NAME: JONATHAN GRIFFITHS
UNIVERSITY NUMBER: 07002313
SCHOOL OF SPORT
UNIVERSITY OF WALES INSTITUTE, CARDIFF
POSSESSION LENGTHS IN THE ENGLISH FOOTBALL CHAMPIONSHIP
Table of Contents
Page
CHAPTER I
Introduction
1.0 Introduction
1
1.1 Background
1
1.2 Statement of Problem
3
1.3 The Rationale of the Study
3
1.4 Hypothesis
4
1.5 Aim of the Study
4
1.6 Limitations
4
1.7 Delimitations
5
CHAPTER II
Review of Literature
2.0 Review of Literature
6
2.1 History of Hand and Computerised Notational Analysis
6
2.2 Notational Analysis of Soccer
8
2.3 Attacking Profiles and Tactics in Soccer
10
2.4 Possession and its Determinants
12
2.5 Effects of Match Status on Possession
13
2.6 Effects of Game Location in Soccer
14
2.7 Effects of Opposition Strength on Attacking Profiles
15
CHAPTER III
Methodology
3.0 Methodology
17
3.1 Introduction
17
3.2 Subjects
17
3.3 Equipment
18
3.4 Pilot Study
18
3.5 The Final System
20
3.6 Operational Definitions
22
3.7 Data Collection Procedure
22
3.8 Reliability
23
3.9 Data Processing
23
CHAPTER IV
Results
4. 0Results
24
4.1 Introduction
24
4.2 Reliability
24
4.3 Match Status
25
4.4 Match Location
26
4.5 League Position
27
4.6 Match Half
28
4.7 Goals
29
4.7 Shots
30
CHAPTER V
Discussion
5.0 Discussion
32
5.1 Limitations
35
CHAPTER VI
Conclusion
6.0 Conclusion
36
6.1 Recommendations for Fture Research
37
References
Appendix A - Printed A4 paper with Final notation system
List of tables
Table
Title
Page
Table 1
Snapshot of the First Pilot notation sheet
19
Table 2
An example of the second notation system
20
Table 3
An example of the final notation system
21
Table 4
Intra-observer reliabiliy
24
Table 5
Mean and medium over the data set dependant on match status
26
Table 6
Mean and medium over the data set dependant on match location
27
Table 7
Mean and medium over the data set dependant on opponents
27
Table 8
Mean and medium over the data set dependant on halve
28
Table 9
Frequency of goals dependent on possession length
29
Table 10
Frequency of shots dependent on possession length
30
List of figures
Figure
Table
Page
Figure 1
Mean and medium over the data set dependant on match status
26
Figure 2
Mean and medium over the data set dependant on match location
27
Figure 3
Mean and medium over the data set dependant on opponents
28
Figure 4
Mean and medium over the data set dependant on halve
29
Figure 5
Frequency of goals dependent on possession length
30
Figure 6
Frequency of shots dependent on possession length
31
Acknowledgements
Thanks to Nic James for your help and support throughout my dissertation. Thanks to my
family as I will be ever grateful for your help guidance and always being there.
i
Abstract
In soccer, possession of the ball has been linked with success, however little research has
been afforded to its determinants. Using data from Swansea City’s 2008-2009 English
Football League Championship. 8 matches were analysed using a hand notation system
and analysis took place in SPSS (SPSS 17.0, SPSS Inc, Chicago, Illinois). In particular,
five variables were examined: match status (i.e. whether the team was winning, losing or
drawing), match opponents (i.e. whether opponents were higher or lower in the final
league standings), match location (i.e. playing at home or away), match half (i.e. first half
or second half) and outcome of possession (i.e. goal or a shot). Analysis showed if these
five variables were statistically significant to possession length (i.e. number of passes in a
possession). The findings showed Swansea City had longer possession when they were
losing rather than winning or drawing, also Swansea City had longer possession when
playing away rather than home. Possession lengths increased whilst playing teams higher
in league status. However, there was no significant difference between possession length
and halves. The findings of the study highlighted a number of variables that could explain
possession lengths in soccer. This suggests possession should be looked at from all angles
and not only be investigated regarding goals scored. A combination of these variables
could predict possession lengths and outcomes in soccer
ii
CHAPTER I
INTRODUCTION
1.0 Introduction
1.1 Background
The English Football association was formed in 1863; it was not until 2004-2005 season
that the first English football league championship got underway. The English football
championship was previously known as the football league first division. The football
league first division was the top division of the English football league between 1892 and
2004 and the highest in English football until the FA Premier League was created in
1992. The English football league championship is now the secondary tier in English
football. According to Jones (2005) the English football championship was the wealthiest
non- top flight division in the world in the first season and the sixth richest division in
European football. Sponsorship and television coverage has grown and this has increased
its national and worldwide popularity. Due its popularity and the finance in soccer, every
team attempt to improve and to progress in anyway they can. To improve performance,
coaches and individuals are using multi-disciplinary areas such as sports science and
biomechanics. Performance analysis is steadily increasing in many sports and in soccer it
is seen as a means of improving sporting performance.
Performance analysis investigates actual sports performance, during training or matches.
Hughes (1998) describes the purpose of performance analysis as Analysis of Technique,
Tactical Analysis and Evaluation, Analysis of Movement and Work-Rate, Coach and
Player Education, Performance Databases, Data Mining and Modelling. Analysis of
performance and feedback from coaches is important in every sport. Hughes (2004)
identified feedback as being central to the performance improvement process, whereby it
is vital for the feedback given to the individual or team to be both accurate and precise.
Using performance analysis provides relevant details to players and also assists coaches.
Coaches who do not use analysis of performance limit their ability to recall. Research has
suggested that coaches’ feedback can be subjective as it is based around recall of match
events which are often inaccurate (Franks and McGarry., 1996). Franks (2004) identified
coaches are limited in their ability to accurately recall critical incidents that occur during
competitions and the feedback provided may, therefore be incomplete, imprecise and
inaccurate.
1
Soccer analysis has been broadly researched over the years. It has been categorised into
patterns of play and movement analysis. Scoring goals is the ultimate determinant of
success for a soccer team and has received much attention in notation literature (Jones et
al., 2004) Retaining possession of the ball is important during a game of soccer. For a
team to score they will usually be in possession of the ball. However, a number of
notation analysis studies have divided support for different possession lengths leading to
goals and goal scoring opportunities. Bate (1998), for example found that moving the
ball forward quickly creates more opportunities of scoring goals and creating chances.
Bate concluded his study by favouring a more direct strategy rather than possession
football. Grant et al. (1999) and Hook and Hughes (2001) also agreed with Bate (1988).
Grant et al. (1999) found in the 1998 World Cup successful teams were able to keep the
ball for longer sequences of play than unsuccessful teams. The successful teams were able
to penetrate the defence more therefore creating more goal scoring opportunities. Hook
and Hughes (2001) suggested keeping the ball for longer durations would be an indication
of success. However, there was no significant difference found in the number of passes
leading to a goal in an attacking situation. Stanhope (2001) found in World Cup 1994,
there was no decisive evidence that proved that the duration of possession would end a
success.
However, research on possession of the ball has a limited amount of literature available
when paying attention to its determinants. Studies such as Pollard (1986), Thomas et al.
(2004) and Lago and Martin (2007) investigated the importance of match location on
teams’ performance. The findings of the studies showed when teams played a home
match they held possession for longer spells, compared to playing away. However, the
studies concluded that depending on the location, a team would play different formations
and strategies to improve performance. James et al. (2004), Bloomfield et al. (2005) and
Lago & Martin (2007) each completed research on ‘possession duration’ and the ‘effects
of match status’ (winning, losing or drawing). The studies found that teams had longer
possession in the games when they were losing than when they were in the lead, despite
the teams being successful and unsuccessful.
2
Opposition strength is another variable that has limited research. Strength may affect
possession duration. The quality of opposition has been identified as influencing
performance during global performance measures; however Sasaki et al. (1999) and
Tucker et al. (2005) were not able to integrate these variables in their studies. In much
football literature, opposition strength has been ignored. Teams however, have been
regarded as “successful” or “unsuccessful” based on their effectiveness of winning games
in a particular tournament (e.g. Hook and Hughes, 2001; Hughes and Churchill, 2005).
Scoulding et al. (2004) identified a problem when looking at “successful” or
“unsuccessful teams. The author suggested; teams may be high quality but are deemed to
be unsuccessful due to them not progressing through a certain tournament.
Another variable looked upon in this study is the difference in possession length in each
half of the game (i.e. first half and second half). In notational analysis there has not been
any research on this variable.
1.2 Statement of problem
This study will investigate possession length in soccer. To determine the differences or
similarities within the data, depending on the outcome, match status, match location,
opposition strength and possession in each half.
1.3 The Rationale of the study
To date, there has been limited published research on the English Football Championship
regarding Performance Analysis. Previous literature identifies a gap in the research,
where studies have only identified International teams or top European club teams while
researching patterns of attacking play. The English Football Championship has increased
its profile over the last ten years, with Sky Sports covering more live games. However,
there have been no published studies on an English Domestic Football Championship
team. Variables such as match status, venue and opposition strength have not been
accessed to use in the English Domestic Football Championship. This investigation will
allow research to be completed on an English Domestic Football Championship team.
3
1.4 Hypothesis
1. The team will have higher possession sequences when losing in a match situation.
2. The team will have higher possession sequences when playing at home rather than
away.
3. The team will have a shorter number of passes (four and under) leading to a Goal.
4. The team will have higher possession sequences when playing opposition lower in
the table.
5. The team will have higher possession sequences in the first 45 minutes of play
(first half).
1.5 Aim of the Study
1. To devise a hand notation system which will effectively assess possession
sequences and outcomes
2. To explore possession as a concept within soccer.
3. To identify key aspects which contribute to possession in soccer.
1.6 Limitations
1. Video availability- matches were available at the time.
2. Literature is limited in some variables that are being researched.
4
1.7 Delimitations
1. Size of the sample was kept at 8 matches.
2. All matches were from the English Football League Championship.
3. The matches consisted of professional footballers
5
CHAPTER II
REVIEW OF LITERATURE
2.0 Review of literature
2.1 History of hand and computerised notational analysis
Historically, coaching has been based on subjective observations of athletes and teams.
Hughes (2004) identified feedback as being central to the performance improvement
process, whereby it is vital for the feedback given to the individual or team to be both
accurate and precise. Performance analysis provides relevant details to players and also
assists coaches with feedback. Coaches who do not use analysis of performance limit
their ability to recall. Franks and Miller (1986) and Franks (2004) both suggested coaches
are limited in their ability to accurately recall critical incidents that occur during
competitions and the feedback provided may therefore, be incomplete, imprecise and
inaccurate. Hughes (2004) stated notational analysis is an objective way of recording
performance so that key elements of that performance can be quantified in a valid and
consistent manner. Hughes and Franks (2004) suggested four main purposes to notational
analysis data, as listed below.
1
Analysis of movement
2
Tactical evaluation
3
Technical evaluation
4
Statistical compilation
The history and development of Notational analysis varies between sports. Numerous
sporting disciplines have used Notational analysis, such as Tennis (Hughes and Taylor
1998), Soccer (Reep and Benjamin 1968) and Netball (Otago 1983). However, Hughes
and Franks (2004) identified some sporting disciplines have limited or no notational
research published. Nevertheless, this does not indicate that systems are not in use in the
disciplines or do not exist.
The first publication in notation in sport was by Fullerton (1912, cited by Hughes and
Franks, 2004). Fullerton (1912) explored the different combinations between baseball
players batting, pitching and fielding. The author also investigated the probabilities of
success in different combinations (Hughes and Franks 2004). The first attempt to devise a
6
notation system for specific sport analysis was Messersmith and Bucher (1939, cited in
Hughes and Franks, 2004). Messersmith and Bucher (1939) attempted to monitor distance
covered by specific basketball players during a match. Since Messersmith and Bucher
(1939), hand notation system has progressed and been published for sporting situations.
Hand notation system can provide rich data when data is hand gathered and processed in
a database. Hand notation systems are easily created and are very accurate but have
limitations. As the system becomes more sophisticated and produces an increased amount
of data, the hours of work involved processing the data into forms of outputs that are
meaningful to the coach, athlete or scientist increase (Hughes and Franks, 2004). As the
analysis becomes specific, the data required increases. The increased amount of data leads
to more times spent by operators learning notation systems and processing the data into
forms of output which is ready for coaches, players and other sporting staff.
However, a computerised notation system has created advantages within data processing
and the forms of output data. The systems reduced the amount of hours it takes to process
the data and it can present data which makes the results clear for the coach and performer
to understand, an example would be graphical forms. The computerised notation system
can produce information for many purposes which assist the coaching process. Franks et
al., 1983, p.81, cited in Hughes and Franks, 2004) identified the following purposes;
1
Immediate feedback
2
Development of a database
3
Indication of areas requiring improvement
4
Evaluation
5
As a mechanism for selective searching through a video recording of the game.
However, computerised notation systems have limitations. Hughes and Franks (2004)
identified these systems introduced problems for the operator. Operators may make an
error by entering incorrect data due to wrong keys being pressed. This error would most
likely happen in a real- time analysis so data from the performance would not be missed.
Another problem with computerised systems is errors could occur in hardware and
software that is used.
7
To overcome this problem video playback was introduced which enables operators to
notate after the event has taken place (Hughes and Franks, 2004). Post match analysis
allows accuracy when notating. The accuracy is down to the operators who can observe a
passage of play repeatedly to ensure the correct response has been made.
2.2 Notational analysis of Soccer
In soccer, notational analysis has been used in many ways which are listed below:

Penalty kicks

Movement analysis in soccer

Patterns of play.
Penalty kicks have had a limited amount of research in the notational area. However,
Hughes and Wells (2002) used a hand notation system to analyse 129 penalties. The
penalty taker and goalkeeper were analysed from the start of the phase, throughout the
phase and the outcome. This study produced accurate data and was analysed through a
database, which had Microsoft access. The study provided a clear data analysis. A clear
picture was produced of the most efficient ways of saving and taking a penalty, (Hughes
and Franks, 2004). Movement analysis has vast quantities of research in notational
analysis. Reilly and Thomas (1976) recorded and analysed the intensity and the degree of
discrete activities during the match. Reilly and Thomas (1976) is the definitive motion
analysis study using hand notation. The study used hand notation combined with a use of
a video tape to analysis the movement of players in detail.
In notational analysis, patterns of plays have seen the most research in this sporting
discipline. A pattern of play is an important factor in a game of soccer. Counter attacking
and possession in soccer is a successful way for creating opportunities and scoring goals.
Reep and Benjamin (1968) started the analysis in this area. The research data focused on
actions within a game such as passing and shooting rather than other match analysis such
as work rate and movements of individual players. Reep and Benjamin (1968) collected
3,213 matches in the English league and World Cup between the years of 1953 and 1968.
8
The author’s findings reported 80 per cent of goals came from a sequence of three passes
or fewer. Reep and Benjamin (1968) also identified fifty per cent of all the goals came
from possession gained in the final attacking quarter of the pitch.
Bate (1988) investigated the aspect of chance in soccer and how it related to tactics and
strategies. Bate (1988) furthered the investigation and compared his results with Reep and
Benjamin which were obtained in 1968. The study used all levels of international soccer.
Bate (1988) reported that 94 percent of goals scored were from sequence involving four
or fewer passes, and 50-60 per cent of all movements leading to shots on goal had started
in the attacking third of the field. The author suggested goals are not scored unless the
attacking team gets the ball and one or more attacking players enter into the attacking
third of the field. The author claimed the greater number of passes the team had, the
greater chance they have of progressing into the attacking third, which creates more
opportunities to score. Bate’s (1988) study reported the higher number of passes per
possession, the lower the total number of match possessions, the total number of entries
into the attacking third, and the total chance of shooting at goal. Bate (1988) concluded,
to increase the number of scoring opportunities a team should play the ball forward as
often as possible; reduce space and back passes to a minimum; increase the number of
long passes forward and forward runs with the ball; and play the ball into space as often
as possible. Hughes and Franks (2005) also accessed Reep and Benjamin (1968) findings
for validity and relevance. Hughes and Franks (2005) used all FIFA World cup matches
from the years of 1990 and 1994. The findings were approximately 80% of goals
occurred from possessions of 4 passes or less. The findings were very similar to Reep and
Benjamin (1986).
Different styles of play have been compared and analysed since Reep and Benjamin
(1968) in notational analysis. Pollard et al. (1988) investigated the quantitatively assess
determinants and consequences of various styles of play. Pollard et al. (1988) identified
that complex styles of plays relied on multi pass sequences of possession and direct styles
of play relied on long forward passes and long goal clearances. Furthermore, the authors
found that there was no relation between the degree of complex play and the use of width.
Pollard et al. (1988) concluded that it was important for the coach to build up a style
profile of each opponent for future analysis by using this type of assessment of playing
style. Ali (1988) used a hand notation system for analysis.
9
Ali (1988) developed a system to record 13 basic factors of a game. The system designed
attempted to establish if there were specific and identifiable patterns of attack and how
successful each pattern impacted the result of the match. The findings stated that
attacking patterns that advance along the wing were more successful than those through
the centre of the field. Furthermore, plays that involve a great number of passes increased
the likelihood of a goal.
Patterns of play in soccer have had many important studies which are linked to this
investigation. To conclude, Reep and Benjamin (1968) produced a significant research
paper in this area, suggesting that 80% of goals are scored from a build up of 3 passes or
less. While Bate (1988) reported 94 percent of goals scored were from sequence
involving four or fewer passes. Hughes and Franks (2005) also found there were
approximately 80% of goals occurring from possessions of 4 passes or less.
2.3 Attacking profiles and tactics in soccer
Many studies in Performance Analysis have investigated possession, offensive tactics and
patterns in soccer. Hewer and James (2004) investigated the goals scoring strategies of a
top premiership team in European and British competitions. The aim of the study was to
extend the work of James et al. (2002) by examining the goals scored by one team over
four seasons. It was felt that if different attacking moves were employed to overcome the
different defensive strategies between competitions then the way in which goals were
scored would reflect that. From the findings of the research, a case has been made that
European and British teams employ different strategies, which is probably based on
relative strengths and weaknesses between them. It was found that the analysed team
played more passes to attacking players in pre offensive areas. Small differences were
seen in the direction of attack with the two thirds of crossing assists played from the right
in European matches compared to a balanced profile in British matches. This may
indicate real attacking strategy differences, although it is equally possible that defensive
strategies may force these choices on attacking teams.
10
Yiannakos and Armatas (2006) study evaluated goal scoring patterns. This is important to
coaches because it shows when, where and why goals are being conceded. Yiannakos and
Armatas (2006) examined the Evaluation of the goal scoring patterns in European
Championship in Portugal 2004. The aim of the study was to record and evaluate the
characteristics of goal scoring patterns in the competition. The findings of the studies
reveal that coaches should focus on dead- ball situations. The study also found attention
must be given to the fatigue of players towards the end of a game, which consequently
leads to goal scoring by the opposing team, and to its confrontation through training.
Konstadinidou and Tsigilis (2005) examined offensive playing profiles of football teams
from the 1999 Women’s World Cup Finals. The aim of the study was to examine the
profiles of offensive tactics of four teams in the competition. The results showed that the
four teams had different offensive profiles. The result found were comparable with Olsen
and Larsen (1997) study regarding the Norwegian national women’s team and provides
additional support for the style of offence play used. Linking to Konstadinidou and
Tsigilis (2005) study, Olsen and Larsen (1997) analysed the offensive game for both the
men and womens Norwegian national football team. Their findings showed the
Norwegians offensive tactic was characterised by long passes from the defence area to
start attacks. This study only showed the offensive game for one nationality over a four
year period.
Brown and Hughes (2004) investigated the attacking patterns in offensive areas of
European, South American, African and Asian teams in the 2002 Soccer World Cup. The
study was aimed to provide an objective and quantitative analysis of attacking playing
patterns in offensive areas of four different global continents. This study also tried to
address problems linked with research methodologies. The results identified that each
continent appeared to have its own playing pattern in offensive areas. The profiles of each
continent were somewhat generalised, which could enable defensive strategies to work
against them. This study has addressed the attacking patterns of four continents. Further
research on attacking patterns of just one continent could be assessed. This would develop
normative profiles of a continent on a general scale. If this occurred, results would
become more valid due to comparisons between continents improving.
11
Fleig and Hughes (2004) examined counter attacks in the 2002 Soccer World Cup. The
aim of the study was to carry out detailed analysis of counter attacking play during the
competition. The study found that successful counter- attacking play relied on accurate
passing within defensive and midfield thirds, making use of width and skills on the ball
played towards the attacking third. It was found that counter attacks were used by lower
ranked teams, even though success was dependant upon individual ability levels rather
than overall performance.
2.4 Possession and its determinants
Research on Possession and its determinants has been limited. However Jones, et al.
(2004) investigated possession as a performance indicator in soccer. The study aimed to
compare the duration of possession of successful and unsuccessful teams in the premier
league. A relevant method of analysis was developed and balanced for evolving match
status as a potential independent variable, Venue, strength of opposition and the number
of matches played. Twenty four matches which consisted of six teams from the 2001-02
English Premier League. The top three teams were selected for successful and the bottom
three teams for unsuccessful. Operational definitions were agreed by observers which
made each entry more consistent for each possession. Jones, et al. (2004) agreed
possession started when a player on the analysed team had sufficient control over the ball
to enable a deliberate influence on its direction. Possession continued until the ball either
went out of play, an opposing player touched the ball or the referee blew the whistle for
an infringement. Jones, et al. (2004) findings showed that the successful teams had
significantly longer possessions than unsuccessful teams, regardless of the match status.
The authors also found that durations of possession were longer when teams were losing
irrespective of a successful team or an unsuccessful one. Jones, et al. (2004) concluded
that successful performance is related to elite English football possession, but it is likely
to relate in individual player’s skill levels rather than specific team strategy. Lago and
Martin (2007) also investigated possession and it determinants. The authors used data 170
matches from the 2003-2004 Spanish Soccer league. Lago and Martin (2007) aimed to
explain why the difference in the possession of the ball among teams was so great. They
examined four particular variables: evolving match status (i.e. weather the team were
winning, losing or drawing), venue (i.e. playing at home or away) and the identities of the
team and the opponent in each match.
12
The analysis showed that the four variables were statistically significant and together
explained some of the variance in possession. The results identified home teams had more
possession than away teams; teams had more possession when they were losing in a
match compared to winning and drawing, and the worse the opponent, the greater the
possession of the ball. Lago and Martin (2007) concluded that the combinations of these
variables could be used to predict possession in soccer. However, Taylor, et al. (2008)
approach was slightly different. The authors investigated the influence of match location,
quality of opposition, and match status on technical performance in a single professional
British football team. Forty matches were notated post event using a computerised
notation analysis system over two seasons in the team’s domestic league. The authors
assessed 13 on-the-ball behaviours and resultant outcomes (successful or unsuccessful).
All on-the-ball technical behaviours, except set-pieces were influenced by at least one
situation variable, with both independent and interactive effects found. The authors also
found there was no general influence of the situation variables on the outcomes of the onthe-ball behaviours. From the findings, Taylor, et al. (2008) suggested there is a need for
notational analysts and for coaches to think about the effects of match location, quality of
opposition, and match status when assessing the technical components of football
performance. The authors also suggested future research which should consider the
effects of an additional situation.
2.5 Effects of match status on possession
Studies focusing on the effects of match status on possession have been limited.
However, Bloomfield, et al. (2005) investigated the difference in team strategies of 3 FA
Premier League clubs (Manchester United, Chelsea and Arsenal) at different score lines
by analysing match possession and zones of play. The authors observed 22 performances.
The analysis showed that all three teams dominated possession over their opponents in all
score-line states. However Manchester United and Chelsea retained more possession than
Arsenal and Chelsea kept the ball most when scores were level. Manchester United kept
the ball most when ahead and behind. The authors suggested Manchester United and
Arsenal prefer to control the game by dictating play when in possession whether they are
ahead or behind.
13
Bloomfield, et al. (2005) suggested that findings indicate that strategies are influenced by
score-line and teams change their playing style during the game. The authors concluded
that different teams appear to employ different strategies when ahead, level or behind, but
it depends on the coaching, management, players and resources at a certain club.
2.6 Effects of Game location in soccer
Throughout the years in sport, studies have indicated playing at your home location is an
advantage. Tucker, et al. (2005) investigated the game location effects in professional
soccer. Thirty matches of the top five sides from the Premiership league were analysed in
the season of 2004-2005. The matches were notated via a computerised system post
event. The authors used non-parametric analysis which compared the function of game
locations. The findings showed overall home advantage was found for the analysis which
related to home-wins and home-goal percentage. Technical performance showed there
were more successful behaviours at home rather than away. For tactics-related
behaviours, such as shots on goals, were performed at home in the attacking third.
Tucker, et al. (2005) concluded the findings suggest that game location effects may exist
at a strategic level within individual teams. The authors suggested future research should
be considered. The research that could be considered is the influence of other
confounding variables; these variables could include team form, game status and
opposition quality. Sasaki et al. (1999) and Pollard (1986) also completed research on
home advantage in soccer. Sasaki et al. (1999) assessed 26 Ipswich Town matches and
explored the player’s perceptions of home advantage during the games. A hand notation
system was used to record data in the game, while a 30 item questionnaire was used
which assessed the players critical psychological states and players thoughts on home
advantage. Sasaki et al. (1999) findings suggested performance outcomes such as goal
attempts and shots on targets favoured the team when they were playing at home.
However, players had a greater expectation to win more at home than away. Pollard
(1986) investigated home advantage in soccer in general. The author suggested soccer has
achieved the greatest advantage of home location than any other professional team sports
in England. Pollard (1986) statistical evidence suggested crowd support and travel fatigue
have a say less to home advantage in soccer than do the less benefits of familiarity with
conditions when playing a home match.
14
2.7 Effects of opposition strength on attacking profiles
Opposition strength within a league setting has been limited in research in soccer.
However, investigations into “successful” and “unsuccessful” during competitions has
been researched. Grant et al. (1999) investigated the difference between successful and
unsuccessful teams in the 1998 soccer World Cup. Successful teams were the teams that
reached the semi finals, while unsuccessful teams were deemed as those that failed to
progress to the second round. Analysis on several aspects of match play was conducted
on 30 matches. Grant et al. (1999) findings produced a number of outcomes. The
successful teams averaged more attempts at goal and performed more passes per game.
Successful teams penetrated the defence by passing, running and dribbling the ball
forward for longer sequences of play then the successful teams. Finally, successful teams
produced more attempts at goal in open play with build ups of four passes or more. This
indicated successful teams in the 1998 World Cup had an ability to create chances while
maintaining possession. Hughes and Churchill (2005) investigated attacking profiles of
successful and unsuccessful teams in 2001 soccer Copa America. The authors aimed to
compare the patterns of play of successful and unsuccessful teams leading to shots and
goals during the tournament. Matches analysed involved 19 successful teams and 11
unsuccessful. The team’s performances were compared using performance indicators
from 10 variables. Hughes and Churchill (2005) results showed there were no significant
differences between successful and unsuccessful team’s patterns of play leading to shots.
However, successful teams used effective styles of play to a greater degree. Hughes and
Churchill (2005) suggested the shorter the duration and the less number of passes in a
possession, the more likely a shot will occur, and the better is the chance of scoring. Hook
and Hughes (2001) investigated patterns of play leading to shots in 2000 soccer European
championship. The authors aimed to analyse all shots and possessions leading to those
shots, for successful and unsuccessful teams in the championship. The semi finalists in
the championship were deemed as successful teams and the eight teams that did not
progress into the quarter finals were deemed unsuccessful. Hook and Hughes (2001)
findings showed successful teams kept the ball for longer duration’s of play. They were
able to move the ball up the pitch to create a shot from their defensive half more
effectively than unsuccessful teams. The authors concluded that unsuccessful teams were
predictable in attacks and did not score as many goals due to longer range shots.
15
However, Scoulding et al. (2004) aimed to provide a detailed insight into passing. Post
event analysis was performed on 6 group matches (3 each for a successful and an
unsuccessful team) in the 2002 soccer World Cup. A computerised notational analysis
software package (Noldus Observer Video-Pro) was used and data produced was
transferred to SPSS for statistical analysis. Scoulding et al. (2004) findings suggested that
there was no difference between passing strategy and passing ability between the
successful and unsuccessful teams. Scoulding et al. (2004) concluded the factors used
were not sensitive enough to analyse the differences in passing. Other factors can
determine match outcomes and the teams used were too much of the similar standard.
16
CHAPTER III
METHODOLOGY
3.0 Methodology
3.1 Introduction
A hand notation system was created to record the number of passes in a possession, the
outcome of the possession and match status. The hand notation system was developed and
improved through the use of pilot studies.
3.2 Subjects
One English soccer league team that competed in the 2008/2009 English Football
Championship domestic league was analysed in the study. The team’s opponents were
chosen randomly and also competed in the same domestic league. Eight matches were
recorded live by Swansea City FC and copied onto DVD’s.
English Championship matches:
1. Swansea City verses Queens Park Rangers
(21st October 2008)
2. Wolverhampton Wanderers verses Swansea City
(28th October 2008)
3. Swansea City verses Cardiff City
(30th November 2008)
4. Burnley FC verses Swansea City
( 10th January 20090)
5. Swansea City verses Ipswich Town
(7th February 2009)
6. Swansea City verses Doncaster Rovers
(21st February 2009)
7. Swansea City verses Charlton Athletic
(28th February 2009)
8. Cardiff City verses Swansea City
(5th April 2009)
17
3.3 Equipment
The equipment used for the recording, coding and presenting the data is listed as follows;

Black pen

Pencil

Phillips Video camcorder

Phillips DVD player and recorder

9 Sony DVD-R containing match footage

Sony colour television

Gateway Laptop

Printed Hand notation system on A4 paper – See Appendix (?)

Microsoft Office 2007

SPSS
3.4 Pilot Study
Two pilot studies took place before the initial hand notation system was produced. The
first study was carried out between Liverpool and Lyon during the Champions League
group stage of 2009/2010 season. The system produced coded material of every
possession during the game of the team being analysed. Each possession was put into a
successful or unsuccessful category, with the number of passes in that possession. A
successful possession was deemed to be a goal. A snapshot of the system is shown in
table 1.
18
Table 1. Snapshot of the First Pilot notation sheet.
Unsuccessful possession
0-1
2-3
4-5
Successful possession
5+
passes passes passes passes
lll
llll
lll
0-1
2-3
4-5
5+
passes passes passes passes
l
l
The hand notation system used in the first pilot study, did not meet the needs of the
investigation. The system did not produce data that could be analysed. The raw data only
showed how many passes had occurred in each possession and if it was successful or
unsuccessful. However the notation table did not account for other variables that were
being investigated.
The second pilot study was carried out between Swansea City and Reading FC; both
teams were in the English Championship league. The notation system used in this second
study was similar to the final system. The strengths of the system were its simplistic
procedure for the input of data, it met the needs of what the study was investigating and it
could also be used for other studies. The system recorded each possession, which includes
the number of passes in the possession, match status, shot and a goal scored as shown in
table 2.
19
Table 2. An example of the second notation system
Number of passes in Match status
Goal
Shot
possession
3
0
0
0
0
0
0
1
10
0
0
0
6
0
0
0
4
0
1
0
3
1
0
0
0
1
0
0
2
1
0
0
0
1
0
1
The second pilot study was successful. However, some further adjustments were needed
to improve the system and make the system more simplistic.
3.5 The final system
The final notational system was developed to overcome the problems found in the pilot
studies. The notation system was created in Microsoft Excel on A4 white paper. The
system produced was in a table format with 3 columns, which was a clearer way for
transferring data for analysis. An example of the final notation system is in Appendix 1.
The hand notation systems column headings and system abbreviations are illustrated in
table 3 and listed below respectively.
20
Table 3. An example of the final notation system
Column 1
Number
of
passes
in
a Column 2
Column 3
possession
Outcome
Match Status
6
0
0
7
1
0
1
2
0
2
0
1
2
0
2
Column1: Number of passes in a possession, Which Start from 0 +
Column 2: Outcome of the possession
0
Other
1
Shot
2
Goal
Column 3: Match Status
0
Drawing
1
Winning
2
Losing
21
3.6 Operational Definitions
The operational definitions were defined after the final notational system was developed.
The definitions were as accurate as possible before the operator started observing. This
enabled the operator to ensure reliability of the data being coded.
Possession was deemed to start when a player on the analysed team had sufficient control
of the ball to enable a deliberate influence on its direction. Possession continued until the
ball either went out of play, an opposing player touched the ball or the referee blew the
whistle for an infringement. (Jones et al., 2004)
A pass was deemed to a player kicking, heading or throwing the ball to his teammate. A
pass to the opponent or` ball out of play would end possession
A shot was deemed to happen when a ball was kicked or headed by a player towards the
opponents net in an attempt to score a goal. A shot would end possession unless the ball
touched or was controlled by a team mate
A goal was deemed to happen when the ball had passed totally over the goal line between
the posts and under the crossbar. The referee’s whistle and hand point towards the centre
circle will also indicate a goal. After the goal was scored, the team that conceded the goal
would kick off from centre circle to restart the game. A goal would end the possession of
the team that scored it.
3.7 Data collection procedure
All matches were recorded by Swansea City Football club onto individual DVD’s and
played back for observing and analysing via a laptop computer. Prior to data collection,
the hand notation sheet was filled in, naming opponents, date of match, venue, opponent’s
league position and full time score. As a game started, every time Swansea City were in
possession each pass was counted until the possession ended. Once the possession ended,
the notation table would then been filled in. Firstly, the number of passes in possession,
22
then the outcome of the possession and finally match status. As the game progressed, the
observer worked through each column when possession ended. The DVD was paused and
rewound to review any passes or possession that was doubtful. Once the game was
finished, the columns statistics were totalled. This procedure was completed for each
match observed.
3.8 Reliability
A reliability study was performed in order to examine the validity of the hand notation
analysis system. It is important that the observer’s analysis was consistent when repeating
the analysis on the same material. An intra-reliability study was performed on the first
forty five minutes of Swansea’s City FC match against Ipswich Town. The first forty five
minutes were notated twice, with a 2 week period between the observations. Hughes’
percentage error was calculated to analyse the reliability. The number of passes in a
possession, the number of shots and the number of goals scored was compared to give a
clear image of the reliability.
3.9 Data processing and analysis
Once the observed match was over, all raw data was inputted into Microsoft Excel.
However the data analysis process was conducted in SPSS (SPSS 17.0, SPSS Inc,
Chicago, Illinois). Data was analysed in SPSS using Kruskal-Wallis test and a MannWhitney test to determine significant differences between the number of passes in
possession and various variables. In SPSS, the variables were also explored which
produced statistical data which were compared.
23
CHAPTER IV
RESULTS
4.0 Results
4.1 Introduction
The result section for this study has been divided into specific areas looking at different
variables. The results will show if there was a significant difference between variables
and possession length.
To determine whether a significant difference (P < 0.05) or (P < 0.01), tests were carried
out in SPSS. The results provide clear information and feedback to coaches and
individuals.
4.2 Reliability
Variables were tested for intra- observer reliability. The outcomes are shown in table 4.
Reliability was set at a mark of 5%. A percentage over 5% was classed as unreliable.
Table 4. Intra-observer reliability
Swansea City vs. Ipswich Town (1st Half)
Variable
V1
V2
Number of passes in the half
407
407
Number of possessions in the half
147
147
Number of shots
18
18
Number of goals scored
2
2
Number of passes in the half Percentage Error statistic
= ((abs[V1-V2]) / Vmean)*100
= (0/407) x 100
= 0 % error
24
Number of possessions in the half Percentage Error statistic
= ((abs[V1-V2]) / Vmean) *100
= (0/147) x 100
= 0% error
Number of shots Percentage Error statistic
= ((abs[V1-V2]) / Vmean)*100
= (0/18) x 100
= 0 % error
Number of goals scored Percentage Error statistic
= ((abs[V1-V2]) / Vmean) *100
= 0 % error
 = sum of; abs = absolute value; V1 = observation 1; V2 = observation 2; Vmean =
mean of both view.
The percentage error statistic for all the variables was calculated as 0%, which meant
reliability levels were acceptable and the intra - observer viewings of the performance
were reliable.
4.3 Match status
The Kruskal-Wallis test (df = 2, P<0.05) showed a significant difference on the number of
passes in a possession dependant on the match status. Swansea City recorded higher
25
number of passes per possession when they were losing during matches. The mean and
medium over the data set is shown in figure 1 and table 5.
Table 5. Mean and medium over the data set dependant on match status
Drawing
Mean number of passes in a possession 2.67
Winning
Losing
2.46
3
2
3
Medium number of passes in a
possession
2
Figure 1. Mean and medium over the data set dependant on match status
4.4 Match location
The Mann-Whitney test (P<0.05) showed a significant difference on the number of passes
in a possession dependant on the location of the match. Swansea City recorded a higher
number of passes per possession when they were playing away. The mean and medium
over the data set is shown in figure2 and table 6.
26
Table 6. Mean and medium over the data set dependant on match location
Home
Away
Mean number of passes in a possession
2.45
2.81
Medium number of passes in a possession
2
2
Figure 2. Mean and medium over the data set dependant on match location
4.5 League position
The Mann-Whitney test (P<0.01) showed a significant difference on the number of passes
in possession dependant on the position of the opponents in the league table. Swansea
City recorded higher number of passes per possession when playing teams in a higher
league position. The mean and medium over the data set is shown in figure 3 and table 7
Table 7. Mean and medium over the data set dependant on opponents
Higher
Lower
Mean number of passes in a possession
2.80
2.34
Medium number of passes in a possession
2
2
27
Figure 3. Mean and medium over the data set dependant on opponents
4.6 Match half
The Mann-Whitney test (P>0.05) showed no significant differences were found between
the number of passes in possession in both halves of the match Swansea City were
playing. The mean and medium is shown in figure 4 and table 8.
Table 8. Mean and medium over the data set dependant on halve
First
Second
Mean number of passes in a possession
2.55
2.71
Medium number of passes in a possession
2
2
28
Figure 4. Mean and medium over the data set dependant on halve
4.7 Goals
The number of passes in the possession that created a goal was analysed. Figure 5 and
table 9 shows the frequency of goals and the the number of passes in the possession that
created them.
Table 9. Frequency of goals dependent on possession length
Number of passes in a
possession
Frequency
0
3
1
2
2
2
3
2
4
3
5
0
6
0
7
0
8
1
>=9
1
29
Figure 5. Frequency of goals dependent on possession length
4.8 Shots
The number of passes in the possession that created a shot was analysed. Figure 6 and
table 10 shows the frequency of shots and the number of passes in the possession that
created them.
Table 10. Frequency of shots dependent on possession length
Number
of
passes
in
possession
Frequency
0
33
1
20
2
18
3
20
4
10
5
8
6
5
7
5
8
0
>=9
15
30
Figure 6. Frequency of shots dependent on possession length
31
CHAPTER V
DISCUSSION
5.0 Discussion
It was set out within this study to explore possession as a concept within Soccer and to
identify key aspects which contribute to possession in Soccer. The data produced from the
analysis proved to be encouraging and has displayed an insight into possession and its
determinants. Previous studies have viewed possession as a determinant of soccer success
but research on possession of the ball has limited amount of literature available when
paying attention to its determinants.
There was a significant difference (P<0.05) on the number of passes in a possession
dependant on the match status (winning, losing drawing). Swansea City retained higher
possession sequences when they were losing during the matches. This evidence supports
hypothesis 1 which stated “The team will have higher possession sequences when losing
in a match situation”. Swansea City kept possession more efficient when they were
losing rather than winning or drawing. When winning, the team had the lowest mean
number of passes in a possession (2.46) followed by drawing (2.67). The results found
are similar to the findings of James et al. (2004) and Lago and Martin (2007). These
studies reported teams having greater possession when losing rather than when they are
winning. Furthermore, Bloomfield et al. (2005) study supported the finding; the authors
reported possession is influenced by the score. Bloomfield et al. (2005) suggested that
different teams appear to employ different strategies when ahead, level or behind, but it
depends on the coaching, management, players and resources at a certain club. Swansea
City employed different tactics when they were in a losing in a match. They kept the ball
for longer trying to retain possession to create opportunities to score goals and turn the
game into a drawing situation. This shows possession is affected by the score, but
different teams appear to follow different tactics (retaining more or less possession) in a
game. However, previous researches have suggested that “direct style” of play equals
success in scoring goals.
Match location showed a significant differences (P<0.05) on the number of passes in a
possession. The mean results showed Swansea City had higher number of passes in a
possession when playing away (2.81) rather than at home (2.45). The findings did not
32
support hypothesis 2 which stated “The team will have higher possession sequences when
playing at home rather than away”. Swansea City showed they could retain possession
more away from home. This could suggest Swansea City were more attacking at home
and losing possession of the ball, rather than keeping possession and waiting for the right
opportunity to create an attack. Previous research does not support this finding from the
study. Pollard (1986), Thomas et al. (2004) and Lago and Martin (2007) found when
teams played a home match they held possession for longer spells, compared to playing
away. However, the studies stated that depending on match location, a team would play
different formations and strategies to improve performance. This suggests Swansea city
employed a different strategy away from home, trying to keep possession and not trying
to play direct football to create chances to score goals.
The position of opponents in the league table showed a significant difference (P<0.01) on
the number of passes in possession. Swansea City recorded a higher mean number of
passes in a possession when playing opponents that were higher (2.80) in the league than
opponents lower (2.34) in the league. The findings did not support hypothesis 4 which
stated “The team will have higher possession sequences when playing opposition lower in
the table”. Previous literature in opposition strength is limited. Lago and Martin (2007)
identified differences in possession depending on the identities of the team and the
opponent. The limitation to the identification is that the study did not consider the reasons
for this observation. Lago and Martin (2007) suggested it was likely style of play is the
reason for teams’ differences in possession. Except for Lago and Martin (2007) study the
quality of opponent has been ignored, however teams have been regarded as “successful”
or “unsuccessful” based on their effectiveness in a particular tournament( e.g. Hook and
Hughes 2001). Scoulding et al. (2004) identified a problem when looking at “successful”
or “unsuccessful teams. The author suggested; teams may be high quality but are deemed
to be unsuccessful due to them not progressing through a certain tournament. The
difference found in this study stated that Swansea city kept the ball longer when playing
opponents higher in the league. This could suggest that tactics and styles of play against
higher teams could result in this difference in possession. Keeping possession of the ball
means the opponents can not score and there is more chance of creating opportunities of
creating chances and scoring.
33
Swansea City showed no significant difference (>0.05) between halves and the number of
passes in the possession. This suggests that patterns of play were not altered throughout
the game. The same tactics and strategies that was in place for the first half was carried
out also throughout the second half. Hypothesis 5 stated the team will have higher
possession sequences in the first 45 minutes of play (first half). The findings did not
support the hypothesis. There has not been any research on this variable in notational
analysis literature in soccer to support the results.
The number of passes in a possession that leads to a goal has been widely researched in
soccer literature. Due to the number of games viewed during analysis, there was not
enough data to see the difference between the numbers of passes in a possession when
scoring a goal. However studies such as Grant et al. (1999) and Hook and Hughes (2001)
have agreed with Bate (1988) findings which found that moving the ball forward quickly
creates more opportunities of scoring goals and creating chances. However, not being
able to analyse possession length that ended with a goal, can not be compared with other
studies. Also it does not give support towards Hypothesis 3 which stated “The team will
have a shorter number of passes (four and under) leading to a goal”. Previous literature in
this area can support hypothesis 3. Reep and Benjamin (1968) identified 80% of goals are
scored from a build up of 3 passes or less. While Bate (1988) reported 94 percent of goals
scored were from sequence involving four or fewer passes. Hughes and franks (2005) also
found there were approximately 80% of goals occurring from possessions of 4 passes or
less. Figure 5 shows the frequency of goals scored with the number of passes in the
possession that created the actually goal scoring opportunity. The results are shown in a
graph which makes it clear to the coach how many passes were played before the goal
was scored. The findings can be worked on in training to apply tactics for a game
situation. If a team is scoring more goals from “direct” style possession, coaches can
work on this play in training and utilise this tactics to make it more beneficial for scoring
a goal.
34
5.1 Limitations of study
The first limitation of the study was the number of games that were analysed. Eight
games did not produce enough data, so the number of passes in possession could not be
analysed with goals scored and shots at goal. This was due to video availability at the
time of when the analysis was taking place and the time scale for the analysis to be
completed. More time was needed to collect the data necessary which would have given
more time for more available videos. If more games were analysed many more goals and
shots would have been analysed leaving more data to be compared in the results The
second limitation was the number of teams analysed. Swansea City was the only team
analysed during the study. Swansea City could not be compared to other teams in the
division for similar trends of possession; this was due to the duration of the study. On a
longer time scale more teams could be analysed due to matches available on DVD from
championship clubs and Sky Sports covering more championship games throughout the
season. The final limitation of the study is previous literature in possession and its
determinants were limited. The results produced of some variables could not be compared
and backed up with other research. However, the results produced can further soccer
literature for possession and its determinants.
35
CHAPTER VI
CONCLUSION
6.0 Conclusion
The study served to investigate possession length in soccer by determining the differences
or similarities within the data, depending on the outcome, match status, match location,
opposition strength and possession in each half. By adapted previous research within the
field of possession and its determinants, this study created several promising results.
However, some results produced different outcomes that do not agree with previous
research. The results that agreed with previous research are reported here as follows.
Firstly, Swansea City’s possession lengths depended on the evolving match status
(Drawing, Winning, and Losing). Swansea City had greater number of passes in a
possession when they were losing rather than when they were winning or drawing. The
evidence produced supported hypothesis 1 in the study and also agreed with previous
literature which identified teams retained possession longer when they were in a losing
stage of the match. This suggests possession is affected by the score, but different team
employ different tactics (retaining more or less possession) in a match situation.
Secondly, Swansea City’s possession lengths depended on the opposition strength
(Higher or lower in the league table). Swansea City had a greater number of passes in a
possession when they were playing a team higher in the league. The evidence produced
did not support hypothesis 4. Previous research in opposition strength identified
differences in possession depending on the identities of the team and the opponent.
However there has not been any exclusive research on opposition strength within a league
setting, only in “successful” and “unsuccessful” teams in certain competitions. The result
that disagreed with previous research is match location in relation with possession length.
Swansea City had greater number of passes in a possession when they were playing away
rather than at home. The evidence produced did not support hypothesis 2. Previous
research identified teams retained possession longer when they were playing at home
rather than away. Another variable that was tested with possession length was each half
of the game. There had been no literature produced in this area. However, there was no
significant difference between possession lengths in each half. The outcome of possession
was looked at throughout the analysis. Each possession that ended with a shot or a goal
was recorded. However, due to the lack of data collected there was not a significant
difference between possession length and a goal or a shot. Plenty of soccer research in
possession lengths and outcomes has been published.
36
The findings of the study have highlighted a number of variables that could explain
possession lengths in soccer. This suggests possession should be looked at from all angles
and not only be investigated with how goals are scored. A combination of these variables
could predict possession lengths and outcomes in soccer
6.1 Recommendations for further research
As this research investigated possession and its determinants there are many options in
which further research can go down. Some aspects of the study which warrant further
research are recommended below:
1. To analysis a team or a number of teams over a greater period of time to see the
trends and difference in possession length and its determinants.
2. To analysis teams from different leagues to get a wider data set on possession
within the world of soccer. Different leagues could be analysed for styles of
successful possessions. Other variables such as Location, opponents strength and
match status could be integrated into the study.
3. To analyse possession in lower leagues of soccer and comparing it to the higher
leagues. This can indicate a difference in higher standard football compared to
lower and also what style f possession works best at a lower league level.
4. To analyse opposition strength rather than teams deemed as “successful” or
“unsuccessful” when looking at possession lengths.
37
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APPENDICES
Appendix A