JAMES TURNER
ST07002605
SCHOOL OF SPORT
UWIC
THE IMPACT OF SCORE-LINE ON THE USE OF
POSSESSION IN SOCCER
Table of Contents
1.0 CHAPTER ONE – INTRODUCTION
Page Number
1.1 Soccer
1
1.2 Statement of problem
2
1.3 Aim of the study
2
1.4 Limitations
2
1.5 Delimitations
3
1.6 Hypotheses
3
2.0 CHAPTER TWO – LITERATURE REVIEW
2.1 Introduction
4
2.2 Match Analysis of Football
4
2.3 Score-line
5
2.4 Tactical Analysis
9
2.5 Possession
11
2.6 Justification for study
12
3.0 CHAPTER THREE - METHODOLOGY
3.1 Participants
14
3.2 Instrumentation/Equipment
14
3.3 System
14
3.4 Procedure
15
3.5 Data Analysis
19
3.6 Reliability
20
3.7 Ethical Issues
21
4.0 CHAPTER FOUR - RESULTS
4.1 Descriptive statistics
22
4.2 Locations where possessions begin
23
4.3 Locations where possessions end
25
4.4 Methods used to start possessions
27
4.5 Methods used to end possessions
30
4.6 Passes
32
4.7 Players
33
5.0 CHAPTER FIVE - DISCUSSION
5.1 Introduction
34
5.2 Reliability
34
5.3 General possession characteristics
35
5.4 Differences in possession when behind compared to level
38
5.5 Differences in possession when ahead compared to level
41
6.0 CHAPTER SIX - CONCLUSIONS
6.1 Conclusions
43
6.2 Future Directions
44
REFERENCES
45
List of Tables
Page Number
Table 1 – An example of the system used in the data
16
collection process taken from the pilot study.
Table 2 – Kappa values for each variable observed
22
in the reliability study.
Table 3 – Descriptive statistics of basic variables used
23
in data collection.
Table 4 – Methods of ending possessions when behind,
level and ahead.
31
List of Figures
Page Number
Figure 1 – Example of the pitch diagram used to assess
15
where possessions begin and end.
Figure 2- Location of where possessions start, as a
24
percentage of total possessions per score-line state.
Figure 3- Area on the pitch where possessions end,
26
as a percentage of total possessions per score-line state.
Figure 4 - Methods of starting possessions when behind.
27
Figure 5 - Methods of starting possessions when level.
28
Figure 6 - Methods of starting possessions when ahead.
29
Figure 7 – The number of passes per possession as a
32
percentage when behind, level and ahead.
Figure 8 –The number of players per possession as a
percentage when behind, level and ahead.
33
Acknowledgements
I would like to thank Peter O’Donoghue for all his help throughout this study, his
guidance and knowledge has helped considerably. I would also like to thank Sam
Dent for supplying matches used in the data collection.
i
Abstract
The issue of score-line effects on possession in soccer has been examined in very
little detail in the literature (Redwood-Brown, 2008; Jones et al., 2004; Lago &Martin
2007; Bloomfield et al., 2004a). The studies have shown mixed results involving the
differences seen when behind, level and ahead. The current study aimed to examine
possession effects including locations and methods used to start and end
possessions, the number of players and number of passes in each sequence. Ten
Premier League matches were examined from the 2009/2010 season with a Kappa
inter reliability undertaken resulting in good levels of agreement (>0.70) for all
variables analysed (Altman, 1991). Chi squared tests of significance were carried
out to determine differences between the score-line states and there was found to
be no significant differences between the number of passes per possession and the
number of players (p>0.05). Significant differences were seen for the methods in
which possessions started and the locations of where possessions started and
ended (p<0.05). When behind a greater number of passing sequences started on
the wings, ending in the centre. In comparison, when teams were ahead a greater
number of possessions started in the centre and ended on the wings with very little
variation seen when level. The differences observed were suggested to be because
of the desperation of teams when behind and their need to get balls into the box,
creating chances to score goals and get back into the game.
ii
CHAPTER I
INTRODUCTION
1.0 Introduction
1.1 Soccer
Soccer is the most popular sport in the world, played and observed by millions of
people across the globe. The popularity of the game is massive especially in
England where there are 92 teams in the 4 tiered football leagues, with the best 20
teams in the elite level Premier League. The league is considered to be one of the
best in the world attracting the greatest players and managers. The strength of the
league can be justified as the last two UEFA Champions League finals (a knock out
competition for the best club teams in Europe) have involved three English teams,
with the competition being regarded as the finest club soccer competition in the
world. As the technical and physical abilities of the players improve, teams are
constantly looking at new ways to try and improve and develop. One of these
methods is through using notational analysis, which is an objective way of recording
performance (Hughes, 2004) so that the results can be fed back to coaches for
improvement in future matches.
The use of performance analysis in football has become more prevalent to help
teams
identify
opposition
weaknesses
and
improve
on
individual
team
performances. One of the earliest pieces of performance analysis research in soccer
was undertaken by Reep and Benjamin (1968) and provided detailed information
which has been used in the world of soccer for over forty years. The authors
identified that 80% of goals resulted from possessions starting from passing
sequences of 3 passes or less. This has influenced the playing style of English
soccer teams for many years with the teams being known for their direct style of
play, getting many balls into the box to finish off possessions as quickly as possible
(Bangsbo & Peitersen, 2000).
1
1.2 Statement of Problem
There has been quite a lot of research undertaken to examine possession in soccer
(Hook & Hughes, 2001; Bate, 1988; Hughes & Franks, 2005; Stanhope 2001), but
very little concerning the different methods in which teams play in varying score-line
states. Some research has examined goal effects in 5 minute segments (RedwoodBrown, 2008), others have examined the time in possession of the ball (Lago &
Martin, 2007; Jones et al., 2004). There has not been any research comparing the
impact of different score-line states; behind, level and ahead and how this impacts
upon the use of possession for soccer teams, which the current study addresses.
1.3 Aim of the study
The aim of the study was to examine the effect of different score-line states on the
use of possession in elite level soccer. Matches will be analysed to compare the
differences between the use of possession when teams are behind, level and ahead.
The possession characteristics will include the locations and methods used to
assess where possessions start and end, the number of players and the number of
passes in each passing sequence.
1.4 Limitations
1. The time available to complete the study (12 months), resources available
and the word count allocation (10,000 words).
2. The footage was taken from Sky Television and therefore the quality of
footage when transferred to DVD was sometimes not very good.
3. The use of action replays by Sky Television cameras although beneficial to
the viewer, resulted in the starts of some possessions being missed.
2
1.5 Delimitations
1. The influence of external factors such as temperature, time of day and pitch
surface which were not accounted for in the study.
2. The study was undertaken on elite level (Premier League standard) players
and therefore cannot be applied to lower levels of soccer.
3. The study was undertaken on domestic (Premier League) soccer and
therefore should not be applied to international soccer where standard of play
or tournament length and structure may be different.
1.6 Hypotheses
Null Hypothesis: There will be no significant differences between locations and
methods of starting and ending possessions, number of passes and number of
players between different score-line states.
Alternative Hypothesis: There will be significant differences between locations and
methods of starting and ending possessions, number of passes and number of
players between different score-line states.
3
CHAPTER II
LITERATURE REVIEW
2.0 Literature Review
2.1 Introduction
The study examined the impact of score-line on passing sequences in soccer. This
literature review will consist of four main subject areas; a) match analysis of football,
b) score-line, c) tactical analysis and d) possession. Score-line was considered from
all sports due to the lack of literature in the area which was soccer specific. All
literature was considered to assess the impact of score-line on other variables, not
just possession. Tactical analysis of soccer will then be reviewed to show the
different methods teams or individual players use and if score line does, or can have
a realistic effect on performance. Finally, soccer specific literature on possession will
be analysed. This will look at variables influencing possession, different methods of
measuring possession and then finally the justification for the study as a whole.
2.2 Match Analysis of Football
Match analysis in football has been used in both practical and research settings to
enhance performance and identify trends and similarities in the game. The use of
match statistics can be as basic as the result of the game or as complicated as the
work-rate or pass completion percentage of individual players on the team.
As it is impossible for a coach to accurately remember everything that happens in a
match the need for performance analysis is vital because the difference between
success and failure for top level teams can be so small. Franks and Miller (1986)
explain that coaches can only recall 30% of the incidents that occur in a game of
football resulting in a huge collection of actions that have not been addressed, which
can be with the use of performance analysis (Hughes & Franks, 2004).
4
The need for performance analysis is obvious as it provides an objective analysis as
opposed to a subjective one. Olsen and Larsen (1997) explain how nearly all the
coaches in the Premier League use performance analysis even ten years ago. The
analysis collected can be presented in a number of ways, with the use of video
feedback resulting in reduced observer bias and collection of more information
(Hughes & Franks, 2008). The use of notational analysis is an objective way of
recording performance (Hughes, 2004) so that the results can be fed back to
coaches for improvement in future matches.
Yiannakos and Armatas (2006) explain that one of the main characteristics of
football is that it is low scoring; therefore an objective understanding of the
fundamentals of attempts on goal is essential. In order to become successful a team
must be able to score goals (Jones et al., 2004) and also concede less than the
opposition through the personnel they put out on the pitch (Szszepanski, 2008).
2.3 Score-line
It has been shown that score-line can affect performance, Shaw and O’Donoghue,
(2004), O’Donoghue, (2003), Redwood-Brown, (2008) have all looked at the issue.
In tennis, serving is of vital importance and breaking the serve of the opposition
gives the player the lead and momentum in a set. Scully and O’Donoghue (1999)
found that successful players (those which won the match) maintained a similar
strategy when serving throughout the match, whereas the unsuccessful players
changed strategy when serving on service breaks. This change in strategy was
found to be disadvantageous to the player, making them more susceptible to a break
back from their opponents. A drawback of this paper was the assumption of a
generalised class of player, which O’Donoghue (2003) addressed. The author used
a cluster analysis to compare the strategies adopted by different classes of player.
Different groups of player were found to attack the net more when ahead than when
behind, predominantly players who serve-volley. Other groups attack the net more
5
when behind, experimenting with net strategy. The study shows that score-line does
affect the way in which tennis players play, but the affect is different depending on
the class of player.
O’Donoghue and Tenga (2001) argued that score-line can be viewed as a
performance accomplishment, influencing the effort of a player in soccer. Elite
soccer players were observed and actions recorded on audio-cassette as to the
effort exerted by the player. The values were split into eight sub-categories ranging
from stationary to high-intensity activity. Results showed that teams tended to work
harder when level than when ahead or behind and teams that were leading tended
to relax allowing opponents back into the game. It was also found that teams that
were losing may lose the motivation to work hard. Although this paper showed
significant results, there is an issue with the method of data collection as with the
large number of sub-categories it is difficult to assume definitely that a player is
walking not jogging or jogging and not running. The transition between these
categories is also difficult to quantify and separate operators may code these actions
differently creating ambiguity in the system.
The O’Donoghue and Tenga (2001) paper discussed the issue of score-line
influencing effort during a match. The authors explain how the effort expanded
depends on the likelihood of success. This is confirmed by Bandura (1977) where if
the perceived task is difficult then the effort extenuated will reflect the difficulty level.
This can be applied to the score-line during a match, if one team is two or three
goals behind with only a small amount of time left there is very little chance of getting
a result so the motivation to maintain the effort drops (Bandura, 1977). Although this
suggestion is practical, results were not found to support this view in a paper by
Mohr et al. (2003). The study looked at 27 Premier League football matches and the
physical activity of players in different positions was measured. Results showed in all
matches there was a lower level of activity in the last 15 minutes of play which was
6
accredited to fatigue. Of the 27 matches, 6 had a difference of more than 1 goal and
in the last 15 minutes of play there were found to be no difference between activity
patterns.
Shaw and O’Donoghue (2004), like O’Donoghue and Tenga (2001) used similar
categories to examine the effect of work rate on score-line with amateur players.
Although a similarly large amount of categories were used, high levels of agreement
could be seen (difference of 0.3% was shown between the authors for time spent
performing high-intensity activity). Work rate was compared between teams that
were level and ahead and teams that were level and behind. Results supported the
work of O’Donoghue and Tenga (2001) that teams work harder when level than
when ahead or behind.
Jones et al. (2004) and Lago and Martin (2007) found that teams had more of the
ball when they were behind compared to when level or ahead. Jones et al. (2004)
collected data from Premiership games and Lago and Martin (2007) from La Liga.
As the data is from club football in different countries it may have been expected that
differences in possession would be seen, as the style of play associated with each
country is different. England is known for its direct style compared to the ‘continental’
possession football associated with Spain (Franks & McGarry, 1996). Jones et al.
(2004) explained the differences in possession when behind was due to the
desperation of the losing team, i.e. needing a goal to avoid defeat. The authors also
found that when winning, successful teams held onto the ball for longer periods than
unsuccessful teams. The study examined total periods of play where evolving match
status (level, ahead or behind) was taken to have an influence on possession. Other
variables used were opposition, location (home v away) and team identity (reference
to a team which were top of the league at the time). The data only considers
possession as minutes in control of the ball which is not very detailed and does not
analyse the numbers of passes in possessions only a length of time.
7
Redwood-Brown (2008) studied the number of passes and successfulness of these
passes for five minutes before and five minutes after a goal was scored in soccer.
This five minute period was decided upon because overall changes in the behaviour
of players could be more closely identified if the game was split into five or fifteen
minute segments (Carling et al., 2005). Redwood-Brown (2008) justified the choice
of five minute intervals because of the work by Carling et al. (2005) on changes of
the behaviour of individuals. Possession is not a type of behaviour, and passes by
players are counted for the whole team, unlike the example by Carling et al. (2005)
where sprint performance of individual midfield players was studied. The choice to
split the match into these segments is perhaps a little flawed and should only be
applied to individual behaviours where differences throughout the game would be
expected, e.g. sprint time change due to fatigue. The study showed that there was
not a difference in passes or successfulness of passes before or after the goal. As
the study only investigated the five minutes before a goal was scored where in
reality a team may be in control of a match for much longer than five minutes before
scoring, or alternatively a goal might be scored against the run of play.
Work by Bloomfield et al. (2004a) found that the strategy used by teams in the FA
Premier League was influenced by the score-line in the game. Successful teams had
more possession of the ball when winning or losing than when they were drawing,
with the opposite seen with unsuccessful teams. Although this is true there was
found to be no effect of score-line on intensity of play. Shaw and O’Donoghue (2004)
found that work rate can be due to fatigue or if the outcome of the result is obvious.
This study was carried out on amateur level soccer players, so assuming these
same results will occur with elite professional footballers is unrealistic. Bloomfield, et
al. (2004a) found that score-line affected work rate as more high intensity activity
could be seen when scores were level compared to being ahead or behind. Both
these studies agree that score-line does have an effect on performance, but
Bloomfield et al. (2004b) disagreed, finding that score line had no effect on work rate
when more detailed methods were used.
8
2.4 Tactical Analysis
Reep and Benjamin, (1968) discovered that 80% of goals in soccer were scored
from possessions involving three passes or less. Bate (1988) supported this issue,
concluding that with more possessions, the attacking team has more possibility of
entering the attacking third of play, creating a greater chance of scoring a goal. The
importance of regaining possession of the ball in the attacking third was also found
to be beneficial with 50-60% of goals in the study scored from this scenario. Bate
(1988) argues that a direct style of play is more advantageous than possession
football because more shots and goals are created from possessions occurring with
a low number of passes.
This statement was challenged by Hughes and Franks (2005) as data was
normalized giving an equal number of possessions for sequences of each length of
pass. Original results did support previous research that more goals are scored from
possessions occurring with a low number of passes. This is only true because there
are more possessions of shorter length in a match. Data from the 1990 and 1994
world cup gave possessions of around 16,000 for a possession of 0 passes, 8,000
for 1 pass, 5,000 for 3 passes and so on (Hughes & Franks, 2005). When data was
normalized giving the number of goals scored per 1,000 possessions more goals
were scored from possessions ranging in 4-7 passes in length compared to 0-3
(Hughes & Franks, 2005). The study has shown that a direct style of play is not
necessarily the most favourable way to play compared to possession football as
thought previously in the literature.
Pollard et al. (1988) compared different strategies or styles of play in soccer. The
authors developed six categories including multi pass possessions, long forward
passes and regaining possession in attack. Data was only considered for some
teams for two or three matches, which in reality is not enough to base the style of
play of a team upon as with so few outside factors such as level of opposition,
9
players available and state of the game play a key role (Pollard, et al., 1988).
Another issue is the number of categories used. One style of play can be
misinterpreted as another very easily causing ambiguity in data collection, this can
also be found in the work of Ali (1988) where seven categories were used to define
possession types. The data collected should be viewed with caution as a reliability
study was not undertaken on the data collection process.
Hughes et al. (1988) found that to play down the centre was typical of successful
teams, but Griffiths (1999) found that the most successful team at the time
predominantly used the wings. This may be due to when the papers were published
as over 10 years the style of football played by the top nations may have changed.
The latter paper also found that wing play was only favoured by the most successful
team, this may be due to that team having world class wingers and to give the ball to
them was to play to the team’s strengths. Other teams may not favour wing play as
highly. Stanhope (2002) disagreed with both papers, finding that there was not a
significant difference between where on the pitch passes were played. The paper
compared a successful team (winners), against an unsuccessful one (previous
holders, but failed to make it past the group stage). The paper also found that it is
unfair to define success and failure on the outcome of one game. Stanhope (2002)
explains how the unsuccessful team may still have played in a successful manner
but lost the matches. This is because one moment of brilliance by the attacking team
or a defensive error by the opposition can be the difference between success and
failure in top level football matches. The difference between international teams in
top level soccer is so small that to classify success on the outcome of a match is
maybe a little unforgiving. Stanhope (2002) continues by explaining how analysts
need to re-evaluate methods of clarifying success especially for major tournaments.
Also the playing style, i.e. central versus wing play cannot be proved successful on
matches that can be one and lost by one single incident of brilliance, luck or critical
error.
10
2.5 Possession
A study by Grant et al. (1999) found that successful teams can penetrate the
defences of the opposition for longer sequences of play. This agrees with Hook and
Hughes (2001) where successful teams were found to utilise possession longer.
Bate (1988) also supported the argument for possession being an indicator of
success, with more possessions giving a greater chance of entering the attacking
third of play. Furthermore, the author concluded that it is not beneficial to just move
the ball forward quickly. Stanhope (2001) provided more ambiguity to the issue when
he found that time in possession was not indicative of success. It is concluded that
although having the ball for long periods of time is beneficial to performance, this
alone does not provide success. It is more important to create something with the
possession gained, than to hold on to the ball for long periods of time and do
nothing.
Bergier et al. (2005) carried out a study on women’s football counting the number of
passes for each possession, but also where on the pitch the possession started, the
number of players involved, length of time and detailed information on the final ball.
The authors only considered those possessions that resulted in a shot at goal, all
other possessions were discarded. The study found that possessions with a shot at
the end mainly started when teams gained the ball in the middle or offensive thirds
of the pitch and with longer possessions it was harder to score. Data collected found
that 14% of shots attempted resulted in a goal, a figure in agreement with Hughes
and Franks (2005) on the men’s game where around 10% of shots were found to
result in a goal. Although the data was collected on women’s soccer the results are
similar to men’s game where the highest number of possessions were of zero pass
length, then one, then two etc. This is also in accordance with Hughes and Franks
(2005), Reep and Benjamin (1968) and Bate (1988).
11
Hewer and James (2004) compared goal scoring strategies between the United
Kingdom and Europe. It was concluded that there was generally very little difference
between the numbers of passes played to score a goal, a mean of 3.2 passes per
goal was seen in Europe and 2.9 passes per goal in the United Kingdom. Europe
was found to have deeper defences, which can maybe explain the need for more
passes to break them down. The long ball behind the defence was found to be more
prevalent in the UK which is unsurprising as British football is well known for this
direct style of play.
Jones et al. (2004) explained that the many studies looking at possession in football
have been criticised because of a lack of reliability of the data collection systems
used. The authors also discussed the fact that it is difficult to categorise teams as
successful or unsuccessful because of match outcome. Consider a match where the
score is 0-0 for 90 minutes and then an injury time winner separates the sides. For
almost the whole match the teams could not be separated but if only the result was
taken one team would be classed as successful and the other unsuccessful, where
as in reality this is unfair.
2.6 Justification for study
The current study will therefore investigate the influence of score-line on possession
in Premier League Football. Score-line is more indicative of the way possession
varies across a match so is therefore more suitable than simply categorising
matches based on result (Jones et al., 2004). As the outcome of a match can be
influenced by a single moment of brilliance or a bad error, to presume that a team is
successful based on outcome of a match is potentially unreliable (Scoulding et al.,
2004). The topic has not really been considered in that much detail with very little
research on score-line at all, especially that which is soccer specific, containing
teams from all levels in the Premier League. Therefore the current study compared
the possession of teams when they were level, ahead or behind. The possession
12
data collected looked at the number of passes and players involved in every
possession, where on the pitch these possessions took place, the methods in which
they started and ended and how many resulted in a shot at goal.
13
CHAPTER III
METHODOLOGY
3.0 Methodology
3.1 Participants
All players were Premier League footballers and were passive participants in the
data collection process. They were not required to undertake any specific tasks for
the study, only their actions were observed and analysed.
3.2 Instrumentation / Equipment
The football matches used for the study were recorded from Sky Television onto
DVD where they were analysed. The DVD could be paused and rewound if any
occurrences were missed and all important events were entered into a spreadsheet
using the Microsoft Excel for Windows program. The Statistical Package for Social
Sciences (SPSS) was used for data analysis.
3.3 System
The system was developed and tested on one football match to assess the length of
time to code a match and whether the amount of variables for each possession was
realistic. The first draft of the system was a little too basic and only examined where
on the pitch possession started and ended as attacking, middle and defensive thirds.
This was then split into left, middle and right to give more detail to the data (an
example of the template used can be seen in figure 1). Earlier trials in the study
included noting the player that starts and ends the possession, but this was rejected
due to time constraints and its lack of importance compared to the actual passes
and players per possession. Methods of starting and losing possession were also
reduced to make clarification of each variable simpler. To start with, too many
variables were used, including blocks, clearances and the use of different parts of
the body to move the ball. This overcomplicated the data enhancing the likelihood of
14
error and increasing the time needed for data collection. The final system was
chosen as it gave enough detailed information on each possession and did not take
too much time allowing more matches to be analysed. There were a few
complications with observing all possessions during the match in the pilot study due
to replays. Some replays ran over into the ball in play time, resulting in the start of
some possessions being missed. This tended to happen after a shot at goal or bad
challenge, but to overcome this difficulty, the possession was just started from where
the footage resumed and “after replay” was placed into the method of starting
possession column.
Figure 1 – Example of the pitch diagram used to assess where possessions begin
and end.
15
3.4 Procedure
Ten random football matches from the FA Premier League 2009/10 season were
chosen and possessions were noted for both teams when the game was level and
when one team was winning and the other was losing. This was described as the
current game status, either ahead, level or behind. This number of matches was
chosen because of the amount of time required to analyse each match, (around six
hours) due to the detailed nature of the data collection process. Each match was
then examined by the observer for defined possession characteristics which were
predetermined. For each match every possession was analysed for a) game status,
b) team in possession of the ball, c) number of players involved, d) where on the
pitch the possession started and ended, e) how it started and ended, f) number of
passes involved, g) number of players involved and if a shot or goal was the
outcome (an example of the system used can be seen in table 1).
Table 1 – An example of the system used in the data collection process.
Poss Start
(area)
Poss End
(area)
MU
9
8
Free Kick
Intercepted Pass
0
1
CH
8
5
Intercepted Pass
Foul
3
3
CH
5
2
Free Kick
Intercepted Pass
0
1
MU
2
4
Intercepted Pass
Tackle
3
4
CH
4
2
Tackle
Ball out of play
3
3
MU
2
2
Throw
Ball out of play
0
1
CH
1
2
Corner
Foul
1
2
MU
2
6
Free Kick
Ball given Away
0
1
CH
6
2
Ball given away
Ball given Away
4
4
Score
Team
0-0
Poss Start
(how)
Poss End
(how)
Passes
The team in possession of the ball was either of the two teams playing the match.
The game status was the current score-line during the game, either level, ahead or
behind. In order to determine where on the pitch the possession takes place, sectors
were used splitting the pitch into three vertical zones and three horizontal zones.
Nine sectors were then shown and each possession could start in only one of the
16
Players
sectors, giving an attacking third, middle third and defensive third and then left side,
middle and right side. This reduced error in the data collection, but the decision was
still down to the perceived view of the operator. Each possession started in a
specific third of the pitch and on either side or the middle. The possession ended
where the opponent picks up the ball on the pitch or where it went out of play, not
where the ball was given away from.
The number of passes was then noted for each possession. A pass was described
as “the act of passing the ball with any part of the body (apart from the arms and
hands) which is received by the team mate” (Redwood-Brown, 2008). The
Redwood-Brown (2008) paper defined a pass as successful if it was received and
controlled by the team mate. A set of three trained observers were used to code this
process which was too complex and complicated for the current study and therefore
discarded. Instead, a pass was deemed successful if it reached the team mate and
not if they had it under control, this is because it was easier to clarify and should
provide reliable data in the study. If the pass or clearance does not reach a team
mate then this counted as a zero pass possession.
The number of players involved in the possession was always a minimum of one. An
example of this was where a player wins the ball and then clears it out of play,
nobody else touched the ball but the possession has changed because the
opposition has the throw in. This was classed as a 0 pass possession involving 1
player. For the purposes of a foul, a new possession will start for the team that has
just been fouled, even if this results in two consecutive possessions involving the
same team.
To determine how a possession started and ended an extension of the work by
Pollard and Reep (1997) was used. The authors explained that a possession could
17
end in one of three ways; if the ball touches a player of the opposition, if the ball
goes out of play or if an infringement of the rules takes place. This was expanded for
the current study to include; foul, centre, corner, throw in, free kick, goal kick, tackle,
intercepting a pass or giving the ball away. As the end of one possession gives the
ball to the opposition, the location and method of the end of the first possession will
be the same variable as the start of the next.
A tackle was described as a player attempting to dispossess the opponent of the ball
through either a physical challenge or defensive pressure (Rowlinson &
O’Donoghue, 2009). An intercepted pass is where a player predicts where a pass
will go and moves to make an effort to cut it out. This is similar to when the ball is
given away, but when this event occurs the ball is given straight to the opposition
with no threat of a member of the team in possession of the ball getting it. The main
difference is the intent to gain the ball when intercepting a pass compared to the ball
being given to the opposition when the ball is given away. Goal kicks, throws and
corners were all started from what the referee awarded. If it appears the referee has
made a bad decision and a corner should have been awarded as a goal kick, the
decision of the referee will be taken as that is final, and true of what has occurred in
the game.
For the purpose of determining a shot, it was defined as any effort on goal with intent
to score by any part of the body apart from the arm or hand. An intended through
ball or clearance that resulted in being in the hands of the opposing goalkeeper was
not deemed as an effort on goal, so therefore did not count.
The study aimed to compare the different styles of play that occur in different scoreline states. This was achieved by comparing the number of passes and number of
players that touched the ball in each passing sequence. Data was also collected on
18
where and how possessions start and end, and analysed to compare the differences
between the various score-line states.
In addition to all the data collected, general statistics were calculated for the data
set. These included the number of possessions, shots and goals per match. These
results were then used to calculate other useful variables to analyse the data,
including the number of possessions required to create a goal scoring opportunity,
the number of possessions required to score a goal and the number of shots
required to score a goal.
3.5 Data Analysis
The Statistical Program for Social Sciences (SPSS) was used to assess the
difference between the results of possessions for different score-line states. Chi
squared tests were used on the non-parametric data and if a value of (p<0.05) is
seen then the data is deemed as significant. Score-line (ahead, level and behind)
was compared with a) area on the pitch (at the start and end of each possession), b)
method of possession gain (also at the start and end of each possession), c) number
of players involved, d) number of passes and e) current team in possession. A chisquared test is used to compare the frequencies of the data collected compared with
the frequencies that would be expected if no differences could be seen between
groups (Gratton & Jones, 2010). The test uses a null hypothesis, where there is no
association between the two variables and finds the frequency expected for each
variable if the null hypothesis were true (Bland, 2006).
19
3.6 Reliability
To assess the reliability of the data collection process, an inter-reliability study was
undertaken on one half of a match. The statistical test Kappa was used to compare
the levels of agreement between the two observers. This was achieved by creating
pivot tables in Microsoft Excel and calculating the Kappa value from the data
collected. The results of the reliability study can be seen in table 2. As the score-line
remained the same throughout the half, this was not included in the data collection
process. Kappa measures the agreement between the decisions made by the
observers, divided by what the expected value due to chance would be with a value
of 1 showing perfect agreement and 0 showing the level of agreement expected due
to chance (Everitt, 2003).
Table 2 – Kappa values for each variable observed in the reliability study.
Variable
Location of possession start
Location of possession end
Method of possession start
Method of possession end
Number of passes
Number of players
Team
20
Kappa Value
()
0.87
0.89
0.76
0.75
0.82
0.85
0.93
3.7 Ethical Issues
As only passive participants were used for the study, the players were not required
to do anything specific for the data collection process. The data was taken from
publicly available sources so written consent was not required. Team and individual
player names were not used and the data will be stored so only the researchers
involved can use it. After the study data will be stored in University Wales Institute
Cardiff (UWIC) for five years and then destroyed as part of the Data Protection Act
of1984.
21
CHAPTER IV
RESULTS
4.0 Results
4.1 Descriptive Statistics
The general statistics of the possessions, shots and goals scored can be seen in
table 3. There was found to be a total of 4,218 possessions in the study, giving an
average of 421.8 for the ten games analysed, with 34 goals scored resulting in an
average of 3.4 goals per game. Of the 4,218 possessions in the study, 232 resulted
in shots on goal, either on target, off target or saved, resulting in an average of 23.2
shots per game. The total number of possessions was divided by the total number of
shots to give a value of 18.2. Therefore, on average a shot will occur every 18.2
possessions. The same process was undertaken to find the average number of
possessions needed for each goal, and a value of 124.1 was discovered. The final
measure calculated was the amount of shots required to score a goal. This was
achieved by dividing the number of shots by the number of goals to give a value of
6.8. This indicates that on average a goal was scored every 6.8 possessions.
Table 3 – Descriptive statistics of basic variables used in data collection.
Variable
Possessions per match
Goals per match
Shots per match
Possessions per goal
Possessions per shot
Shots per goal
22
Value
421.8
3.4
23.2
124.1
18.2
6.8
4.2 Locations where possessions begin
Results for the study showed that there was a significant difference between the
location of starts of possessions (p<0.05) for different score-line states. There was
found to be more possessions starting in the middle three zones of the pitch as
opposed to on the wings (see figure 2). The diagram illustrates this as a percentage
of the total number of possessions for each score-line state. Values for the central
zones (2, 5 and 8) when behind were 16.2%, 16.0% and 14.0% respectively, when
level it was 14.6%, 19.0% and 15.6%, and when ahead was 14.1%, 16.6% and
18.7%. Very little difference can be seen between play down the left sides of the
pitch (3, 6 and 9 zones) compared to the right (1, 4 and 7 zones) in all three scoreline states. When teams were behind 46.3% of possessions started in the middle
zones compared to 53.7% from both wings. These figures were a little different for
the level and ahead score-line states. Possessions started in the middle zones for
49.2% of all possessions compared to 50.8% on the wings when level and 49.4% in
the middle zones and 50.6% on the wings when ahead. These figures indicate that
when teams are behind more possessions started on the wings compared to when
scores are level or ahead. The middle sectors (4, 5 and 6) accounted for 43.4% of
possession starts when behind, 46.4% when level and 42.5% when ahead.
Therefore, more possessions start in attacking positions (zones 1, 2, 3, 7, 8 and 9)
when teams were losing and winning opposed to drawing. These results were 56.5%
when losing and 57.5% when winning compared to only 53.6% when the scores
were level.
23
Figure 2- Location of where possessions start, as a percentage of total possessions
per score-line state.
Key
B = behind
L = level
A = ahead
24
4.3 Locations where possessions end
There was also found to be a significant difference for the location of where
possessions end when behind, level and ahead (p<0.05). As with where
possessions start there was a greater number of passing sequences in the middle
zones compared to on the wings (see figure 3). When behind these values were
15.5%, 16.0% and 19.2% in the three central zones (2, 5 and 8) giving a total value
of 50.7% compared to only 49.3% for the wings (zones 1, 3, 4, 6, 7 and 9). When
scores were level percentages in the central zones were 15.8%, 17.6% and 16.3%
giving a total of 49.3% with 50.7% made up from possessions ending on the wings.
When teams were ahead the central zones made up 46.9% of all possessions
(17.6%, 13.9% and 15.4%) compared to 53.1% from the wings. This shows that
more possessions ended in central zones when ahead compared to when level or
behind. This is in contrast to where possessions start where more passing
sequences began in central zones when teams were behind as opposed to ahead.
As one possession ends another one begins in the same place showing that as with
the possession start data, more possessions ended in attacking areas of the field
when the scores were level compared to when they were behind or ahead. As the
goals are located in zones 2 and 8 on the pitch the aim of each possession is to
move the ball to these areas to generate a goal scoring opportunity. When the
score-line statuses were behind and level a value of 30.2% was seen for
possessions ending in these zones but was higher, 32.8% when the score-line
status was ahead.
25
Figure 3- Area on the pitch where possessions end, as a percentage of total
possessions per score-line state.
Key
B = behind
L = level
A = ahead
26
4.4 Methods used to start possessions
Figure 4 illustrates the various methods of starting possessions when the score-line
status was behind. Chi squared tests found a significant difference between the
methods of starting possessions for different score-line states (p<0.05). The majority
of possessions started from either an intercepted pass, when the ball was given
away or a tackle. These three variables accounted for 69.8% of all possessions, with
the other six variables accounting for the other 30.2%.
Intercepted Pass
Ball Given Away
Tackle
Throw In
Free Kick
Corner
Goal Kick
Shot
Shot Blocked
Shot Saved
After Replay
Centre
Penalty
Figure 4 - Methods of starting possessions when behind.
27
Figure 5 shows the different methods of starting possessions when the score-line
status is level. As with the behind data, intercepted pass, ball given away and tackle
made up the majority of possessions, adding up to 70.5%. The percentage for
intercepted passes is 2.4% lower when level, and for ball given away and tackle is
2.1% and 1.0% higher respectively.
Intercepted Pass
Ball Given Away
Tackle
Throw In
Free Kick
Corner
Goal Kick
Shot
Shot Blocked
Shot Saved
After Replay
Centre
Figure 5 - Methods of starting possessions when level.
28
Figure 6 explains the methods of starting possessions when the score-line status
was ahead. As with the two previous score-line statuses the majority of possessions
were made up of intercepted pass, ball given away and tackle, 71.3% slightly higher
than the other two. This is broken down into 33.3% for intercepted pass, 25.5% for
ball given away and 12.5% for tackle. With the ahead and behind score-line status,
possessions values for intercepted pass were 2.4% higher than when level.
Intercepted Pass
Ball Given Away
Tackle
Throw In
Free Kick
Corner
Goal Kick
Shot
Shot Blocked
Shot Saved
After Replay
Centre
Penalty
Figure 6 - Methods of starting possessions when ahead.
29
4.5 Methods used to end possessions
Chi squared tests on the different methods of finishing possessions did not find a
significant difference between score-line states (p>0.05) and can be seen in table 4.
The data found that as with the methods used to start possessions, possessions
ended from predominantly intercepted passes, balls given away and tackles, a fourth
variable, ball out of play, also contributed to a large number of possession losses.
The totals of these four variables accounted for 87.4% of possessions when behind,
86.6% when level and 85.1% when ahead. As the values were higher for behind in
contrast to level, this leaves a lower number of possessions to turn into shots or
goals. The table shows the amount of shots that were off target (shot) on target but
saved (shot saved) or blocked (shot blocked). These 3 variables combined with the
number of goals give a total number of attempts on goal. The results were; when
behind 4.9% of possessions result in an attempt on goal, when level it was 5.7% and
when ahead it was also 5.7%. It is clear that this level is a lot lower for the behind
score-line state, which can be transferred into the number of goals scored in the
study. Although there were more possessions when level compared to ahead or
behind, the amount of goals scored was a lot less when behind. This was a value of
7 compared to 12 when level and 12 when ahead.
30
Table 4 – Methods of ending possessions when behind, level and ahead.
Intercepted Pass
Ball Given Away
Ball Out of Play
Tackle
Foul
Shot
Shot Blocked
Shot Saved
Goal
Own Goal
Offside
Half Time
Full Time
Count
(n)
398
286
184
167
74
21
15
14
7
0
13
3
2
Behind
Percentage
(%)
33.6
24.2
15.5
14.1
6.3
1.8
1.3
1.2
0.6
0.0
1.1
0.3
0.2
Level
Count Percentage
(n)
(%)
587
31.4
484
25.9
297
15.9
251
13.4
116
6.2
46
2.5
17
0.9
32
1.7
12
0.6
1
0.1
22
1.2
1
0.1
2
0.2
31
Ahead
Count
Percentage
(n)
(%)
385
33.0
293
25.1
176
15.1
139
11.9
83
7.1
24
2.1
14
1.2
16
1.4
12
1.0
1
0.1
12
1.0
6
0.5
6
0.5
4.6 Passes
Data collected for the number of passes in each possession did not show a
significant difference between score-line states (p>0.05) see figure 7. For all scoreline states a clear negative relationship could be seen with the highest number of
possessions occurring with 0 passes, and the second highest for 1 pass and so on.
Very few possessions were seen that exceeded 10 passes, 18 out of 1,184 when
behind (1.5%), 19 out of 1,867 when level (1.0%) and 20 out of 1,167 when ahead
(1.7%). The numbers of 0 pass possessions as a percentage of total possessions
were 42.8% for behind, 40.1% for level and 44.6% for ahead. These values do not
differ greatly between score-line states but the value when level is a lot lower that
what would be expected if no difference was seen and the level when ahead is a lot
higher.
50
45
40
35
30
Behind
25
Level
20
Ahead
15
10
5
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 21 24 31
Figure 7 – The number of passes per possession as a percentage when behind,
level and ahead.
32
4.7 Players
As with the numbers of passes per possession the number of players that touch the
ball shows a negative relationship with possession. This relationship was not
deemed to be significant (p>0.05) between the varying score-line states. The
number of possessions decreased as the number of players involved increased.
Possessions involving up to three players represented the majority of all
possessions for each score-line state. When behind this total was 80.6%, when level
it was 80.9% and when ahead it was 82.4%. This illustrates that very few
possessions involved large numbers of different players and there was not a single
case where a possession involved all members of the same team out of 4,218 in
total. From figure 8 it is clear to see that there is very little difference between the
score-line states for the number of players involved per possession.
50
45
40
35
30
Behind
25
Level
20
Ahead
15
10
5
0
1
2
3
4
5
6
7
8
9
10
Figure 8 –The number of players per possession as a percentage when behind,
level and ahead.
33
CHAPTER V
DISCUSSION
5.0 Discussion
5.1 Introduction
The aim of the study was to examine the effect of score-line on possession in
soccer. The study looked at the method and location on the pitch where the
possessions started and ended, the number of passes and the number of players
involved in each possession. The variables examined were compared when behind
to level and ahead to level to identify differences in the data set.
5.2 Reliability
The results of the reliability study were good, with the Kappa values for 5 out of the 7
variables examined over 0.80, which Altman (1991) explains is very good. The other
2 variables showed a good level of agreement (>0.60). Although this is the case,
there was some confusion when deciding the methods used to start and end
possessions. These provided the lowest Kappa reliability scores (0.76 for the starts
and 0.75 for the ends) as the events ‘intercepted pass’ and ‘ball given away’ were
entered differently on a number of occasions. The difference between the two events
was clearly stated for both observers before the data collection process began,
where a player must make a movement towards the ball to intercept the pass
(intercepted pass) before it reaches the opponent compared to when the ball is just
given to him (ball given away). This can be subjective and with the amount of
changes of possessions that take place during a match there is bound to be some
level of error, but it was not too high.
From this type of research process there can be three types of error; operational where the observer presses the wrong button, observational - where the operator
fails to code an event and definitional - where the observer labels the event
34
incorrectly (James et al., 2002). As the analysis was done post game and not live,
the amount of operational error was low because the match could be paused and
the events entered. The same is true for observational error as if play is moving too
quickly for the observer the match can be paused or rewound to examine any events
that may have been missed. The use of clear operational definitions that were
outlined before data collection began enabled a reduced amount of operational error
between users.
5.3 General possession characteristics
Previous research has showed a negative binomial relationship between possession
length (passes per possession sequence) and the number of possessions (Hughes
& Franks 2005; Bate, 1988; Reep & Benjamin, 1968). This relationship was further
confirmed in the current study, with a steep decrease shown in the number of
possessions as the number of passes increased per sequence increased. This
relationship could also be seen between the numbers of players involved in each
possession which has not been considered in the literature up to now.
This negative binomial relationship is unsurprising as the English game is well
known for its direct style of football (Bangsbo & Peitersen, 2000). The authors
explained how the direct style aims to get the ball forward and finish possessions as
quickly as possible, preferably with a shot or even a goal. This approach opposes
both possession soccer and counter attacking play where the aim is to break down
opponents through elaborate and fast passing sequences (Bangsbo & Peitersen,
2000). Although this relationship was seen, there are still influences of the other
styles of play, through foreign managers and players more suited to those styles.
This can be observed in the data with many possessions over 20 passes in length
and 3 goals out of 34 scored from possessions of more than 10 passes.
35
The total number of possessions in the study was 4,218, giving an average of 421.8
per match. This value disagrees with the work of Lanham (1993) where 220-270
possessions per match were seen; considerably lower than the current study. The
probable difference in the studies is concerning the definition of a possession. In the
current study a change in possession included any touch of the ball by the
opposition unless this touch is very slight or meaningless. This resulting in a large
number of 0 pass possessions increasing the total number of possessions during a
match. If the current study had discarded all 0 pass possessions, the number of
possessions per match would be 244, agreeing with the work of Lanham (1993).
This difference was suggested due to the work of Jones et al. (2004) where between
201 and 262 possessions per match were observed. The study measured
possessions as the length of time that a team had the ball and excluded all
possessions of 3s or less, which is suggested would be similar to removing all 0
pass possessions. Other factors that may have caused the differences observed
may be due to the data set used. In the Lanham (1993) study, matches were
analysed from a number of English Leagues, not just the top league, and the data is
from 1981-1991 which is therefore outdated. During this time football has changed
considerably, so differences in results between these time periods would be
expected.
As well as possessions, the number of goals scored in the study was examined and
the results showed that 34 goals were scored during the 10 matches analysed. This
resulted in an average of 3.4 goals per game which was higher than the current
league average of 2.79 (www.soccerstats.com). The average was higher because
games were chosen which had goals in, excluding goalless draws so that the match
could be analysed in each score-line state.
36
On average, a goal was scored every 124 possessions which is a lot less that
reported by Lanham (1993) who explains that this figure will rarely deviate by more
than 10%, but the current study shows a deviation of over 30%. This can possibly be
explained by 2 explanations. Firstly, the goals per game average was high because
only matches were used in the study where goals were scored (to incorporate all
score-line states) and secondly the improvement in efficiency of scoring by
professional players in the modern day game.
It is widely recorded in the literature that 80% of goals are a result of possessions of
three passes or less (Bate, 1988; Reep & Benjamin, 1968; Hughes & Franks, 2005).
The current study offers some support for this view and showed a value of 70.59%
for goals that were scored from three passes or less, with 76.47% seen for four
passes or less, which is similar to Hughes and Franks (2005) who found 80% of
goals were scored from passing sequences of 4 passes or less. This figure is a lot
less than Bate (1988) where a figure of 94% was discovered, possibly demonstrating
the influence of more possession soccer as the most recent studies found a lower
percentage of goals being scored from possessions involving lower passing
sequences.
Many studies have also considered the ratio of goals to shots, with a value of around
10% consistently seen (Reep &Benjamin, 1968; Carling 2005, and Hughes and
Franks, 2005). The current study showed a slightly higher value of 14.59% which
although higher is still relatively similar to the other studies and supports the findings
of Bergier et al. (2005) who found 14%. This gives ratios of shots to goals of around
1:7 for the current study compared to 1:10 in the majority of the literature.
37
5.4 Differences in possession when behind compared to level
For all score-line states there was found to be more possessions starting in the
middle zones of the pitch than on the wings. When teams were behind, only 46.3%
of possessions started in the middle zones compared to 49.2% when level. The
explanation for these figures is due to offensive tactics when behind. Prestgiacomo
(2003) describes how when teams are behind they need to push forward and score
a goal to equalise. The simplest way to do this is to increase the number of balls into
the penalty box the team is attacking. The author explains that this is achieved
through predominantly crosses or long balls, with this style of play becoming more
prevalent as the final whistle approaches.
The results also found that more possessions start in the attacking and defensive
zones when behind, than when level. This disagrees with the work of Bloomfield et
al. (2004a) where more play was found in the attacking and defensive zones when
level and less when behind. The study only examined three top level teams which
would expect to win all their matches, as opposed to fifteen in the current study
spanning the whole league. When the top teams are level they are therefore more
likely to start possessions in attacking areas to get them into the lead. As their
players are of a greater quality they can keep onto the ball when winning. This was
suggested by Jones et al. (2004) where successful teams had more possession than
unsuccessful accredited to the more skilful players of the top teams.
As the
Bloomfield et al. (2004a) study only concerns the top teams, the amount of time
when they are behind is notably less than when level and ahead.
The opposite was found when examining where possessions end. When behind
50.7% of possessions end in the central zones compared to 49.3% on the wings.
These figures differ when the score-line state is level, where 49.3% possessions
ended centrally and 50.7% ended up on the wings. Although the difference is small it
further supports the notion of Prestigiacomo (2003). When behind teams try to get
38
more balls into the box resulting in the possessions ending in the central zones. As
this is most efficiently achieved through crossing, more possessions start from out
wide when behind. Carling et al. (2005) explains how crosses are an important part
of all types of football but are more prevalent in domestic soccer compared to
international soccer and therefore these differences may not be seen in a study
concerned with international teams.
Data gained on the methods of starting possessions in soccer found a significant
difference between score-line states (p<0.05). Values for tackles and when the ball
was given away were observed to be higher when the score-line status was level.
These variables can be most attributed to work-rate in soccer, and therefore the data
supports the view of O’Donoghue and Tenga (2001) that teams are put under more
pressure when level than when behind.
The data collected on the way in which possessions end was not found to be
significant (p>0.05), but some differences between score-line states could still be
observed. The four major methods of losing possession were intercepted pass,
tackle, ball given away and ball out of play. A greater percentage of possessions
were found for these variables when behind compared to when level, leaving a lower
number of possessions to turn into shots. This could be seen in the data set, with
higher numbers of shots and goals when teams were level compared to when
behind. This contradicts Taylor et al. (2008) where shot success was found to be
similar when behind and level.
There was found to be no significant difference between the number of passes per
possession and number of players involved for each score-line state (p>0.05). The
data shows that with each score-line status a negative binomial relationship can be
seen (Franks & McGarry, 1996). The data is almost identical when behind and level
39
concluding that the length of passing sequence and the number of players that touch
the ball does not change when behind or level. Bloomfield et al. (2004b) offers some
support to this notion although the study examined work-rate and not possession.
The authors found that there was no difference between the work-rate of players in
all three score-line states. If the work-rate of the players does not vary then the
amount of pressure applied onto the opposition will not change, impacting upon the
number of passes for each score-line state. Redwood-Brown (2008) also provided
some support, finding no meaningful correlations between the number of passes
before and after a goal was scored for both the scoring (ahead) and conceding
(behind) teams. Although this was the case, the accuracy of the passes increased
for the attacking team before scoring and decreased for the conceding team. This
variable was not calculated in the current study as a pass was only deemed a pass if
it was successful, unsuccessful passes were classed as a change in possession.
Therefore this finding by Redwood-Brown (2008) cannot be supported by the current
study as the successfulness of a pass is just defined as a pass, and there was not
found to be a difference when behind compared to when level.
In the study possession was measured by the number of passes per sequence and
not by the actual time each team has the ball. Jones et al. (2004) and Lago and
Martin (2007) found that when behind teams had more possession of the ball as a
length of time compared to teams that were ahead. Although there is a difference
between measuring the number of passes per possession compared to the length of
time in possession, a difference can be seen between the lengths of possessions
when behind compared to ahead. If all 0 and 1 pass possessions are discarded as
Jones et al. (2004) did with possessions less than 3s in length, the total number of
possessions left is 36.0% when behind, and 36.6% when level. These values are
higher than the 32.4% seen when ahead, supporting the views of these authors that
teams have more of the ball when behind. Although this may be true, it is more
important to create opportunities with the possessions that you have as opposed to
having lots of possession and doing very little with it.
40
5.5 Differences in possession when ahead compared to level
The results collected show that when ahead possessions start more centrally than
on the wings. This is in agreement with Prestgiacomo (2003) who explains that when
behind possessions start on the wings more often. When ahead the need to score
another goal is not as vital as when behind, so fewer balls are shifted wide to cross
where there, although there may be a greater chance to score, there is also a
greater chance of losing possession. The results show similar values for ahead and
level when comparing wings versus central, but the values differ when comparing
the attacking and defensive zones on the pitch compared to the midfield zones. The
possessions were found to start more often in the attacking and defensive zones
when the score-line status was ahead and behind compared to level, which is in
disagreement with the work of Bloomfield et al. (2004a) where the opposite was
found.
The same results were seen for location of possession endings with more in the
attacking and defensive zones when ahead and behind compared to level. Some
support for the higher number of possessions when ahead and behind can be
explained by Lucchesi (2003). The author concluded that when teams are losing
they tend to become more desperate and increase their pressing further up the
pitch, when previously they would be happy for the opposition to have the ball in
their own defensive areas. This increase in pressing puts the team ahead under
more pressure forcing them to get rid of the ball. This reduces the number of passes
per passing sequence and therefore increases the numbers of possessions in these
areas for both score-line states.
The opposite is true when the score-line is level. When teams are level they tend to
allow the opposition to have the ball in their defensive zone and not start pressing
until they enter the midfield zone (Lucchesi, 2003). This leads to a lower number of
possessions as a numerical value, but results in a higher number of passes per
41
sequence. The totals of 0 and 1 pass possessions are higher when ahead compared
to level; this value is 67.7% when ahead compared to 63.5% when level. These
results further confirm the view that when teams are ahead they are put under more
pressure by the desperate measures of teams that are behind (Lucchesi, 2003),
reducing their number of passes per possession and increasing the total numbers of
possessions.
There is further disagreement with previous literature when the different methods of
starting possessions are examined. The three major contributors are the same with
all score-line states; tackle, intercepted pass and ball given away, but the value is
higher when ahead compared to level. This would suggest that the players work
harder to get the ball back when ahead compared to level which contradicts
Bloomfield et al. (2004a) where the level score-line state was associated with a
higher work-rate. Although this is true, between all score-line states the values of the
three methods of starting possession which can be most linked to work-rate only
vary by 1.5%. The data is therefore more supportive of the study by Bloomfield et al.
(2004b) where more detailed methods were used to examine work-rate, and there
was found to be no significant difference between the effort extenuated when
behind, level or ahead.
When ahead and level, the data shows that the values for the number of
possessions that are transferred into an attempt on goal are the same, but a lot
lower when behind. The success rates of these shots (those that are turned into
goals) are a lot higher when ahead compared to level and behind. This agrees with
Taylor et al. (2008) where this difference was accredited to the teams attempting
more difficult shots as their situation is more desperate.
42
CHAPTER VI
CONCLUSIONS
6.1 Conclusions
Results from the study show that there are some differences between the use of
possession in different score-line states. The null hypothesis stated that there would
be no significant differences between the locations and methods of starting and
ending possessions, number of passes and number of players between different
score-line statuses. This hypothesis was accepted for the methods of ending
possessions, number of passes and number of players involved in each passing
sequence because Chi squared tests revealed values of p>0.05. Alternatively, the
null hypothesis had to be rejected for the variables location of possession start and
end and method of possession start, because Chi squared tests revealed significant
differences of p<0.05 for the varying score-line states.
These findings show that the number of passes per possession and players involved
does not vary for differing score-line states, but the locations and methods of which
these possessions start and end do change. When behind teams increase their
chances of getting balls into the box by passing wide and crossing with the opposite
being true when ahead, as more possessions start in central positions. When teams
are level there was found to be very little difference in the locations of where
possessions started and ended.
6.2 Future directions
The study has concluded that the style of play teams adopt differs somewhat when
level, ahead and behind. Due to the time constraints of the study and available
resources the data set was relatively small, so the process should be applied to a
larger sample of matches. The study has also only considered elite level domestic
soccer. In the future research should be broadened to examine these differences in
lower level and international soccer.
43
The study only examined the effect of score-line on possession in soccer. Score-line
is not the only influence on performance, other variables such as home advantage,
crowd size, referee decisions and level of opposition should also be taken into
account. Many studies have examined the impact of these variables, but very few
combine all variables including individual skill and luck. This is because team sports
are notoriously difficult to accurately analyse compared to individual sports. There
are so many more outside influences and interactions with other team mates than
can be the reason for winning or losing a game. The combination of these variables
should be examined and also their relative level of importance to the outcome of the
match, e.g. home advantage may be found to be more important that score-line
status etc.
More detailed analysis should be employed to create more categories than just
behind, level and ahead. When behind and ahead the score-lines states should be
expanded into severity of score, as if a team is 0-1 behind they will play very
differently to if they were 0-3, or 0-4 behind. This was not considered in the study
and needs to be addressed in the future.
44
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