www.hoopmechanix.com:

Finding players who want to shoot and score is easy; finding players who

want to shut down an opponent's offensive weapon is difficult. Why? Read

the box score. Great defenders aren't fully recognized in the box score the

way offensive players are. Box scores highlight rebounds and blocks, but

rarely publicize how many charges were taken. More importantly, only

close observation of the game can detect truly outstanding defense, for

27

there is no box score category for cutting one’s man off at the baseline.

There is no category for impeding a player who is trying to cut in front of

your face and gain position. (p. 27)

What plagues so many sports is that the better players prefer the more high

profile tasks. The great soccer players tend to play striker, so they can earn

goals, the great football players tend to prefer offense to score touchdowns and

basketball players are similarly praised for their efforts on the offense.

College basketball.

In a playoff game between Manhattan College and University of

Wisconsin-Green Bay, the New York Times (1992) reports, “A desperation

inbounds pass the length of the court by Wisconsin-Green Bay was intercepted

by the Jaspers' Keith Bullock, and Manhattan had its first post-season victory

since 1975” (p. 8). This is one of several cases where a seemingly over-matched

opponent has earned a victory because of multiple turnovers or a poorly timed

turnover. As reported by the New York Amsterdam News’ Jaime C. Harris

(2007), “Hampton University's defensive game plan was evident from the

opening tip-off. Pressure, pressure and more pressure! The Pirates harassed the

Howard University Bison from baseline to baseline and turned 25 Bison turnovers

into easy baskets in coasting to a 65-31 victory” (p. 1). Later in the article Pirates'

head coach Kevin Nick-leberry said, “It was a good win for our program, we didn't

play great offensively, but we played well defensively. I think anytime we play

well defensively, we have a chance to win. And that's been the constant for us”

(p. 1).

28

Kevin Burke and Michelle Burke did a study on the perception of

momentum in both collegiate and high school basketball arena. As they reported

in the Journal of Sports Behavior (2009):

The five most frequently occurring actions at the beginning of perceived

momentum in rank order were a 3-point shot, defensive stop, steal,

fastbreak, or a turnover. During momentum, the five most frequently (in

rank order) occurring actions were turnovers, crowd noise, defensive

stops, steals, and "string" of unanswered points. The five actions most

frequently observed (in rank order) at the end of momentum were

turnovers by momentum team, missed shots by momentum team, time

outs, fouls, and end of the playing period. (2009, p. 303)

Burke and Burke have rated three categories; how momentum starts, during

momentum and how momentum tends to end. In starting momentum, the

second, third and fifth most frequent reasons for momentum were defensive

plays. In sustaining momentum, the first, third and fourth were defensive plays,

and in ending momentum three of the five reasons, including the number one

reason, turnovers, were also defensive plays.

Burke and Burke (2009) initiated a study that was largely based on

offensive performance or momentum. One of the earlier cited definitions of

momentum was provided by Iso-Ahola and Mobily (1980) who stated that

momentum is, “A gained psychological power which may change interpersonal

perceptions and influence physical and mental performance” (p. 1). The

researcher finds it interesting that in an attempt to prove offensive prowess and

29

to determine why teams get momentum in scoring an abundance of points, they

have found in each of their three categories that defensive plays were more

responsible than offensive plays.

Research regarding wins, losses, and draws in soccer

General soccer.

In soccer research, reasons one team won, lost or drew with an opponent,

tend to be:

a.) Shots

b.) Shots on Goal

c.) Possession

d.) Corner Kicks

e.) Fouls (Coinciding with Direct Kicks)

f.) Ejections

In some cases researchers go so far as to count consecutive passes in hopes for

a correlation to winning games. Such is the case with Greevy et al. (2009):

The data show the percentages of single, double, triple, and quadruple

(plus) passes made during the particular half. The data across halves are

largely consistent, except that there is more variability in the first half than

the second. Inspection of Figures 1 and 2 shows that more than 50% of

the passes in the first half were single passes with increases during the

last three games of the reason. The data for the remaining pass

sequences are relatively stable, with little evidence of trends. Two pass

sequences ranged from 25% of passes to about 35%. Three pass

30

sequences consistently ranged between 10 and 20% of all passes. Four

pass sequences were consistently at or below 10% of passes, with a few

exceptions. The outcome of each game is shown as a win (W) or loss (L)

above each data point. Inspection of the relationship between the

proportions of single or multiple passes shows no consistent pattern

associated with wins and losses. (p. 1)

In the Greevy et al. study of nine games over the course of Cortland State

College of New York’s men’s soccer team, showed no patterns of greater

success in consecutive passes in regard to winning games. Had Greevy et al.

had another chance at their research, it may have been important to not only

count the consecutive passes but count the passes that advance the team down

the field. Along those lines, counting passes completed in the attacking half or

attacking third of the field would be the more dangerous and difficult area to

complete passes which could imply more skill by whichever team is able to do

so. With soccer being a game that has so many different playing styles, it is

more than possible that a highly successful team may not complete many passes

in any area of the field but prefer to play a ball long allowing their athleticism to

dictate their success.

Had Greevy et al. (2009) had an opportunity to look at more advanced

players, such as Division I soccer or professional soccer, they may have seen

significance in their study with pass completion. With teams such as the World

31

Cup Champion’s, Spain, tallying nearly 60% possession in the tournaments’ final

match, it is likely that they had more consecutive passes than their competition,

The Netherlands.

Shots taken and shots surrendered are the mainstay of nearly all soccer

matches. It is the one statistic that is almost always given after every match and

nearly all competitive teams across the world keep the statistic in competitive

games. In looking at the 2010 World Cup’s final eight games, the team that

earned more shots won their match 50% of the time. With shots dictating the

winner only 50% over these eight games, the researcher wanted to look at more

statistics regarding these matches. Shots on goal can be statistic that can be

more telling than shots. Shots on goal are defined as a shot taken that scores,

are saved by the goal keeper or strikes the goal post or cross bar. In the final

eight games of the 2010 World Cup, the teams that had more shots on goal than

their opponent won 62.5% of the time. Of the sixteen teams of these eight World

Cup matches, there were six teams that tallied five shots on goal or less, of those

six teams two of them actually won but each of those two teams played a team

that tallied four and two shots on goal respectively.

In the 2010 NCAA final three games, between divisions I, II, and III, the

team with more shots won 77% of the time and the team with more shots on goal

won 56% of the time, which is shown with Table 6:

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Table 6: 2010 NCAA Tournament

Division I Match-up

Shots Shots On Goal Score

Akron Louisville

19 15

7 7

1 0

Louisville North Carolina

11 9

4 3

2 1

Akron Michigan

22 9

8 1

2 1

Division II Match-up


Northern Kentucky Rollins College

11 14

9 11

3 2

Northern Kentucky Dowling College

11 5

5 2

4 1

Rollins College Midwestern State

13 10

5 8

2 1

Division III Match-up


Messiah College Lynchburg College

12 10

2 4

2 1

Messiah College UW-Oshkosh

18 10

8 5

4 1

Lynchburg College Bowdoin College

14 18

9 5

2 1

Data taken from: http://www.ncaa.com

It is clear that shooting in a soccer match is an important part of the game,

in this instance, shooting more than the opponent won 77% of the time. A team

that takes no shots has no chance of winning. This is not to imply that merely

shooting at random will guarantee success. Shots and shots on goal are

wonderful statistics to look at in getting a general feel for how a team did during a

33

particular match, however, the researcher still thinks there is a gap in the data

and believes more statistics should be used in measuring a team’s successes or

failures.

Time of possession is a loosely defined statistic that is kept at nearly every

professional soccer match. Pollard and Reep (2007) define possession as

follows:











committed). (p. 1)

Although time of possession is formerly followed and expected to show which

team is commanding the field, it does not always correlate into wins, losses and

draws. In the 2010 World Cup the team that led in possession for the final eight

games won 75% of the time.

In looking at time of possession, the reader must understand that it is a

subjective topic. Depending on which news outlet a reader chooses to use, there

34

may be very different records of the exact same game. Table 7 shows four media

outlets reporting the World Cup final between the Netherlands and Spain, all four

outlets show different statistics regarding time of possession.

Table 7: Possession in the 2010 World Cup Final

Source Spain The Netherlands

soccerstats.com 62.9% 37.1%

FIFA.com 57% 43%

theage.com.au 56% 44%

news.bbc.co.uk 60% 40%

With the commonality of this statistic and its usage in soccer matches

across the world, it is clear that subjective statistics are accepted and used to

show fans, players, and coaches alike the success or failures of given teams.

Similar to time of possession, the statistics of turnovers in the defensive

half would also be subjective in nature. Almost assuredly different statisticians

would keep the number in a slightly different manner. The researcher

understands the discrepancy in who is keeping the statistic but wonders if this is

the main reason for the statistic not being kept when similar statistics, like time of

possession, are kept for nearly all major professional soccer matches?

Corner kicks are a set play that occur when the defensive team is last to

touch the ball over their defensive end line that did not result in a goal. Corner

kicks tend to be a product of an attacking team putting pressure on the defensive

team, where the defensive team is looking to clear the ball, block a shot, or tackle

35

a ball carrier deep in their defensive territory. In the final eight games of the 2010

World Cup the team that won the more corner kicks won the match 62.5% of the

time. This is situation similar to shots and shots on goal where the teams with

more corner kicks tend to win their matches. Although it must be noted that

when a team gets a lead, there is a tendency to play more defensive which

allows the opposition to attack with more vigor and opportunity.

When looking at fouls and ejection, it is important to also think about the

restart of play. When a foul occurs in a soccer match the ball can be restarted in

one of two manners.

a.) Direct free kick: the ball is placed at a standstill, the nearest defenders

keeps a distance of ten yards or greater from the ball. Upon striking the

ball, a goal may be scored without any other players touching the ball.

b.) Indirect free kick: the ball is placed at a standstill, the nearest defender

keeps a distance of ten yards or greater from the ball. Upon striking the

ball, a goal may only be scored when the ball is touched by a second

player from either the attacking or defensive team.

Direct free kicks are far more common and are issued when a player trips,

charges, pulls/holds, tackles or by other means impedes an opposing player.

Direct free kicks have been charted for effectiveness but Allison Alcock from the

Australian Institute of Sport has found is that the sheer number of direct kicks is

not nearly as important was where the direct kicks are actually taken. Alcock

finds:

36

The potential for a direct free kick to result in a goal is largely dependent

on the pitch location from where it is taken, as this influences the distance

the player must kick the ball, the positioning of any defensive wall of

players, and the angle to the goal. (p. 1)

Alcock furthers her findings by illustrating the goals scored from direct free kicks

in the women’s World Cup as follows:

Table 8: 1991-2009 Women’s World Cup Statistics

Data taken from: http//ncaa.com

By Alcock’s own admission she was selecting direct free kicks that were taken in

the teams attacking half, which leaves a large amount of fouls and direct kicks

that are taken without any reasonable chance of scoring. Fouls and free kicks

are another interesting side not to a soccer match but rarely do they dictate a

victor, unless the foul turns into an ejection.

In the 109th minute of the 2006 Men’s World Cup final, Zinedine Zidane

head butted defender Marco Materazzi in the chest drawing a red card and

immediate ejection (Longman, New York Times, p. 1). What is crucial to realize

in a soccer match once a red card (ejection) has been issued, the player

Women’s World Cup Tournament

Year

Number of Games

Number of Goals Scored

Number of Goals Scored

Number of goals direct from a free

kick as a percentage of all

goals

1991 26 99 1 1.01%

1995 26 99 Not Available Not Available

1999 32 123 5 4.07%

2004 32 107 5 4.67%

2009 32 111 7 6.31%

37

receiving the ejection may not be replaced on the field, leaving his team to ten

players while the other team continues with eleven. Although France did not lose

during regulation to Italy, playing ten versus eleven for the remainder of the

match all but assured France would not be able to score during the last minutes

of overtime.

Carl Bialik of the Wall Street Journal writes about a quarterfinal match

between the Netherlands and Brazil in which Brazil was favored to win but came

up short because of an ejection to one of their players:

In the second half of Brazil’s quarterfinal match against the Netherlands,

Felipe Melo made two catastrophic errors that burned the Brazilians. First,

he deflected a Wesley Sneijder shot into the goal when trying to clear it

with his head. Then, with Brazil trailing 2-1, Melo was sent off for doffing

his spikes into Arjen Robben in the 73rd minute. Brazil was forced to play

down a man for the last 20 minutes, and couldn’t come back, exiting in the

quarterfinal stage for the second consecutive World Cup. (2010, p. 1)

In the same 2010 World Cup involving the same team who had previously

benefited from a Brazilian player’s ejection, were victims of their own ejection in

the tournament finale against Spain. Fletcher states (2010), “After gradually

taking a grip on a tense and bad-tempered contest that produced 14 yellow cards

with (Netherlands’) Johnny Heitinga sent off on 109 minutes after picking up a

second yellow card” (p. 1). Unlike the Netherlands previous match with Brazil,

Spain did end up scoring in the extra period with the Netherlands being down a

field player for the final eleven minutes.

38

A team does not merely lose because they have had a certain number of

fouls or a certain number of fouls in a general area that may prompt a goal. Nor

is it fair to say that just because a team has had a player ejected from the match

that their team has no chance at winning. What this does say is that when

looking at these statistics in an all encompassing view, it is important for them to

tell a story. In looking at the 2010 World Cup final, having issued 14 yellow

cards, it was highly likely that one or more players would be ejected from the

match. This is because after the same player is issued two yellow cards, it turns

into a red card, which is an ejection. If one chooses to look at the match

statistics, it becomes very telling as to why Spain won the game.

Table 9: 2010 World Cup Statistics

Spain The Netherlands

Possession 60% 40%

Total Shots 20 11

Shots on Goal 8 5

Corner Kicks 8 6

Fouls 18 28

Ejections 0 1

Data taken from: http://news.bbc.co.uk/sport2/hi/football/world_cup_2010/matches/match_64 Spain won in every major category. Although the score was only 1-0, the

statistics paint a picture of a dominant victory for the Spanish. The researcher

suggests another statistics be added, turnover in the team’s defensive half.

Conclusion

It is clear that in looking at soccer statistics some of the stats are

indisputable to a statistician, like goals scored, offside calls, corner kicks, foul

calls or ejections, while others are extremely subjective and leave the

39

interpretation up to the stat keeper. Time of possession, shots, and even saves

can look very different depending on who is keeping the statistics. The

researcher contends that adding another statistic with relative subjectivity would

not only improve the significance of game statistics, it would add another point of

merit in how one looks at the makeup of a game.

Statistics of a match may never prove more noteworthy than actually

viewing the match, but it is the researcher’s contention that the gap can be

bridged between statistical analysis and actual viewership of a soccer match.

40

Chapter Three: Methodology

Introduction


coaches, and players alike. Numerous studies have been conducted which

cover, in detail, tangible statistics such as: shots on goal, shots, corner kicks,

goal kicks, free kicks, and in some cases, consecutive passes. In looking at

research conducted for other sports such as football and basketball, the effects

of turnovers on wins or losses have been studied and discussed in depth. The

researcher saw a gap in current and past soccer research regarding a lack in

turnover statistics. The effect of turnovers, and more specifically, the effect of

turnovers in the team’s defensive half in soccer has been limited. It was the

researcher’s goal in this study to help close this gap.

The purpose of this study was to fill the gap in the statistical outcome of

soccer matches by keeping the statistics of turnovers in the defensive half.

Currently soccer has statistics that cover most offensive aspects of the game, but

in a sport where possession, shots, and saves can have multiple definitions,

keeping the statistic of turnovers in the defensive half could also be defined in

many ways. The researcher’s goal was to provide data and conclusions on how

to develop teams in terms of player positional placement, attacking styles and

defensive formations. It was hypothesized that the more information a coach or

team has, the more likely teams will gain an advantage on the competition and

be more successful over the course of a season, or a multitude of seasons.

The definition of possession for the purpose of this study will be taken

41

from Pollard and Reep (2007). In which they state:











committed). (p. 1)

Other definable terms that were used for the researcher’s data collection were:

a.) shot: When a player makes an attempt to score by striking a ball in the

direction of the goal where the ball would or would not have actually

scored, hit the goal’s frame, or necessitated a save by the defensive team

or its goal keeper.

b.) shots on goal: When a player makes an attempt to score by striking the

ball in the direction of the goal where the ball would score, or hit one of the

posts, unless otherwise saved by the defensive team or its goal keeper.

c.) turnovers in the defensive half: A ball being passed from a player on the

defensive half of the field being intercepted by an opponent on the

defensive half of the field.

42

i.) A ball passed to an intended receiver already on the defensive half

of the field at any distance that is intercepted by an opponent.

ii.) A player losing the ball in the defensive half to an opponent while


iii.) A player improperly clearing the ball from their defensive half, in

that the ball was either completely missed or miss-hit so that the

ball stayed in the general area in which it was being cleared from.

iv.) A player turns the ball over to an attacker, and instead of allowing

the attacker to continue towards goal or taking a shot, the defender

fouls the attacker. If he ensuing direct kick scores, it will be

counted as a goal directly off of a turnover in the defensive half.

v.) A goal keeper mishandling a catchable shot or cross and being


In this chapter the researcher will describe a) research design, b)

participants, c) data collection, and d) data analysis.

Research Design

The researcher’s goal was to gain more informed information on how to

develop teams in terms of player placement, attacking styles and defensive

formations. It was hypothesized that the more information a coach or team has,

the more teams will be allowed to gain an advantage on the competition over the

course of a season or a multitude of seasons.

Is there a direct correlation to more turnovers in a team’s defensive half,

shots surrendered, and shots on goal surrendered, to losing matches? For this

43

study, the researcher narrowed the research down to turnovers in the defensive

half because those are the plays that tend to result in shots for the opposing

team.

The researcher looked at ten different NCAA men’s soccer games; the

games were chosen based on which games were being broadcast by The Big

Ten Network or WISN Milwaukee. The statistics were taken first hand by the

researcher; all games took place throughout the fall 2011 soccer season. This

study followed a qualitative design, using collective case study methods. Data

were obtained and collected using the statistics drawn from ten games across

fourteen NCAA Division I men’s soccer teams.

The researcher viewed ten games for fourteen different NCAA teams;


Michigan State University, Northwestern University, Notre Dame, The Ohio State



of Wisconsin-Madison, and University of Wisconsin-Milwaukee. To ensure the

researcher did not inflate the statistics by choosing particular games that may

skew the statistics to prove the hypothesis, the researcher watched game tapes

of teams that were broadcast on one of two local networks: The Big Ten Network

and WISN Milwaukee. At no point did the researcher view the previously charted

game statistics of the matches that were viewed. All statistics were taken first

hand by the researcher.

The research design for this study was qualitative. A collective case study

44

was done. Johnson and Christensen (2008) define case study research as

“research that provides a detailed account and analysis of one or more cases” (p.

406). Further, Creswell (2008) defines collective case studies as “case studies in

which multiple cases are described and compared to provide insight into an

issue” (p. 439). In the instance of this study, turnovers in the defensive half is the

issue explored through ten separate cases of NCAA Division I soccer matches

throughout the fall 2011 soccer season.

Johnson and Christensen (2008) explain that a collective case study

allows the researcher to compare several cases for similarities and differences

(p. 408). Johnson and Christensen also emphasize that “one can more effectively

test a theory by observing the results of multiple cases” and “one is more likely to

be able to generalize the results for multiple cases then from a single case” (p.

408). Studying multiple cases allowed this researcher to draw conclusions with

greater confidence as a result.

Participants

NCAA Division I Athletics.

The participants for this collective case study were players that were on

teams being broadcast by The Big Ten Network or WISN Milwaukee. These were

simply the Division I soccer games that were on TV during the fall of 2011. All

statistics were taken first hand by the researcher and at no point during the study

did the researcher have any interaction with the teams, players, or coaches.

According to its website, the NCAA oversees 89 championships in 23

sports. There are more than 400,000 student-athletes competing in three

45

divisions at over 1,000 colleges and universities within the NCAA. The National

Collegiate Athletic Association (NCAA) defines the parameters of its three

divisions on its website http://www.ncaa.org as follows:

Colleges and universities determine the level at which they will compete,

and new members must petition to join the division they choose. Once

division affiliation is determined, members must comply with rules

(personnel, amateurism, recruiting, eligibility, benefits, financial aid, and

playing and practice seasons) that vary from division to division.

The division structure enables each NCAA member institution to choose

the level of competition that best fits its mission. The NCAA does not

assign membership classification. NCAA rules permit limited multidivision

classification.

a.) Division II programs may classify one men’s and one women’s

sport at the Division I level.

b.) Division III programs may sponsor one men’s and one women’s

program at the Division I level but cannot offer athletically related

financial aid in those sports (several Division III members were

grandfathered in under previous rules and are permitted to provide

aid in those sports).

c.) Division I members may not classify any of their sports in other

divisions. (http://www.ncaa.org)

46

The researcher chose cases that only involved NCAA Division I schools. The

NCAA further defines the requirements of Division I athletic programs as follows:

Division I members must offer at least 14 sports (at least seven for men

and seven for women, or six for men and eight for women). The institution

must sponsor at least two team sports (for example, football, basketball or

volleyball) for each gender. The school also must have participating male

and female teams or participants in the fall, winter and spring seasons.

Each Division I program must play a minimum number of contests against

Division I opponents. The minimums vary by sport. (http://www.ncaa.org)

Schools.

Bowling Green State University.

According to http://www.bgsu.edu, Bowling Green State University is a

Division I soccer program. The men’s soccer team was led by head coach Eric

Nichols in 2011. Bowling Green was founded in 1910, in Bowling Green, Ohio.

As of 2001, they had nearly 20,000 students enrolled in the University.

Indiana University.

According to http://www.indiana.edu, Indiana University was founded in

1820 and is located in Bloomington, Indiana. In 2011, Indiana University’s

enrollment was nearly 41,000 students. The head coach of the Indiana Hoosiers

men’s soccer team in 2011 was Todd Yeagley.

Marquette University.

Marquette University was founded in 1881 in Milwaukee, Wisconsin

according to http://www.marquette.edu. In 2011, Marquette had a student

47

population of nearly 8,200 students. The head coach of the Marquette Golden

Eagles men’s soccer team in 2011 was Louis Bennett.

Michigan State University.

According to http://www.msu.edu, Michigan State University was founded

in 1855, with nearly 48,000 students as of 2011, located in East Lansing,

Michigan. The head coach of the Michigan State Spartans men’s soccer team in

2011 was Damon Rensing.

Northwestern University.

Northwestern University was founded in 1851 in Evanston, Illinois. It 2011,

it had a population of nearly 8,100 students. According to

http://www.northwestern.edu, the head coach of the Northwestern men’s soccer

team was Tim Lenhahan in 2011.

University of Notre Dame.

According to http://www.nd.edu, the University of Notre Dame is located in

South Bend, Indiana, with nearly 12,000 students as of 2011. It was founded in

1842. The head coach of Notre Dame men’s soccer in 2011 was Bobby Clark.

The Ohio State University.

The Ohio State University Buckeyes are located in Columbus, Ohio.

According to http://www.osu.edu, the university was founded in 1870 and in

2011, had a student population of nearly 57,000. The head coach of the

Buckeyes men’s soccer team in 2011 was John Bluem.

48

Pennsylvania State University.

The Pennsylvania State University website, http://www.psu.edu, states

that the university was founded in 1855 and is located in University Park,

Pennsylvania. The university had nearly 39,000 students in 2011. The head

coach of the Nittany Lions men’s soccer team in 2011 was Bob Warming.

University of Akron.

According to http://www.uakron.edu, the University of Akron is locaed in

Akron, Ohio, had a population of nearly 26,000 students in 2011, and was

founded in 1870. The head coach of Akron men’s soccer in 2011 was Caleb

Porter.

The University of Louisville.

The University of Louisville is located in Louisville, Kentucky. It was

founded in 1798, with a student population of nearly 22,000 in 2008. Louisville’s

head men’s soccer coach in 2011 was Ken Lolla. This is according to

http://www.louisville.edu.

University of Michigan.

According to http://www.umich.edu, the University of Michigan is located in

Ann Arbor, Michigan, with a student population of nearly 42,000 students in

2011. It was founded in 1817. The head coach of the men’s soccer team in 2011

was Steve Burns.

University of Wisconsin-Green Bay.

The University of Wisconsin-Green Bay is a Division I school, located in

Green Bay, Wisconsin and founded in 1965. In 2011, it had a student population

49

of nearly 6,600 students according to http://www.uwgb.edu. Green Bay’s head

coach in 2011 was Kris Kelderman.

The University of Wisconsin-Madison.

The University of Wisconsin-Madison was founded in 1848 and had a

student population of nearly 43,000 students in 2011. It is located in Madison,

Wisconsin, according to http://www.wisc.edu. The head coach of the Division I

men’s soccer program in 2011 was John Trask.

University of Wisconsin-Milwaukee.

The University of Wisconsin-Milwaukee was founded in 1885 in

Milwaukee, Wisconsin. It had a student population of nearly 31,000 students in

2011. According to http://www.uwm.edu, the head coach of the Milwaukee

Panthers men’s soccer program was Chris Whalley in 2011.

Cases

The research design for this study incorporated qualitative events.

Creswell (2008) defines qualitative research as an in-depth exploration of the

“event” of a bounded system which means it is separated out for research in

terms of time, place or some physical boundaries (p. 465). This researcher

conducted a collective case study, where ten NCAA Division I men’s soccer

games were analyzed in order to determine whether or not turnovers in the

defensive half contributed to wins, losses, or draws. The researcher looked at

one event, turnovers in the defensive half, as it related to wins, draws, and

losses, across ten cases. Table 10 illustrates those cases.

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Table 10: Events Compared to Cases

Event Cases

Turnovers in the Defensive Half

Case 1: University of Wisconsin-Madison vs. University of Wisconsin-Green Bay

Case 2: University of Wisconsin-Green Bay vs. University of Wisconsin-Milwaukee

Case 3: University of Wisconsin-Madison vs. University of Michigan

Case 4: Bowling Green University vs. The Ohio State University

Case 5: Northwestern University vs. The Ohio State University

Case 6: Northwestern University vs. Pennsylvania State University

Case 7: Pennsylvania State University vs. Michigan State University

Case 8: University of Notre Dame vs. Marquette University

Case 9: Indiana University vs. University of Michigan

Case 10: University of Akron vs. University of Michigan

Data Collection

The research design for this study was qualitative. A collective case study

was done. Johnson and Christensen (2008) define case study research as

“research that provides a detailed account and analysis of one or more cases” (p.

406). Further, Creswell (2008) defines collective case studies as “case studies in

which multiple cases are described and compared to provide insight into an

issue” (p. 439). In the instance of this study, turnovers in the defensive half is the

issue explored through ten separate cases of NCAA Division I soccer matches


51

The researcher viewed ten game tapes for fourteen different NCAA teams;


Michigan State University, Northwestern University, Notre Dame, Ohio State





skew the statistics to prove the hypothesis, the researcher watched games of

teams that were broadcast on one of two local networks: The Big Ten Network




For each game the researcher gathered information for each team,

specifically: turnovers in the defensive half, shots, shots on goal, goals, goals

directly off of a defensive turnover, and game result as a win, draw, or loss. This

information was gathered to analyze the impact that turnovers in the defensive

half would have on a Division I soccer match. The researcher’s main focus was

on turnovers in the defensive half as it pertained to wins, losses, and draws. The

researcher gathered data on shots and shots on goal as well, in order to

compare previously acceptable statistics to show subjectivity.

The researcher gathered this data on a simple spread sheet while viewing

each recorded game and was able to view the game more than once for

accuracy.

52

Data analysis

In the instance of this study, turnovers in the defensive half was the issue

explored through ten separate cases of NCAA Division I soccer matches


The researcher viewed ten game tapes from fourteen different NCAA

teams; Bowling Green State University, Indiana University, Marquette University,

Michigan State University, Northwestern University, Notre Dame, Ohio State





skew the statistics to prove the hypothesis, the researcher watched games of

teams that were broadcast on one of two local networks: The Big Ten Network




Data were then analyzed through an in depth discussion of each case as it

related to the event of turnovers in the defensive half with regard to wins, losses,

and draws.

53

Chapter Four: Findings

Introduction

The overall purpose of this study was to research a variable that has not

been discussed before (turnovers in the defensive half of the field) and evaluate

how these turnovers contribute to wins, losses, and draws in soccer matches.

In a game with so few statistics available to be followed, it was this

researcher’s opinion that soccer needed to collect more statistics, including the

more difficult (qualitative) statistics, such as turnovers in the defensive half.

Furthermore, if the consequences of turnovers in a team’s defensive half

becomes qualitatively significant, it may result in teams re-thinking their offensive

and defensive strategies relative to building their attacks further from their

defensive goal than was previously accepted.

The researcher’s goal was to gain more informed information on how to

develop teams in terms of player placement, attacking styles and defensive

formations. It was hypothesized that the more information a coach or team has,

the more teams will be allowed to gain an advantage on the competition over the

course of a season or a multitude of seasons.

For this study, the researcher narrowed the research down to turnovers in

the defensive half because those are the plays that tend to result in shots for the

opposing team. The researcher looked at ten different NCAA men’s soccer

games; the games were chosen based on which games were being broadcast by

The Big Ten Network or WISN Milwaukee. The statistics were taken first hand

by the researcher; all games took place throughout the fall 2011 soccer season.

54

This study followed a qualitative design, using collective case study

methods. Data were obtained and collected using the statistics drawn from ten

games across fourteen NCAA Division I men’s soccer teams.

In this research, the researcher viewed ten games from fourteen different

Division I NCAA teams; Bowling Green State University, Indiana University,

Marquette University, Michigan State University, Northwestern University, Notre

Dame, The Ohio State University, Pennsylvania State University, University of

Akron, University of Louisville, University of Michigan, University of Wisconsin-

Green Bay, University of Wisconsin-Madison, and University of Wisconsin-

Milwaukee. This was an original study and all research was taken first hand by

the researcher.

The average amount of turnovers in the defensive half was proven to be

6.9 over these ten games. When a team turned the ball over more than 6.9

times, they lost seven times and won five. When a team turned the ball over in

the defensive half less than 6.9 times, they won five and lost three. This

correlation does not mean causation, but does suggest a link.

Data findings

Case 1: University of Wisconsin-Madison vs. University of

Wisconsin-Green Bay.

On October 19th, 2011, the University of Wisconsin-Madison played a

Division I contest at the University of Wisconsin-Green Bay. Information provided

by http://www.ncaa.com detailed that, UW Madison registered seven shots with

two shots on goal, while UW-Green Bay registered eleven shots, with six shots

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on goal. In contemporary thinking, UW-Green Bay had the advantage in winning

the game by outshooting their opponent in that shots and shots on goal tend to

dictate the victor. Table 11 shows that not only were UW-Madison outshot; they

also turned the ball over with more frequency in the defensive half. In

observations of the games that followed, the researcher found that when a team

lost by multiple goals, they tended to lose in each of the three statistically kept

categories (turnovers in the defensive half, shots, and shots on goal).

Table 11: Madison Vs Green Bay

Turnovers in

Defensive Half

Shots Shots

on Goal

Goals

Goals directly off of a

defensive Turnover

Win/Loss/Draw

University of

Wisconsin-Madison

10 7 2 0 0 Loss

University of

Wisconsin-Green Bay

7 11 6 2 0 Win

Case 2: University of Wisconsin-Green Bay vs. University of

Wisconsin-Milwaukee.

On September 28th, 2011, UW-Green Bay traveled to UW-Milwaukee for

an intrastate match. UW-Milwaukee had more shots and more shots on goal than

their opponent, but also had more turnovers in the defensive half. Despite the

turnovers, UW-Milwaukee went on to victory by being one of three games where

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a goal resulted directly from a turnover in the defensive half. Similar to the other

recorded matches, the team that scored directly off of a turnover in the defensive

half won the game.

In the researcher’s opinion, scoring directly off of a turnover is one of the

most influential causes in winning. In this match, both teams turned the ball over

more than the average of 6.9 so neither was proven to be particularly cautious in

their defensive half. Olsen and Larsen (1997) found that breakdown attacks

(counterattacks) resulted in more scoring opportunities and goals than longer

attacks (elaborate attacks). Further, univariate and multivariate analyses reveal

that counterattacks were more effective than elaborate attacks when playing

against an imbalanced defense. When UW-Milwaukee scored the goal directly off

of a turnover, UW-Green Bay was not in a position to defend, in that they were

caught off guard by the turnover. With the weight of a score directly off of one of

UW-Green Bay’s turnovers, UW-Milwaukee came away with the victory.

Table 12: Green Bay Vs Milwaukee

Turnovers in

Defensive Half

Shots Shots

on Goal

Goals

Goals directly off

of a defensive Turnover

Win/Loss/Draw

University of

Wisconsin-Green Bay

8 20 9 2 0 Loss

University of

Wisconsin Milwaukee

11 24 10 3 1 Win

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Case 3: University of Wisconsin-Madison vs. University of Michigan.

On October 9th, 2011, the University of Wisconsin-Madison traveled to the

University of Michigan for a Big Ten Conference match. This game was a

statistical conundrum. Madison had fewer shots, fewer shots on goal, and more

turnovers in the defensive half but still won the match. In statistics, not all games

end the way the numbers may imply. According to Reep and Benjamin (1968)

teams:

…demonstrated the existence of random chance, meaning that despite an

excess of shots by one team in any single match, the opposing team can

still score more goals and thus win the match. However, they also showed

that, in the long run, the team producing the most shots tends to score

more goals with a goal-to-shot ratio of approximately 1:10. This implies

that the actions and outcomes in soccer matches can be described on the

basis of probability (p. 270).

In soccer, the statistic that will always carry the most weight is goals for and

goals against. In this match, Madison won in this category and therefore

deserved to win the game.

58

Table 13: Madison Vs Michigan

Turnovers in

Defensive Half

Shots Shots

on Goal

Goals

Goals directly off


Win/Loss/Draw

University of

Wisconsin-Madison

9 6 5 2 0 Win

University of

Michigan

5 23 6 1 0 Loss

Case 4: Bowling Green University vs. The Ohio State University.

On October 5th, 2011, The Ohio State University defeated Bowling Green

University 1-0. In this match, Ohio State turned the ball over in the defensive half

less than the average (6.9), had more shots, more shots on goal, and, in the end,

more goals. If the sample size of one game was used to prove a hypothesis, this

would have been the ideal game. Ohio State proved across the statistics of a

match, and in the final score of the match, that they were the superior team. In

this particular instance, the hypothesis has been proven.

Table 14: Bowling Green Vs Ohio State

Turnovers in

Defensive Half

Shots Shots

on Goal

Goals

Goals directly off


Win/Loss/Draw

Bowling Green

University

8 19 6 0 0 Loss

The Ohio State

University

6 24 11 1 0 Win

59

Case 5: Northwestern University vs. The Ohio State University.

On October 9th, 2011, Northwestern University traveled to The Ohio State

University for a Big Ten Conference matchup. Similar to Ohio State’s match from

four days earlier where they won in the four stated statistics, Northwestern won

all four statistics in this match. Northwestern turned the ball over in the defensive

half six times, less than the average (6.9), and had more shots and more shots

on goal than Ohio State while winning the game. This is another instance where

using a small sample size of one game proved the hypothesis.

Table 15: Northwestern Vs Ohio State

Turnovers in

Defensive Half

Shots Shots

on Goal

Goals

Goals directly off


Win/Loss/Draw

Northwestern University

6 12 6 3 0 Win

The Ohio State

University

7 11 5 2 0 Loss

Case 6: Northwestern University vs. Pennsylvania State University.

On October 16th, 2011, Northwestern University visited Pennsylvania

State University in another Big Ten Conference match. In this match,

Northwestern lost in all three categories yet still won the game. When compiling

the statistics for this match, the researcher noted how over matched

Pennsylvania State was. Pennsylvania State had a game plan of clearing the ball

from their defense so that Northwestern’s superior attack would not force

turnovers. As mentioned in the first chapter of this thesis, the talent in Division I

60

soccer matches should be similar from team to team. That was not the case in

this instance. With Northwestern finishing first in the Big Ten Conference, and

Pennsylvania State finishing last, Northwestern appeared to be the better team.

Pennsylvania State was dominated in ball control, 50-50 balls, and overall

physicality by the Northwestern squad.

This was a game where statistics did not tell the full story of the match at

hand. This happens in all sports and is the exact reason why large sample sizes

are encouraged to validate the research. As is stated by Tenga, Ronglan, and

Bahr (2010):

The broader measures of offensive effectiveness, such as scoring

opportunities and shots at goal, are commonly used as an alternative to

goals scored due to the naturally low probability of scoring (about 1%) in

soccer match-play. These measures may enable soccer practitioners to

objectively see behind single match results, which are often influenced by

chance (p. 1).

During research, there are bound to be outliers that simply do not follow the

regular flow of statistics. This game was one of those instances.

Table 16: Northwestern Vs Penn State

Turnovers in

Defensive Half

Shots Shots

on Goal

Goals

Goals directly off


Win/Loss/Draw


8 6 4 1 0 Win

Pennsylvania State

University

3 12 5 0 0 Loss

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Case 7: Pennsylvania State University vs. Michigan State University.

On October 9th, 2011, Pennsylvania State visited Michigan State for

another Big Ten Conference game. As Table 17 illustrates, Michigan State had

fewer turnovers, almost three times as many shots, and more shots on goals,

and did not surrender a single shot on goal to Pennsylvania State. This was a

dominating performance by Michigan State, despite the score merely reflecting a

1-0 victory. As mentioned in the other Pennsylvania State match, Pennsylvania

State finished last in the Big Ten Conference. They rarely formulated dangerous

attacks and severely lacked in possession. This was another instance of a

dominating statistical performance for the hypothesis.

Table 17: Penn State Vs Michigan State

Turnovers in

Defensive Half

Shots Shots

on Goal

Goals

Goals directly off


Win/Loss/Draw

Pennsylvania State

University

6 4 0 0 0 Loss

Michigan State

University

3 11 7 1 0 Win

Case 8: University of Notre Dame vs. Marquette University.

The University of Notre Dame visited Marquette University on October

12th, 2011. This game was a perfect microcosm for the hypothesis. With

conventional thinking, Notre Dame won the battle of statistics by outshooting

Marquette, 17-12, and by putting more shots on goal than Marquette at 7-4. Had

the statistics stopped there, it would have looked like Notre Dame was the

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superior team. But, by digging further, it can plainly be seen that Marquette did a

far better job in controlling the ball on their defensive half (surrendering a mere

four turnovers) and capitalized on one of Notre Dame’s ten turnovers into what

turned out to be the game winning goal. Without keeping the statistics of

turnovers in the defensive half, this game would not have had this avenue of

dissection.

According to http://www.ncaa.com, the 2010 NCAA final three games,

between divisions I, II, and III, the team with more shots won 77% of the time and

the team with more shots on goal won 56% of the time. It is clear that shooting

and shooting accurately can give a team a better chance at winning. This was

true in the game between Marquette and Notre Dame.

Table 18: Notre Dame Vs Marquette

Turnovers in

Defensive Half

Shots Shots

on Goal

Goals

Goals directly off


Win/Loss/Draw

University of Notre Dame

10 17 7 0 0 Loss

Marquette University

4 12 4 1 1 Win

Case 9: Indiana University vs. University of Michigan.

In one of the more dominating performances of the ten games the

researcher watched, Indiana University defeated University of Michigan on

October 15th, 2011. Indiana turned the ball over in the defensive half only one

time, which is the lowest of the ten games viewed. As was discussed in the

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previous match, in looking at contemporary statistics, Indiana and Michigan were

even on shots while Michigan held the advantage in shots on goal. When adding

turnovers in the defensive half and goals directly off of turnovers in the defensive

half, Indiana won going away and can be looked at as the clear cut winner.

When watching this game, it was noted by the researcher that Michigan

tended to take more erratic shots, giving them a tally on the stat sheet, but a very

low probability of it turning into a goal. As a result, Michigan was going against a

more formulated and organized defense. A study done by Olsen and Larsen

(1997) showed more scoring opportunities and goals from breakdown attacks

(counterattacks) started when the opponent defense was imbalanced rather than

balanced. This is one of the reasons Indiana University played so well. Since

they rarely turned the ball over in their defensive half, they were rarely playing

defense with an imbalanced formation.

Table 19: Indiana Vs Michigan

Turnovers in

Defensive Half

Shots Shots

on Goal

Goals

Goals directly off


Win/Loss/Draw

Indiana University

1 13 5 4 2 Win

University of

Michigan

7 13 7 1 0 Loss

Case 10: University of Akron vs. University of Michigan.

On October 18th, 2011, the University of Akron visited the University of

Michigan. In this match both teams turned the ball over more than the average of

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6.9 per game. Despite Michigan having more turnovers than Akron, Michigan still

won the match. Along with that, Michigan tallied more shots and more shots on

goal. Reep and Benjamin (1968) stated that, “as a team possession advances

towards a goal, the defending opponents progressively converge into a more

compact formation and hence become closer to the ball and therefore improve

their chances of preventing penetration” (p. 275). Despite both teams turning the

ball over in the defensive half more than the average of 6.9, and accumulating

forty one shots between them, only one goal was scored. It is possible that both

teams kept a strong focus on their defense which may have allowed for more

shots. But, if their players are well positioned, it becomes difficult to score.

This game illustrates how nicely these three statistics can work together.

Despite the turnovers, Michigan overcame them by taking more shots and more

shots on goal.

Table 20: Akron Vs Michigan

Turnovers in

Defensive Half

Shots Shots

on Goal

Goals

Goals directly off


Win/Loss/Draw

University of Akron

8 19 7 0 0 Loss

University of

Michigan

11 22 10 1 0 Win

65

Summary of cases

In table 21, the reader will find the accumulation of the ten games and

their statistics. Although the researcher kept statistics on shots and shots on

goal, for the purposes of this table, the researcher used statistics given by

http://www.ncaa.com to insure accuracy. These games were not put in order of

the date in which they were played; rather, they were put in the order of the

researcher’s viewership. Each game carries its own story, as statistics can never

fully describe the details of a soccer match.

66

Table 21: Cumulative Match Totals

Turnovers in the

Defensive Half

Shots Shots on

Goal Goals

Goals directly off of a defensive Turnover

Win/ Loss/ Draw

University of Wisconsin-

Madison 10 7 2 0 0 Loss

University of Wisconsin-Green

Bay 7 11 6 2 0 Win

University of Wisconsin-Green

Bay 8 20 9 2 0 Loss

University of Wisconsin-Milwaukee

11 24 10 3 1 Win

University of Wisconsin-

Madison 9 6 5 2 0 Win

University of Michigan

5 23 6 1 0 Loss

Bowling Green State University

8 19 6 0 0 Loss

The Ohio State University

6 24 11 1 0 Win


6 12 6 3 0 Win

The Ohio State University

7 11 5 2 0 Loss


8 6 4 1 0 Win

Pennsylvania State University

3 12 5 0 0 Loss

Pennsylvania State University

6 4 0 0 0 Loss

Michigan State University

3 11 7 1 0 Win

University of Notre Dame

10 17 7 0 0 Loss

Marquette University

4 12 4 1 1 Win

Indiana University 1 13 5 4 2 Win University of

Michigan 7 13 7 1 0 Loss

University of Akron 8 19 7 0 0 Loss Michigan University

11 22 10 1 0 Win

67

It has been the researcher’s contention that turnovers in the defensive half

compliment shots and shots on goal in telling each game’s story. If the reader

takes the time to look closer at each of these games, they will realize that in only

two games did the winning team lose in the categories of shots, shots on goal,

and had more turnovers in the defensive half (UW-Madison vs. Michigan, and

Northwestern vs. Penn State). As a result it seems that the researcher’s

hypothesis although not statistically significant, provides a viable outlet for

statistical analysis of a soccer match.

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Chapter 5: Conclusions

Introduction

In looking at the ten Division I NCAA games, the reader has to understand

that each game tells a particular story. Some games proved the hypothesis

correct on a small scale, other games disproved the hypothesis. In any event, the

researcher believes that turnovers in the defensive half, coupled with commonly

used statistics such as: shots and shots on goal, can strengthen the viewer’s

ability to follow game statistics and draw their own conclusions as to how games

unfolded or should have unfolded.

The two games that disproved the theory should be looked at a little more

closely. When UW-Madison beat Michigan, and Northwestern beat Pennsylvania

State, both Michigan and Pennsylvania State won the statistical battle of having

less turnovers in the defensive half, more shots, and more shots on goal. It has

been assumed by the researcher that the higher the skill level, the less the

experimental statistics identified in this study will matter. In both of the

aforementioned games, UW-Madison and Northwestern lost the statistical

contests, but clearly dominated the game. Late in both games, both winning

teams opted for possession rather than going for more goals. In their attempts to

control the clock and lessen the chance of comebacks, they played it safe. They

kept the ball, and surrendered wild shots by the losing teams that had low

possibilities for success. Furthering this point, both winning teams ended up

turning the ball over more in their defensive half but were in fine position for

defending the turnovers with multiple defenders behind the ball. In soccer, this

69

style of play can be called “going into a shell”. It is a style of play where the team

with more goals places nearly all of their players on defense, allows more erratic

shots, while taking away the losing teams ability to get unimpeded shots on goal.

Through statistical comparisons and projections, teams can win with the strategy,

but it makes games look much closer than they actually were. Both Michigan and

Penn State finished the 2011 season last in the Big Ten Conference, with 1-5

and 0-6 records, respectively.

Higher skill level has less correlation to turnovers in the defensive half

When the researcher was recording the statistics for this study, it quickly

became apparent that Division I teams had much higher skill levels than the

Division III team the researcher was a part of, Carroll University in Waukesha,

Wisconsin. The players in the back of the formation at the Division I level had as

much talent as the players who played in the front (the attack) for most Division

III teams. Division I teams generally have so much talent throughout their

respective squads, turnovers in the defensive half were rare occurrences, and

nearly nonexistent. This was illustrated in the case when Indiana University

turned the ball over one single time against Michigan but was still able to win the

match.

Over the past several years, the researcher had been thinking of this

statistic while coaching at Carroll University. It had long been noticed that Carroll

had won numerous victories week in and week out, and year in and year out over

conference opponents who committed multiple, untimely turnovers in the

defensive half. Every team that played in the Midwest Conference would

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seemingly put their best players in the attack (offense), leaving their weaker

players to defend. In most matches, these teams committed costly turnovers in

the defensive half, and resulted in multiple shots on goal for Carroll. This is not to

suggest that there have not been great teams to come through the Midwest

Conference, but in this ten team conference there have always been five teams

that play in the same fashion every year. This virtually guaranteed victories for

their opponents.

Unexpected Significance

When initially designing this study, the researcher expected turnovers in

the defensive half to dictate the victor similarly to recent NFL Super Bowls, or the

2010 NBA Finals. The results indicated that the impact of turnovers in the

defensive half dictated victories in over 60% of the matches, not the 90% which

had been assumed. What was interesting to discover, was the number of wins

after scoring a goal directly from a turnover in the defensive half (3 of 3 matches).

As was mentioned earlier in this study, the significance of momentum should not

be ignored in an athletic event. Iso-Ahola and Mobily (1980) stated that

momentum is, “A gained psychological power which may change interpersonal

perceptions and influence physical and mental performance” (p. 1). In this

instance, Iso-Ahola et al. illustrated that players’ or teams’ perceptions of being

better or becoming stronger because of a specific play or sequences of plays.

In the ten games that were studied, three games had teams who scored

goals directly from turnovers in the defensive half. It should be noted that in

Super Bowls from 2006 to 2011, teams that scored points from defensive

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turnovers won their games four of four times. In the remaining two games, the

defense did not score points for their team, but did create more turnovers than

their opponent and resulted in wins in both instances. This is significant to the

researcher because it has become apparent that the mere act of turning the ball

over to the opposition is significant, but not nearly as significant as allowing that

turnover to turn into a score.

In another finding, the researcher found that although a turnover in the

defensive half did not prove to be statistically significant, it did however prove to

be more significant than previously charted statistics such as shots and shots on

goal. In the following chart, the researcher illustrates the three statistical

categories. Turnovers in the defensive half were taken first hand by the

researcher, while shots and shots on goal were kept by NCAA statisticians found

on http://www.ncaa.com.

Table 22: Statistics Averaged

Average Above the Average

Below the Average

Turnovers in the defensive half

6.9 5 wins, 7 losses 5 wins, 3 losses

Shots 14.3 3 wins, 5 losses 7 wins, 5 losses

Shots on Goal 6.1 4 wins, 4 losses 6 wins, 6 losses

Data taken from: http://www.ncaa.com & first hand by the researcher

As the researcher has previously discussed, turning the ball over in the

defensive half more than 6.9 times in the ten games studied resulted in losing

58% of the time. Turning the ball over less than the average resulted in winning

63% of the time. Although not statistically significant, it does suggest a

correlation. With regard to previously accepted soccer statistics, such as shots,

72

and shots on goal, there were no correlations to wins. When outshooting the

average of 14.3 shots per game, teams won 38% of the time. When teams shot

less than the average, those teams won 58% of the time. Based on the results of

this ten game series, shooting less but more accurately was definitively better for

the winning teams. This proved not to be true in instances where teams shot the

ball and it struck a post, was saved, or actually scored. These teams actually

won 50% of the matches by outshooting the 6.1 average and won 50% of the

matches by shooting less than the 6.1 average.

Implications

When the researcher was a young coach for a local high school soccer

team, he implemented tactics that he believed would be advantageous for his

team. He stressed the following basic fundamentals: possession, passing, and

shooting. These behaviors ensured that his team looked skillful, but did not

necessarily correlate with winning matches. His teams made significant

advances in working together, finding open teammates, and making runs off the

ball. As the researcher watched one particular game unfold, the team was doing

exactly as they were coached. They were passing, moving, and generally had

good communication. The problem was they were doing all of this only forty

yards from their own goal, which has been defined as within their defensive half.

The opposition was all but allowing these passes to take place in front of them,

waiting for a mistake and an easy goal scoring opportunity.

As the game progressed, the researcher had a feeling of impending

disaster. Shortly after this feeling, the game began to fall apart. The opposition

73

stole a pass between a midfielder and a defender in the defensive half, made a

simple pass forward to a teammate running towards the goal and it resulted in a

goal for the opposition.

This game occurred late in this particular season; the team had months of

practices where passing, possessing, and shooting were considered to be the

keys to success. With this in mind, the researcher’s team went back to what was

explained to be a successful game plan. The team went back to what they were

taught. They were passing and maintaining possession of the ball, but doing this

thirty yards from our own goal (defensive half). After a multitude of successful

passes, and no shots or shots on goal for the researcher’s team, the opposition

stole another simple pass intended for a defender in the defensive half for yet

another goal. As has been illustrated in this study, surrendering goals in the

defensive half resulted in three losses for three different Division I NCAA teams.

This game was no different. The researcher’s team lost the match, 2-0.

This research was intended to show that soccer is not won by

accumulating passes, or by simply having more skill than the other team. The

keys to winning soccer matches will always be different from team to team, which

is one of many reasons it is referred to as “the beautiful game”. The researcher

is confident in saying that one factor that does not promote winning is turning the

ball over in the defensive half.

Implementations and Recommendations

Possession of the ball will always be large part of soccer matches.

Possession is a way to tire the defense; it can control the clock so that opponents

74

do not have a chance to score. This tactic can uncover weaknesses in the

opposition. It is each coach’s prerogative to teach possession but it should be

cautioned as to where this possession is taking place. If a team does not have

the skill to possess the ball near the attacking goal, forcing them to possess in

front of their defensive goal, the team should work on other means of becoming

successful. In soccer, there are multitudes of ways to be successful. Whether a

given team chooses to play possession of the ball, fast break, play eleven behind

the ball or a combination of these styles. The researcher has two suggestions;

refrain from playing the weakest players in the rear of the formation and not

making passes between defenders that do not gain a tactical advantage in their

own defensive half.

75

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final thesis

Documents

soccer match

research problem

research questions

general soccer

drago research facilitator

robinson date mentor

susan hefferon date

carroll university library