CARDIFF SCHOOL OF SPORT
DEGREE OF BACHELOR OF SCIENCE
(HONOURS)
SPORTS COACHING
TITLE
AN INVESTIGATION INTO THE LINEOUT
PROCESS USED BY TEAMS AT THE 2011
RUGBY WORLD CUP
NAME
SION LIAM SUMMERS
UNIVERSITY NUMBER
ST09001600
SION LIAM SUMMERS
ST09001600
CARDIFF SCHOOL OF SPORT
CARDIFF METROPOLITAN UNIVERSITY
AN INVESTIGATION INTO THE LINEOUT PROCESS
USED BY TEAMS AT THE 2011 RUGBY WORLD CUP
CONTENTS
CHAPTER ONE
1.0 Introduction………………………………………………………………………….……1
CHAPTER TWO
2.0 Literature review…………………………………………………………………………3
2.1 Historical view of Notation……………………………………………………….……..3
2.2 The Need for notational analysis……………………………………………………...3
2.3 Performance analysis as an integral part of the coaching process………………..5
2.4 The use of performance analysis in sport………………………………….…………7
2.5 Hand notation in rugby union……………………………………….………….…….10
2.6 Performance analysis in rugby union………………………………………………..11
CHAPTER THREE
3.0 Methodology……………………………………………………………………………14
3.1 Participants…………………………………………………………………….……….14
3.2 Procedure………………………………………………………………………………15
3.3 Operational definitions and performance indicators……………………………….17
3.4 Pilot study………………………………………………………………………………23
3.5 Template design……………………………………………………………………….25
3.6 System Reliability……………………………………………………………………...26
3.7 Reliability results…………………………………………………….…………………27
CHAPTER FOUR
4.0 Results…………………………………………………………………………………..28
CHAPTER FIVE
5.0 Discussion………………………………………………………………………….…53
CHAPTER SIX
6.0 Conclusion………………………………………………………………………….....60
REFERENCES…….…………………………………………………………….….…….63
LIST OF TABLES
Table
Title
Page number
3.1 Participating teams during the Rugby World Cup 2011…………………….…...16
3.2 Operational definitions for the different areas of the pitch……………….……...17
3.3 Operational definitions for the delivery type options……………………….…….18
3.4 Operational codes and definitions for unsuccessful lineouts…………………....19
3.5 Operational code used for the line-up at the start and the end of the lineout....20
3.6 Operational codes used to highlight who the jumper was in the lineout…..…....20
3.7 Operational codes used to highlight the lifters during the lineout………………..21
3.8 Operational definitions to view if quick ball was produced from the lineout…….21
3.9 Operational definitions of the zone the ball is thrown to…………………………..22
3.10 Operational definitions of the different options available for the use of
possession………………………………………………………………………………….22
3.11 Operational definitions of the gain line being crossed…………………………...23
3.12 Operational definitions for won and lost lineouts…………………………………23
3.13 Initial template designee used for pilot study……………………………………..24
3.14 Kappa values and their strength of agreement (Landis and Koch, 1977)……..26
4.1 Individual teams lineout success during the pool stages of the Rugby World Cup
2011……………………………………………………………………………..…..………28
LIST OF FIGURES
Figure
Title
Page number
2.1. Fairs (1987, pg. 128) model of the coaching process……………………..….…....6
2.2. Hughes and Franks (2002, pg. 59) coaching process model………………....….7
3.1. Hand notation system template…………………………………………….…...…..16
3.2 Rugby Union pitch colour coded and labelled………………………………...…...17
3.3 Final template designee for the hand notation system designed on Microsoft
excel 2010…………………………………………………………………………………..25
3.4 Kappa reliability test results for the performance indicators used…….……..…..27
4.1 Game success rate of the top two teams from each pool………………………...28
4.2 Game success rate of the bottom two teams from each pool……………………29
4.3 Combined percentage of lineouts won and lost between the top two teams…...29
4.4 Combined percentage of lineouts won and lost between the bottom two teams of
each pool…………………………………………………………………………….……...30
4.5 Individual teams lineouts won and lost throughout out the pool stages…..…..…30
4.6 Average amount certain player is used to jump at the lineout by the top two
teams………………………………………………………………………………………..31
4.7 Average amount a certain player is used to jump at the lineout by the bottom two
teams………………………………………………………………………..……………....31
4.8 Average amount a lineout structure was used by the top two teams of each
pool………………………………………………………………………………..……..….31
4.9 Average amount a lineout structure was used by the bottom two teams of each
pool…………………………………………………………………………………….……32
4.10 Combined use of possession for the top two teams of each pool……………...32
4.11 Combined use of possession for the bottom two teams…………………………32
4.12 Combined amount each delivery type was used by the top two teams of each
pool………………………………………………………………………………….………33
4.13 Combined amount each delivery type was used by the bottom two teams of
each pool……………………………………………………………………………………33
4.14 Combined amount a specific player was used to lift in the lineout by the top two
teams……………………………………………………………………………….............34
4.15 Combined amount a specific player was used to lift in the lineout by the bottom
two teams……………………………………………………………………………….….34
4.16 Combined unsuccessful lineouts in each quarter of the game by the top two
teams………………………………………………………………………………………..35
4.17 Combined unsuccessful lineouts in each quarter of the game by the bottom two
teams……………………………………………………………………………….............35
4.18 Lineout success rate for each team individually…………………………………35
4.19 How many times each team individually used a specific player to lift in the
lineout……………………………………………………………………………………….38
4.20 How many times each team individually used a specific player to jump in the
lineout……………………………………………………………………………………….40
4.21 How many times each team individually used a specific delivery type………...42
4.22 How each team individually used their possession from the lineout……..….....45
4.23 How many times each team individually used a specific lineout structure…….47
4.24 How many lineouts each team won and lost during each game played……….50
ACKNOWLEDGEMENTS
I would like to thank my dissertation tutor Chris Davey for his guidance and
supervision throughout the completion of this study. I would also like to thank the
Performance Analysis staff at UWIC for their support and help to gather all the
video footage needed for this study to be carried out.
i
ABSTRACT
The aim of this study was to analyse and investigate the lineout procedure
between the top two and bottom two teams of each pool during the 2011 Rugby
World Cup. The main objective was to highlight any similarities between the top
and bottom teams in world rugby and then asking a further question does a
successful lineout lead to a winning team.
A hand notation template was developed on Microsoft Office Excel 2010 with the
data being collected using this notation system. The template was then tested for
reliability using KAPPA, results from the test illustrated that the system was
reliable. This study analysed a total of 16 Rugby Union teams, each playing 4
games each during the Rugby World Cup 2011 pool stages. The results gathered
from the study were analysed and presented into graphs and pie charts using
Microsoft Office Excel 2010. The top two and bottom two teams of each pool were
analysed together along with teams individually being analysed, this allowed for
comparative analysis to be carried out. The performance indicators selected for
this study were: Area of pitch, time, score, lineout won or lost, lineout line-up at the
start, lineout line-up at the end, lifters, jumpers, zone thrown too, delivery type,
was the gain line crossed, was quick ball produced and the use of possession.
The results gathered from this study illustrate that the performance indicators
chosen for this study has an impact on the lineout being successful and that a
successful lineout has an effect on winning and losing within Rugby Union. During
the pool stages of the Rugby World Cup 2011 the top two teams had the highest
percentage of game success with 84% success, whilst the bottom two teams of
each pool had an 84% losing rate. This can be related to the lineout success rates
of both the top two and bottom two teams, the top two teams had an average of
86% and the bottom two teams had an average lineout success of 75%.
Many similarities and differences arose throughout this study, the top two teams
tended to lose more lineouts to the team at the bottom of the table than anybody
else, also the teams at the bottom of the pool tended to lose more lineouts to the
pool winners. Also, the bottom two teams of each pool lost more lineouts in the
opening and closing quarter of each game than the top two teams.
ii
CHAPTER ONE
INTRODUCTION
1.0 Introduction
The increasing use of performance analysis within professional sport is underlined
by the importance to extend the emphasis on the delivery of biomechanical and
technical information on performance to support the coaching process (Mellalieu,
2005). As the level of professionalism in the sport of Rugby Union grows the need
for high quality performance analysis also grows with it. The sport is in a rapid
state of evolution (Agnew, 2006), therefore, increasing the need for up to date
analysis. Agnew (2006) states that as the sport of Rugby Union evolves, the
speed of the game increases leading to important incidents during a match not
being accurately recorded. Rugby union teams and players individually look to
maximise their performance levels, they look at performance analysis as a way
forward to find new ideas and areas of their game they need to improve (Mullen
and Hughes, 2001). Hughes (2004) supports the previous statement by saying,
performance analysis has been formed into the modern day of rugby union to
produce objective feedback to players and coaches to improve levels of
performance.
A number of studies have been conducted relating to rugby union, Hughes and
Jackson (2001) conducted a study on tactical decisions made whilst using
different patterns of play, Hughes and Griffith (2005) conducted a study on the
biomechanical movements of a place kicker. There is a limited number of rugby
related studies focusing specifically on the lineout area as a whole, studies
focusing on specific aspects such as the biomechanics of the lineout throw have
been conducted but none on the lineout as a whole. Data released by the IRB
(2005) produced statistics on the lineout from all the major tournaments e.g. Tri
Nations, Six nations, but no information was produced revealing the complexity of
the lineout process and its direct effect on having a successful team. Within Rugby
Union there are a number of key sources of possession (Greenwood, 1997). One
such source is the lineout, a previous study conducted by Sasaki et al (2007)
focusing on scoring profiles within Rugby Union found out that 50% of points
scored were from the use of possession from the lineout within the Japanese
Rugby league.
1
The primary aim of this study was to provide detailed information relating to the
lineout process of the top two and bottom two teams from each Pool participating
in the 2011 Rugby World Cup. The main focus was to highlight any major
similarities and differences between the different teams. Individual matches were
also analysed and data collected to identify any differences between teams
individually rather than as the top two and bottom two combined. Thirteen
performance indicators were used to collect the information and provide statistics
to coaches relating to key information on their opposition lineout. The study will
also pay attention to how different teams used their possession.
The aim of this study is to consider whether a successful lineout is important to a
team’s success. In analysing the performances of teams at the 2011 Rugby World
Cup a number of hypotheses will be considered.
H1. Are the most successful teams those with the most successful lineouts.
H2. Do successful teams employ a variation in their delivery type to less
successful teams.
H3. Is there a relationship between the time that lineouts are lost between
successful and unsuccessful teams.
H4. Do successful teams vary the lifters in the lineouts more than
unsuccessful teams.
Limitations
Throughout viewing the recorded Rugby Union matches certain aspects of the
matches were missed, the beginning of the lineout was an aspect that was often
missed by the camera man, the lineout structure at the start and the zone thrown
to was not always shown. This was down to replays being shown as the lineout
was being formed therefore missing the start of some lineouts. Camera angles
were also an issue with some angles zooming out or not focused enough, this
resulted in some aspects of the lineout being missed or not being visible.
2
CHAPTER TWO
LITERATURE REVIEW
2.0 Literature review
2.1 Historical view of Notation.
“General rudimentary and unsophisticated forms of notation have existed for
centuries with most of its early work in sport involving sports such as squash and
football” (Hughes and Franks, 1997).
Notational analysis has been around for thousands of years dating back to the
Egyptians in 1500BC, the Egyptians are thought to have used a hieroglyphics
notation system as a way of measuring gestures and dance patterns. The Romans
on the other hand developed a primitive method in which to use notation to record
beneficial gestures in a military environment (Hughes and Franks, 1997). In spite
of this it was the introduction of dance which set the foundation into the
development of movement notation (Hughes and Franks, 1997). Benseh and
Bensesh (1910) created a method combining of symbols and lines as a means to
record different body movements, this represented the development within the
field of notation. This study by Benseh and Bensesh (1910) later became the first
suitable notation system to be used within sport (Hughes and Franks, 1997).
Notation in Sport was first published by Fullerton (1912, cited in Hughes and
Franks, 1997), the study explores the different combinations of baseball players
such as pitching, fielding, batting and the probabilities of success. Messersmith
and Butcher (1939) later created a notation system focusing on movement,
specifically focusing on the distance player’s travel during a match in basketball.
Other studies by Messersmith (1939) in American Football, field hockey and
soccer have led to the development of several notation studies across sport
(Lyons, 1996)
2.2 The Need for notational analysis
Over the last 30 years sport has become a multimillion pound industry with
extreme media coverage all over the world (Smith, 1997). The amounts of money
professional athletes earn adds increasing pressure on them to perform week in
week out. This leads to high expectations on both the players and coaching staff,
3
which can lead to underperforming (Miller, 1986). Notation is viewed to have a
qualitative approach to analysis, notation analysis produces comprehensive
descriptors of different matches, therefore is seen as a vital part of the coaching
process (Franks, 1993). Coaches can gain in depth knowledge from the analysis
of the matches and relate them player’s performance which leads into future
training sessions and team selection. With the data gained from the matches,
coaches can plan training sessions around their weaknesses and look to enhance
their strengths for future fixtures (Franks, 1986). Franks and Goodman (1986,
pg.78) state that:
“The coaching and teaching of new skills relies a great deal upon notation analysis
in order to effect an improvement in athlete performance”
Before the introduction of notation analysis coaches used to observe a game and
make judgements on what they had seen (Miller, 1986). On occasions’ coaches
would misinterpret something that happened or missed a vital moment of the
game which would lead to inconclusive or poor feedback to the athlete, Hughes
and Franks (1997, pg8) support this fact by stating, “Human memory systems
contain limitations and it is almost impossible to accurately remember every event
that takes place during a game”.
Research by Franks and Miller (1986)
investigates the effectiveness of such observational difficulties and came up with
four main obstacles which had most effect on the coaches’ observation.

Human limitations – difficulty recapturing certain events and their outcomes,
this is down to the amount of information being produced during a game.

Viewing conditions – distance coach is from pitch side, poor light, weather
conditions, the effect the crows plays, for example amount of noise being
produced or any distractions being caused.

Effect of emotions – arousal levels and emotional state at different times of
the game will have a major effect on a coaches observation

Set views and prejudice – the coaches own beliefs on how the game
should be played and his own opinion on certain decisions, this would
damage observation accuracy.
4
A further study conducted by Hughes and Franks (1997) revealed that
international level football coaches were only capable of capturing forty two
percent of vital information relating to their teams successful performance. This
study supported the notion that notation analysis was in a desperate stage and in
need for a better and more reliable system for storing, collecting and the use and
distribution of its data, as the human memory was insufficient for remembering an
entire game or specific performance.
2.3 Performance analysis as an integral part of the coaching process
Lyle (2002) defines the coaching process as a sequence of actions and
interventions, which involve planning, coordination and integration focused on
improving competition performance. Performance analysis of sport plays a major
role within the different coaching processes. Franks and Miller (1986) states that
the information regarding a performer’s performance is used by the coach to plan
and create a practice environment and supports the improvement of the athlete’s
behaviour. Lyle (2002) and Franks (2001) both underpin the importance for
coaches to prioritise performance improvement. There are a number of coaching
processes each with their own unique methods of learning (Lyle, 2002). The
significance of understanding the coaching process and how it can be expanded
into different environments with the main focus on the importance and benefits for
the coaches to build a strong relationship with their athletes, Seidentop (1991).
The appliance of audio visual aids has been recognized by the vast amount of
models in the coaching process that include performance analysis (Winkler, 1988).
Hughes and Franks (2002) along with Fairs (1987) identified coaching models to
reveal the relation between performance analysis and the coaching process.
5
Figure 2.1 Illustrates Fairs (1987, pg128) model of the coaching process
Figure 2.1 above exemplifies the five stage model of the coaching process created
by Fairs (1987), this model is split up into five individual stages, consisting of
observation and data collection, assessment and diagnoses, plan of action,
execution of the plan and evaluation of the whole process.
The coaching process being such a broad area to study, making assumptions
such as this creates an unrealistic vibe surrounding the model (Lyons, 1988). Fairs
(1987) model of the coaching process fails many aspects of the evaluation criteria
but Lyle (2002) defends this model and implements that people are too critical
upon its evaluation of the process. On the other hand Hughes and Franks (2002)
produced a more simplistic model specifically focusing on the evaluation stage
during the coaching process and the link between performance analysis and
coaching, which is demonstrated in Figure 2.2 below.
6
Figure 2.2 Illustrates an adapted version of Hughes and Franks (2002,pg59)
coaching process model.
The use of video recordings to aid coaches in sporting environments was
established soon after video cameras became obtainable (Lyons, 1988). With the
current advances in technology, in particular at elite levels of sport they are given
great input into how performance analysis can assist them to develop their
athletes performance levels (Bartlett, 2001). O’Donoughue (2004) highlights the
importance that while conducting performance analysis the main priority should be
to provide statistics to the coach and athlete regarding a sporting performance that
will further enhance the player or coaches decision making in furtue.
Bartlett
(2000) demonstrates how performance analysis has transformed players and
coaches to analyse their sport performance using biomechanics and a multitude of
notational analysis systems. Verger (2007) explored different methods of coaching
and the impact they have on player’s decision making, exploring the various
contributing factors whilst under pressure to make the correct technical decision.
2.4 The use of performance analysis in sport
Performance analysis is used to support the process by which feedback is
provided for coaches and athletes. Feedback can assist the coaching staff and
players in various different ways to improve sporting performance, Hughes (2002).
The two main disciplines related to performance analysis are biomechanics and
notational analysis, both these can be applied within the sport of rugby union as a
7
type of performance analysis. Bartlett (2001) identifies the link between both
notational analysis and biomechanics and how they improve performance. Both
disciplines require in depth use of video analysis to create top quality feedback for
coaches through using information management procedures and systematic
techniques for observation. Biomechanics studies analyse in fine detail the
technical movement of individual performers in sporting environments, this is used
in many forms in the game of rugby union for specific skills such as lineout
throwing and place kicking. Notational analysis looks to specify particular
movement patterns in team sports instead of movements as a whole (Hughes
1996). For example, Hughes and Bartlet (2002) demonstrated the function of
performance indicators in a variety of sports. Hughes and Bartlet (2002) define a
performance indicator as a selection or combination of action variables that aim to
define all aspects of a certain performance. Different performance indicators are
used by different coaches to view the performance of an individual players or the
team as a whole. Notational analysis systems have been used to answer
fundamental questions regarding game play and performances in different sports
for decades. (Hughes and Bartlett, 2002)
Bartlett (2001) identifies the differences between the different disciplines, focusing
on the how notation analysis mainly focuses on the gross movements in team
sports
highlighting
tactical
and
technical
performance
indicators.
While
Biomechanics on the other hand highlights performance indicators that have
sufficient impact on techniques and how they can be improved (Hughes and
Bartlett, 2002). Managerial and coaching staff must be aware of the changes in
the techniques of top level athletes as they look to continuously improve their
athletes skill levels (Croucher, 2001)
Giatsis and Tzetzi’s (2003) conducted a study comparing the differences between
winning and losing teams in beach volleyball by using notation analysis. A total of
nine teams were observed analysing three specific technical skills, the serve,
reception and the attack. After in depth analysis, results highlighted that two
factors had a major influence on winning and losing, the winning teams used a
spike move at certain times in each match resulting in winning important points at
critical times in the match, while losing teams produced more errors while the
difference in score was at 3 points.
8
Ballesteros and Peñas (2010) researched a similar study focusing on specific
performance indicators between winning and losing teams in La Liga, the Spanish
football league. All 360 games during the 2008-2009 season were analysed using
the ANOVA analysis system. The variables focused on for this study were split
into three groups, goals scored (goals for and against, total shots and on and off
target etc.), offence (assists, offside’s, fouls and crosses etc.) and finally defence
(tackles made, yellow cards received and fouls committed etc.). Results from this
study show that teams in the bottom half of the table required a higher number of
shots per goal ratio compared to teams in the top half of the table who have a
higher average of goals per shot ratio and possession of the ball.
Garganta (2009) conducted a study linking both the biomechanical aspect of
analysis and notational analysis together. The study was conducted using a
female basketball team based in Portugal, the study focused on two elements,
notational analysis and biomechanics. Notational analysis was used to collect data
on the performance such as points scored and tactical decisions used, and
biomechanical data was gathered to improve the athlete’s performance levels by
breaking down their technique, in this case the biomechanical structure of the
jump shot was broken down and analysed.
Performance analysis has a major impact on teams and individual athletes looking
to enhance performance levels to reach their goals of being successful. Hughes
and Franks (1997) identified multiple areas that a team’s performance is
structured around, from tactics to individual skill levels. In conclusion performance
analysis in sport specifies in investigating appropriate areas of team and individual
performances in a professional environment (O’Donoghue, 2005). Performance
analysis has evolved into a big part of professional sport to date due to the
demand for feedback to facilitate coaches and players to improve their sporting
performance. Hughes (2002) acknowledges performance analysis as, ‘the
measurement of performance which allows for simple functional identifications of
both the strong and weak aspects of a performance’.
9
2.5 Hand notation in rugby union
“Rugby union presents slightly different problems for analysis compared to other
sports such as football or water polo, as set piece moves, the lineout and scrum
and the activity ensuring from a tackle either a ruck or maul can be very
complicated” (Hughes and Franks,1997, pg,70). However rugby union has been
analysed for many years and has been transformed from using hand notation to
computerised systems, (Hughes and Franks, 1997).
Hand notation systems were the beginning of analysis in rugby union, and were
experimented with over the years to find the correct process, (Hughes and Franks,
1997). The sequence involved with hand notation is a relatively easy one as long
as the performance analysis team have a clear understanding of the system they
are using and know who and what they are observing.
Lyons (1988) conducted a study using data collected using a hand notation
system overlooking ten years of the Five Nations Championship. From the results
of the study Lyons was able to predict accurately the number scrums, lineout’s,
passes and kicks to within two or three between Wales and Scotland in 1988
fixture.
A further study by Treadwell (1992) also used a hand notation system to analyse
40 various matches over a five year period focusing on the Five Nations
Championship. The results from Treadwell’s (1992) study highlighted that rugby
union formed a rhythm for predicting specific variables in spite of
the playing
conditions, team selection and referee decisions.
Even though hand notation systems were useful and used in significant amount of
sports it was expected that a more scientific and advanced method of analysis
would be created. Computerised notation is quite similar to hand notation but
computerised notation gives you the opportunity to go into greater complexity.
Hours of processing time was removed using computerised notation along with the
analyst who had access to the data straight away. Before computerised notation
was produced, to analyse one game of squash using hand notation it would take
41 hours to process using the Sanderson notation system, (Hughes and Franks,
1997, pg. 64).
10
Hughes and Williams (1988) developed computerised software designed to notate
rugby union matches post event using video tapes. A total of four software
programmes were created by Hughes and Williams (1988), the data collection
programme, this is defined as the most important variables to record while the
other three programmes were being analysed and processed. This system was
used to observe and notate four matches from the Five Nations Championships,
the four matches were compared and the different patterns of play were outlined
for each team. The findings of this study found no significant differences between
the four team’s patterns of play. Not even between the successful and
unsuccessful teams.
McCorry et al, (1996) created a specific match analysis system for post-match
analysis of rugby union, this system focuses on the positive and negative aspects
of attacking and defensive plays, possession changes and why and the method
used to gain territory. O’Donoghue (2002) continued this study and used the same
system to analyse the winning and losing teams during the 1999 Rugby World
Cup which was held In Wales, England, Ireland and France. From O’Donoghue’s
(2002) study results indicate that the possession of the ball crossed the losing
teams 22m line far more frequent than it did the winning teams.
2.6 Performance analysis in rugby union
Performance analysis has become of significant importance in the sport of rugby
union as the need for detailed feedback on performances has increased, coaches
came to the conclusion that detailed analysis on both the opposition and their own
performances was a top priority (Hughes 2001). The assistance of notational
analysis in rugby union has provided an objective to review the performances of
players which is then transformed into data to be presented to the coaches,
therefore aiding feedback to enhance athlete’s performance levels (Hughes and
Franks, 2004). Various studies have been conducted focusing on performance
analysis within rugby union from patterns of attacking play to the biomechanics of
lineout throwing. Hughes and White (1996) conducted a study investigating the
diverse patters of play between successful and unsuccessful forward play during
1991 Rugby World Cup in England. O’Donoghue and Hunter (2001) focused their
11
study on the positive and negative relations between the changes in possession
and the methods used to gain a territorial advantage during the 1999 Rugby World
Cup. Greenwood (2003) tried to identify the effects of elite playing status in rugby
union using the various patterns of play between 1986 and 2000. As the
complexity of rugby union is so high, recent studies surrounding this area have
specified on more detailed aspects of play instead of the game as a whole, such
as Sayers (2004) who focused on the efficiency of an offensive ball carry and
Jones (2002) who explored the biomechanics of a place kicker,
Since the establishment of rules in rugby union in 1845 (Sheard, 1999), the lineout
as a whole has developed to be controlled and reliable.
“It used to be a war zone, a place filled with wild animals and hard men. Some of
us have the scars to prove it. It was as much a horizontal confrontation as it was a
vertical challenge. The emphasis was on domination, exerting your physical will,
with elbows and knees, by barging and jumping to lay claim to your space,
Nowadays the lineout is easier physically, but still no place for pussy cats. It is still
demands accuracy, athleticism and corporate effort”. (Redman and Smith, 1998
p.12)
The evaluation and analysis of the lineout process has a limited amount of
literature and previous studies. Sasaki et al (2007) conducted a study investigating
scoring profiles and defensive performances within rugby union, the Japanese
national league was studied from 2003 to 2005. The main objective of this study
was to examine the correlation between the amount of points scored and the
method in which they were scored (Sasaki et al, 2007). Result from this study
provides evidence that the most common and effective source of scoring tries was
from the lineout, with over 50% of tries scored during this study had been
influenced from the lineout. Hardy (1999) discovered that during the 1996 Five
Nations Championships the average number of lineouts in an international match
was 41. In 1998 the amount of lineout’s in international rugby has roughly halved
to 22, this was also accompanied by changes to the law of the lineout, with the
IRB bringing in new lifting laws to improve safety issues.
The gradual development of the professional sport of rugby union has placed
increased pressure on the delivery of the lineout and its success, due to the lack
12
of relevant literature surround the lineout process specifically it is vigorously
important that additional studies are conducted on this element to support and
assist the coaching process (James, et al. 2005).
13
CHAPTER THREE
METHODOLOGY
3.0 Methodology
This study will analyse, compare and investigate the performances of rugby union
teams during the 2011 Rugby World Cup in New Zealand. The main focus of this
study will be the tactical and technical decisions made at the lineout and its
outcome, such as the number of players in the lineout, the movement prior to the
jump/lift, field position and the use of possession. Sixteen different teams will be
analysed, the top and bottom two teams of the four pools will be focused. The
data collected will then be transferred onto a digital analysis programme using
Sports code Elite for further observations. Following the data collection
comparisons were made using a series of data sheets, tables and graphs, which
provided in depth results enabling an evaluation on how the different international
teams contrast against each other. The Rugby World Cup 2011 was chosen
because it includes both Northern and Southern hemisphere teams along with the
amount of games being played. For the data collection to be conducted, postmatch analysis of the fixtures was carries out using pre-recorded footage of the
Rugby World Cup 2011, the footage was transferred onto a TOSHIBA 500gb
external hard drive and viewed through using a ASUS K53E laptop. By using an
ASUS K53E laptop equipped with Microsoft office excel 2010, a notation system
was created which allowed me to conduct lapsed-time analysis of proceedings
which occurred at the lineout.
3.1 Participants
The sixteen international rugby union teams observed and analysed within this
study were, New Zealand, France, Canada, Japan, England, Argentina, Georgia,
Romania, Ireland, Australia, United States of America, Russia, South Africa,
Wales, Fiji and Namibia.
Thomas and Nelson (2002) identified that for the
information collected to be valid it must be appropriate and recent. The footage
gathered for this study was the live broadcast from the BBC. Forty games were
analysed in total, all ten games from pool A, B, C and D. The teams chosen for
14
this study were selected in relation to the pool tables at the end of the pool stages
during the World Cup. The top two and bottom two teams from the pool table
were selected to take part in this study. Brackendirge (1985) believes that a total
of twenty games or more is regarded to be enough to collect valid data to highlight
differences in patterns of play. Hughes (2001) on the other hand argues the fact
that as the size of the database increases the task of noticing changes in patterns
of play would become harder, therefore Hughes (2001) came to the conclusion
that five matches would create a valid performance profile to be produced.
Previous studies conducted by Hughes et al (2004) highlights the importance of
normative profiles as when a constant state of performance per match is
recognized to categorize data as a profile. Hughes and Wells (2001) reestablished and developed the use of normative profiles within performance
analysis by using specific performance indicators and focusing on technique
during a single match rather than numerous games to produce more detailed
analysis. Prior to the study commencing, ethical approval was granted by the
Cardiff Metropolitan University (UWIC).
3.2 Procedure
Each match was observed using an ASUS K53E laptop and Sports code Elite,
within the performance analysis laboratories at Cardiff Metropolitan University
(UWIC). The matches were coded using a hand notation system designed within
the software Microsoft office Excel 2010. The hand notation system includes the
following:

Lineout number

How the players line up at the start of the lineout

How the player are lined up at the end of the lineout

Zone thrown to

Jumpers

Lifters

Won or lost – if lost why?

Field position

Time

Score
15

Was the gain line crossed?

Was quick ball produced?

Use of first phase possession

Delivery type
Figure 3.1 below shows an example of how the performance indicators were
transferred into template format in Microsoft Office Excel 2010.
The top two and bottom two teams from each of the pools shown in Table 3.1
were analysed focusing on their attacking options, data from each of the
international Rugby Union games was then collected and put together to offer a
larger database.
In choosing the most successful and least successful teams from each pool it
should be possible to consider any differences which might exist between these
teams and therefore discover whether their use of lineout possession is a factor
leading to the success of the team.
Table3.1: Participating countries and the final pool table in the Rugby World Cup
2011.
Pool A
Pool B
Pool C
Pool D
1st New Zealand
1st England
1st Ireland
1s South Africa
2nd France
2nd Argentina
2nd Australia
2nd Wales
3rd Tonga
3rd Scotland
3rd Italy
3rd Samoa
4th Canada
4th Georgia
4th USA
4th Fiji
5th Japan
5th Romania
5th Russia
5th Namibia
16
3.3 Operational definitions and performance indicators
Hughes and Bartlett (2002) define a performance indicator as a variety of action
variables that looks to define specific aspects of a single performance. Tactical
indictors attempt to reflect the style of the athlete by representing the choices
taken at different points of the match (Agnew, 2006).
The rugby union pitch was split into four equal sections, these sections were
colour coded and labelled as shown in Figure 3.1.
Figure 3.2 Rugby union pitch, colour coded and labelled.
GL
YL
BL
RL
Try Line
Try Line
22m line
22m line
GM
YM
BM
RM
GR
YR
Half way BR
line
RR
------------------
Direction of play
Table 3.2: below indicates the operational definitions for the different areas of the
pitch.
Area of pitch
Description
Code
Green Left
Defending 22 meter line to try line, left hand GL
side
Green middle
Defending 22 meter line to try line, middle
17
GM
Green Right
Defending 22 meter line to try line, right GR
hand side
Yellow Left
Defending halfway line to 22 meter line, left YR
hand side
Yellow middle
Defending halfway line to 22 meter line, YM
middle
Yellow Right
Defending halfway line to 22 meter line, YR
right hand side
Blue left
Attacking 22 meter line to halfway, left hand BL
side
Blue Middle
Attacking 22 meter line to halfway, middle
BM
Blue right
Attacking 22 meter line to halfway, right BR
hand side
Red Left
Attacking try line to 22meter line, left hand RL
side
Red Middle
Attacking try line to 22 meter line, middle
RM
Red Right
Attacking try line to 22 meter line, right hand RR
side
Table 3.3 Indicates operational definitions for the delivery type options.
Different types of
Code Definition
delivery type used
Catch and Drive
CAD
The ball is caught at the lineout, player and ball are
grounded and a driving maul is created. This is when
players form the same team bind together in an attempt
to drive the ball up the pitch.
Catch and give
CAG
The ball is caught at the lineout, ball and player are
bought down and grounded then the ball is passed to a
different player, e.g. the scrum half
18
Off the top
OTT
The ball is caught at the lineout, whilst the player is still
in the air he passes the ball down to another player.
This is used to try and generate quick ball.
The ball is thrown past the 15 meter line by the hooker
Long throw
LT
Quick line out
QL
to an attacking player.
A player throws the ball back into the field of play to
himself or a team mate before the lineout has been
formed.
Kick
K
The ball is won by the attacking team then kicked
away.
Penalty for
PF
The official awards a penalty to the attacking team as
an infringement has been committed by the defending
team.
Free kick for
FkF
The official awards a free kick to the attacking team as
an infringement has been committed by the defending
team.
Table 3.4 below indicates operational codes and definitions for unsuccessful
lineouts
Unsuccessful
Code
Definition
OT
The hooker throws the ball over the intended
lineout options
Over throw
receiver resulting in a loss of possession.
Knock on
KO
The ball is knocked forward by the attacking
team resulting in a scrum or an advantage to the
defending team.
Not straight
NS
This occurs when the hooker throws the ball into
the lineout but does not travel in a straight line. If
this occurs a scrum will be offered to the
opposition
19
Stolen
S
The opposition steal the ball at the lineout and
win possession of the ball.
Penalty against
PA
The official awards a penalty to the defending
team as an infringement has occurred.
Free kick against
FkA
The official awards a free kick to the defending
team as an infringement has occurred.
Table 3.5 below indicates the operational code used for the line-up at the start
and the end of the lineout. From the front of the lineout to the back.
Line-up
Line-up code
Prop, second row, prop, second row, 1,4, 3,4,6,8,7
flanker, number eight, and flanker.
Table 3.6 below indicates operational codes used to highlight who the jumper was
in the lineout.
Number on the jumpers shirt / Code
player thrown to
4 – second row
4
5 – second row
5
6 – blindside flanker
6
7 – open side flanker
7
8 – number eight
8
If a player is replaced during the game it will be highlighted as followed, 18 (R8).
So number 8 is replaced by number 18.
20
Table 3.7 below indicates operational codes used to highlight the lifters during the
lineout.
Lifters (number on shirt)
Code
1 – loose head prop
1
3 – tight head prop
3
4 – second row
4
5 - second row
5
6 – blindside flanker
6
7 – open side flanker
7
8 – number eight
8
Table 3.8 below indicates operational definitions to view if quick ball was produced
from the lineout.
Quick ball produced
Code
Definition
Quick
Q
If the ball is passed away from the tackle area
within 0 to 4 seconds, the timing of the ball
being produced will commence once the ball
carrier has been tackled.
Medium
M
If the ball is passed away from the tackle area
within 4 to 8 seconds, the timing of the ball
being produced will commence once the ball
carrier has been tackled.
Slow
S
If the ball does not come out within 8
seconds, the ball is deemed slow, the timing
of the ball being produced will commence
once the ball carrier has been tackled.
21
Table 3.9 Operational definitions of the zone the ball is thrown to.
Zone thrown to
Code
Front – the hooker throws the ball to the F
pod at the front of the lineout
Middle- the hooker throws the ball to the M
pod at the middle of the lineout
Back - the hooker throws the ball to the B
pod at the back of the lineout
Table 3.10 Operational definitions of the different options available for the use of
possession
Use of possession
Code
The ball being passed
9
The ball has been kicked
10 K
Ruck had been formed - Players that ( R , 12,14)
are in the ruck are also added, In this
case players 12 and 14 are in the ruck.
The attacking team loose possessions BL
of the ball e.g. knock on, stolen or
penalty awarded against them.
Try scored off the phase of play
T
Penalty awarded during the phase of
PF
play
22
10
Table 3.11 Operational definitions of the gain line being crossed
Gain line crossed
Code
Definition
Yes
Y
The attacking team have progressed beyond
the hypothetical line from the lineout and
gained territory.
No
N
The attacking team have not progressed
beyond the hypothetical line from the lineout.
Table 3.12 Operational definitions for won and lost lineouts.
Outcome
Code
Definition
Won
W
The attacking team keep possession of the ball
from their lineout.
Lost – reason why lost
L-
The attacking team loose possession of the ball
during the lineout.
As squad rotation varied from game to game, players’ names will not be used
during this study, the player’s position and number on the back of their shirts will
be used as a replacement.
3.4 Pilot study
A pilot study was conducted to ensure the chosen system designs was reliable
and accurate, also to ensure the appropriate information was captured. The pilot
study was conducted on the Rugby World Cup final 2011, New Zealand against
France. All of New Zealand’s lineouts were notated and analysed during the 80
minute match. Two templates were used during this pilot study, the initial template
(Table 3.1) used did not allow me to collect the relevant data needed to conduct
this study. Therefore to improve validity, more performance indicators were
needed to ensure enough valid data would be collected whilst analysing the
matches to generate binding results. Gratton and Jones (2010) highlight that
performance indicators need to be effective and accurately defined to reflect what
23
is being researched. After analysing the results collected from the pilot study and
not getting the information required it became obvious that some modifications
were needed to generate the data required, therefore four modifications were
added to the final template to aid in the data collection process, these were:

Was the gain line crossed?

The use of possession from the lineout

Was quick ball created?

And the line-up formation from the start and the end of the lineout.
Table 3.13 Initial template design for the pilot study, showing data collected for
New Zealand’s lineouts during the World Cup Final 2011.
Lineout
Time in Score
number
minutes
Lost
and
–
seconds
1
01.08
Won/
why?
0-0
L
No
of Zone
Jumper
players
thrown
(players
in
to
shirt
lineout
Lifters
Field
Lineout
position
option
used
number)
- 5
M
4
1+3
BR
-
KO
2
04.06
0-0
W
5
B
4
3+5
BL
OTT
3
09.29
0-0
W
7
M
8
5+3
YR
OTT
4
10.25
0-0
W
5
F
8
1+5
GR
CAD
5
11.40
0-0
W
5
F
5
1+3
YL
CAG
6
13.55
0-0
W
7
B
6
3+7
RR
OTT –
Try
7
19.45
5-0
W
7
B
YL
LT
no8
8
24.03
5-0
W
7
M
5
1+8
RL
CAD
9
28.45
5-0
W
7
M
8
1+5
BR
OTT
24
to
10
44.01
5-0
W
7
B
8
3+5
BL
OTT
11
56.31
8-7
W
0
-
-
-
RR
QL
12
60
8-7
L
- 5
M
7
8+3
BR
-
7
M
4
3
KO
13
65.40
8-7
W
+ YL
CAG
+ GR
CAG
18
14
71.10
8-7
W
7
F
4
1
18(5)
15
79.30
8-7
W
7
F
4
1
+ YR
CAD
18(5)
3.5 Template design
Using Microsoft excel 2010 a hand notation template was designed, (Figure 3.3).
This template would be replicated for each specific team for each match they play
in. The template is devised of 14 individual performance indicators with each
indicator having multiple options to expand on, e.g. quick ball gained would have
Quick, Medium and Slow ball options to choose from. The designee used for this
template provides the option to highlight and analyse the key proceedings of the
lineout, from the first lineout to the last. This enables the data collected to be
recorded and any errors to be changes during the analysis.
Figure 3.3 Final template designs for the hand notation system, created on
Microsoft Office Excel 2010.
25
3.6 System Reliability
Nelson and Thomas (2002) state that for a test to be deemed reliable it must firstly
have dependable sources for this to be considered. To guarantee adequate
reliability levels of the final notation system designed (Figure 3.3) an intra-operator
reliability procedure was undertaken on the final notation system. Vincent (1999)
defines this procedure as the ability to measure the consistency of the information
gathered when the procedure is performed more than once under the same
environment. New Zealand vs. France during the World Cup final 2011 was coded
by the researcher to ensure reliability. The fixture was notated and coded twice
within the same environment, with a two day gap between coding the game for the
second time. After collecting the data, both sets of results were put through a
reliability test called KAPPA to ensure validity and reliability. There is a high
expectation on ensuring that information gathered as part of the study is
sufficiently reliable (Atckinson and Nevill, 1998).
Table 3.14 List of how Kappa might be construed and its strength of agreement
(Landis and Koch, 1977)
Kappa Value
Interpretation
<0
Poor agreement
0.0 – 0.20
Slight agreement
0.21 – 0.40
Fair agreement
0.40 – 0.60
Moderate agreement
0.60 – 0.80
Substantial agreement
0.81 – 1.00
Almost perfect agreement
26
3.7 Reliability results
From conducting the kappa reliability test the results illustrate that all 13 of the
performance indicators have a Kappa value above 0.8, this now confirms that the
study can be viewed as a reliable study (Landis and Koch, 1977).
Kappa Value
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Kappa Value
Figure 3.4. Identifies the Kappa value for the performance indicators selected for
the final notation template following the Kappa reliability test.
27
CHAPTER FOUR
RESULTS
4.0 Results
Team
NZ
France
Canada
Japan
England
Argentina
Georgia
Romania
Ireland
Australia
USA
Russia
SA
Wales
Samoa
Namibia
Number of games played
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
No of lineouts
40
46
35
44
48
44
46
40
44
41
47
49
50
49
46
50
Won
38
42
25
36
42
35
36
27
40
32
40
29
41
42
37
36
Lost
2
4
10
8
6
9
10
13
4
9
7
20
9
7
9
14
Table 4.1 above indicates the amount of games each team played during the pool
stages along with the number of lineouts each team had and how many were
successful and unsuccessful.
Figure 4.1 below shows the game success rates from the top two teams of each
pool.
Number of Games played
4
3
2
Games lost
Games won
1
0
28
Number of games played
4
3
Games won
2
Games lost
Games drawn
1
0
Canada
Japan
Georgia Romania
USA
Russia
Fiji
Namibia
Figure 4.2 above indicates the game success rates for the bottom two teams of
each pool during the Rugby World Cup 2011.
Top two teams lineouts won/lost
14%
Lineouts won
Lineouts lost
86%
Figure 4.3 above shows the combined percentage of lineout’s won and lost
between the top two teams from the pool stages. As you can see the top two
teams from each pool won 86% of their lineouts and losing 14%.
29
Bottom two teams lineouts won/lost
25%
Lineouts won
Lineouts lost
75%
Figure 4.4 above shows the combined percentage of lineout’s won and lost by the
bottom two teams from the pool stages. As you can see above the bottom two
teams from each pool lost a combined amount of 25% of their lineouts and
winning 75% of them.
45
40
42
42
38
40
36
42
41
40
37
36
35
35
36
32
30
29
27
25
25
20
20
10
10
5
14
13
15
2
4
8
9
10
9
6
7
9
7
9
4
0
Won
Lost
Figure 4.5 above summarises how many lineout’s each team won and lost during
the pool stages of the Rugby World Cup 2011.
30
Combined amount each player was used as a jumper during the
pool stages
150
100
50
0
Total amount player jumped
in lineout
4
5
6
7
8
74
100
58
28
32
Figure 4.6 above shows the combined amount a specific player was used as a
target in the lineout focusing on the top two teams of each pool.
Combined amount each player was used as a jumper during the
pool stages
100
80
60
40
20
0
Total amount a specific player
jumped at the lineout
4
5
6
7
8
91
83
59
39
30
Figure 4.7 above highlights the combined amount a specific player was used as a
target in the lineout focusing on the bottom two teams during the pool stages of
the rugby world cup 2011.
Most frequent lineout strucutre used by the top two teams
from each pool.
5% 3%
7man lineout
6 man lineout
49%
36%
5 man lineout
4 man lineout
3 man lineout
7%
Figure 4.8 above illustrates the total amount a specific lineout structure was used
by the top two teams during the pool stages.
31
Most frequent lineout structure used by the bottom two teams
of each pool
5% 2%
7 man lineout
6 man lineout
20%
5man lineout
10%
4man lineout
63%
3man lineout
Figure 4.9 above illustrates the combined percentage each lineout structure was
used by the bottom two teams during the pool stages.
Top two teams use of possession
Run
Ball lost
Pass
Kick
0
Amount used
50
Kick
43
100
Pass
198
150
Ball lost
19
200
Run
24
Figure 4.10 above illustrates the combined use of possession from the lineout for
the top two teams over the pool stages.
Bottom two teams use of possession
BL
K
0
Bottom two teams use of
possession
50
100
150
200
K
P
BL
R
44
173
8
15
Figure 4.11 above illustrates the combined use of possession from the lineout for
the bottom two teams over the pool stages.
32
Top two teams Delivery type used
4% 1%
CAD
41%
40%
CAG
OTT
QL
14%
LT
Figure 4.12 above illustrates the combined percentage each delivery type was
used by the top two teams of each pool.
Bottom two teams delivery type
2% 2%
42%
37%
CAD
CAG
OTT
LT
17%
QL
Figure 4.13 above illustrates the combined percentage each delivery type was
used by the bottom two teams of each pool.
33
Total amount specific players were
used to lift
140
Amount used
120
100
80
60
40
20
0
1
3
4
5
6
7
8
Player used
Figure 4.14 above illustrates the combined amount a specific player was used to
lift at the lineout by the top two teams from the pool stages.
Total amount specific players were
used to lift
140
Amount used
120
100
80
60
40
20
0
1
3
4
5
6
7
8
Player used
Figure 4.15 above illustrates the combined amount a specific player was used to
lift at the lineout by the bottom two teams from the pool stages.
34
Figure 4.16 below illustrates the combined amount of lineouts the top two teams
of the pool lost in each quarter of the game accompanied with a pie chart showing
the percentage.
Lineouts lost
20
15
22%
26%
10
0-20
20-0
40-60
5
19%
33%
60-80
0
0-20
20-0
40-60
60-80
Quarters of the game
Figure 4.17 below illustrates the combined amount of lineouts the bottom two
teams of the pool lost in each quarter of the game accompanied with a pie chart
showing the percentage.
35
Lineouts lost
30
25
20
34%
35%
0-20
15
20-0
10
40-60
5
9%
0
0-20
20-0
40-60
60-80
60-80
22%
Quarters of the game
Figures 4.18 below illustrate the lineout success rate for each team individually
during the pool stages of the Rugby World Cup 2011.
Won
Won
NZ
Lost
Lost
France
5%
9%
91%
95%
35
Won
Lost
Won
Canada
Lost
Japan
18%
29%
71%
Won
Lost
82%
Won
England
Lost
13%
Argentina
20%
80%
87%
Won
Lost
Georgia
Won
22%
Lost
33%
67%
78%
Won
Romania
Lost
Ireland
Won
Lost
Australia
9%
22%
78%
91%
36
Won
Lost
Won
USA
Lost
Russia
15%
41%
59%
85%
Won
Lost
Won
South Africa
18%
Lost
28%
72%
82%
Won
Lost
Wales
Samoa
Won
28%
Lost
Namibia
28%
72%
72%
The pie charts above demonstrate that all the teams that finished in the top two of
their pools had a lineout success rate of over 80% with exception to two teams,
Australia who had 78% and Wales with 72% success rate. In comparison the
teams that finished in the bottom two of their respected pools had a lineout
success rate under 70% with the lowest being Russia with 59% success rate.
Three exceptions arose during the analysis of the teams that finished in the
bottom two of the pools with the USA having 85% lineout success, one of the
highest during the pool stages along with Japan with 82% success rate and
Georgia with 78%.
37
Figures 4.19 below shows how much a specific player was used to lift in the
lineout for each team individually during the pool stages of the Rugby World Cup
24
22
20
18
16
14
12
10
8
6
4
2
0
NZ
Amount used
Amount used
2011.
1
3
4
5
6
7
24
22
20
18
16
14
12
10
8
6
4
2
0
France
1
8
3
Amount used
Amount used
Canada
1
3
4
5
6
7
24
22
20
18
16
14
12
10
8
6
4
2
0
8
1
Amount used
Amount used
3
4
5
6
7
8
3
4
5
6
7
8
Player used
England
1
6
Japan
Player used
24
22
20
18
16
14
12
10
8
6
4
2
0
5
Player used
Player used
24
22
20
18
16
14
12
10
8
6
4
2
0
4
7
8
24
22
20
18
16
14
12
10
8
6
4
2
0
Argentina
1
Player used
3
4
5
6
Player used
38
7
8
Georgia
Amount used
Amount used
24
22
20
18
16
14
12
10
8
6
4
2
0
1
3
4
5
6
7
24
22
20
18
16
14
12
10
8
6
4
2
0
Romania
1
8
3
4
Amount used
Amount used
Ireland
1
3
4
5
6
7
24
22
20
18
16
14
12
10
8
6
4
2
0
8
1
Amount used
Amount used
3
4
5
6
3
7
8
4
5
6
Amount used
6
7
8
3
4
5
6
7
8
Player used
Amount used
3
5
Russia
1
South Africa
1
4
24
22
20
18
16
14
12
10
8
6
4
2
0
Player used
24
22
20
18
16
14
12
10
8
6
4
2
0
8
Player used
USA
1
7
Australia
Player used
24
22
20
18
16
14
12
10
8
6
4
2
0
6
Player used
Player used
24
22
20
18
16
14
12
10
8
6
4
2
0
5
7
8
24
22
20
18
16
14
12
10
8
6
4
2
0
Wales
1
Player used
3
4
5
6
Player used
39
7
8
Samoa
Amount used
Amount used
24
22
20
18
16
14
12
10
8
6
4
2
0
1
3
4
5
6
7
24
22
20
18
16
14
12
10
8
6
4
2
0
Namibia
1
8
3
4
5
6
7
8
Player used
Player used
All the teams during the pool stages spread out the lifting evenly between players
1,3,4,5,6,7,8, with number 1 and number 3 being used as the primary lifters
throughout. With exception to England and Australia who used their second row
(number 4) nearly double the amount of any other player to lift in the lineout as
shown in the graphs above.
Figures 4.20 below illustrating how much a specific player was used to jump in
the lineout for each team during the pool stages of the Rugby World Cup 2011.
France
8
7
7
Player used
Player used
NZ
8
6
5
4
6
5
4
0
2
4
6
8 10 12 14 16 18 20
0
2
4
6
Amout used
10 12 14 16 18 20
Amount used
Canada
8
8
7
7
Player used
Player used
8
6
5
4
Japan
6
5
4
0
2
4
6
8 10 12 14 16 18 20
0
Amount used
2
4
6
8 10 12 14 16 18 20
Amount used
40
England
Argentina
8
Player used
Played used
8
7
6
5
4
7
6
5
4
0
2
4
6
8 10 12 14 16 18 20
0
2
4
6
Amount used
7
6
5
Romania
8
Player used
Player used
Amount used
Georgia
8
8 10 12 14 16 18 20
4
7
6
5
4
0
2
4
6
8 10 12 14 16 18 20
0
2
4
6
8 10 12 14 16 18 20
Amount used
Amount used
Ireland
8
Australia
Player used
8
Player used
7
6
5
4
7
6
5
4
0
2
4
6
8 10 12 14 16 18 20 22
0
2
4
6
Amount used
USA
Russia
8
Player used
Player used
8
8 10 12 14 16 18 20
Amount used
7
6
5
4
7
6
5
4
0
2
4
6
8 10 12 14 16 18 20
0
Amount used
2
4
6
8 10 12 14 16 18 20
Amount used
41
South Affrica
7
6
5
Wales
8
Player used
Player used
8
4
7
6
5
4
0
2
4
6
8 10 12 14 16 18 20
0
2
4
6
Amount used
Samoa
8
7
6
5
4
Player used
Player used
Amount used
0
2
4
6
8 10 12 14 16 18 20
8 10 12 14 16 18 20
Namibia
8
7
6
5
4
0
2
4
6
Amount used
8 10 12 14 16 18 20
Amount used
The graphs above illustrate the amount an individual player was targeted at the
lineout. The main jumper throughout the pool stages were the two second row
players (number 4 and 5), in some cases jumping more than three times any other
players in the lineout. With exception to Ireland and France, Ireland used their
number 8 to jump a large amount of the time, along with France who used number
7 the most to jump at the lineout, 43% of the time, the only team during the pool
stages to use a back row player more than a second row to jump at the lineout.
The team to use each player an even amount to jump at the lineout was Argentina
with each player (4, 5, 6, 7, 8) jumping pretty much the same amount of times
between 8 and 11 times each.
Figures 4.21 below illustrating the delivery type used at the lineout for each team
during the pool stages.
NZ
France
5% 3%
6%
37%
CAD
CAD
40%
CAG
43%
14%
CAG
OTT
47%
OTT
QL
QL
5%
42
LT
Canada
Japan
3%
17%
CAD
38%
17%
36%
CAG
CAG
50%
11%
OTT
28%
CAD
OTT
QL
LT
England
Argentina
2% 5%
CAD
48%
43%
44%
CAG
47%
OTT
CAD
CAG
9%
LT
OTT
QL
2%
Georgia
39%
Romania
37%
CAD
56%
44%
CAG
CAD
CAG
19%
OTT
OTT
5%
Ireland
38%
52%
10%
Australia
34%
44%
CAD
CAG
CAD
CAG
22%
OTT
43
OTT
USA
40%
43%
Russia
38%
CAD
52%
CAG
17%
CAG
10%
OTT
CAD
OTT
Wales
South Africa
2%
15%
34%
CAD
CAG
27%
36%
41%
CAG
OTT
24%
CAD
OTT
21%
QL
QL
Samoa
Namibia
3%
40%
33%
9%
CAD
24%
CAG
24%
OTT
CAD
CAG
21%
QL
46%
OTT
QL
All the teams used a variation of delivery types during the pool stages from catch
and drive to a quick lineout. After analysing the pie charts above it is very clear
that the main delivery type used from the lineout was the catch and drive (CAD)
with 9 out of the 16 teams using the catch and drive as their main attacking option.
The other 7 teams used off the top ball as their number one attacking option from
the lineout. Georgia had the highest percentage for using the catch and drive
delivery option with 56% comparing that to Russia that used off the top delivery
option 52% of the time. South Africa were the closest team to having an equal split
between the amount of times each delivery type was used with the CAD being
used 34%, CAG 24%, OTT 27% and QL 15%.
44
Figure 4.22 below showing the use of possession from the lineout for each team
NZ
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Pass
Kick
Ball lost
Canada
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Kick
Pass
Ball lost
Kick
Pass
Ball lost
Run
Pass
Ball lost
Run
Argentina
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Kick
45
Ball lost
Japan
Kick
England
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Pass
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Run
Amount used
Amount used
Kick
Amount used
Amount used
Run
France
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Amount used
Amount used
during the pool stages of the rugby world cup 2011.
Pass
Ball lost
Run
Amount used
Amount used
Georgia
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Ball lost
Run
Kick
Ireland
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Kick
Pass
Ball lost
Kick
Pass
Ball lost
Run
Pass
Ball lost
Run
Run
Russia
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Kick
46
Ball lost
Australia
Kick
USA
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Pass
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Run
Amount used
Amount used
Pass
Amount used
Amount used
Kick
Romania
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Pass
Ball lost
Run
Amount used
Amount used
South Africa
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Pass
Ball lost
Run
Kick
Samoa
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Amount used
Amount used
Kick
Kick
Pass
Wales
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Ball lost
Pass
Ball lost
Run
Nambia
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Kick
Run
Pass
Ball lost
Run
The graphs above identify how each team used possession of the ball from the
lineout. As it clearly stands out from the graphs every team passed the ball from
the lineout more than double the amount of times any other option was used with
exception to Canada who passed the ball 14 times and kicked the ball 10 times.
Figures 4.23 below illustrating the lineout structures used by each team during the
pool stages.
NZ
5%
France
9%
3 man lineout
50%
16%
5 man lineout
45%
4 man lineout
5 man lineout
Full lineout
75%
47
Full lineout
Canada
Japan
2%
6%
21%
26%
3man lineout
5 man lineout
5 man lineout
Full lineout
73%
3man lineout
Full lineout
72%
England
Argentina
7%
21%
45%
3man lineout
4 man lineout
36%
5 man lineout
5 man lineout
34%
40%
Full lineout
Full lineout
17%
Georgia
3%
Romania
8%
9%
3 man lineout
4 man lineout
26%
65%
14%
5 man lineout
4 man lineout
5 man lineout
Full lineout
75%
Full lineout
Ireland
10%
6 man lineout
Australia
12%
4 man lineout
57%
33%
4 man lineout
38%
5 man lineout
5 man lineout
Full lineout
50%
48
Full lineout
USA
Russia
9%
9%
4 man lineout
52%
39%
4 man lineout
30%
6 man lineout
61%
Full lineout
South Africa
12%
3%
5 man lineout
Full lineout
Wales
5%
Full lineout
32%
Full lineout
6 man lineout
42%
5 man lineout
21%
42%
5 man lineout
4 man lineout
4 man lineout
3 man lineout
32%
6 man lineout
11%
Samoa
3% 3%
Full lineout
16%
Full lineout
13%
6 man lineout
6 man lineout
47%
31%
Namibia
3%
5 man lineout
52%
29%
4 man lineout
5 man lineout
4 man lineout
3 man lineout
3 man lineout
3%
The pie charts above highlight the percentage each teams used a specific
structure to form the lineout during the pool stages. As demonstrated by the green
section of the pie chart every team used a full lineout over 32% of the time, in
some circumstances this structure was used 75% of the time by France and
Romania. 10 out of the 16 teams used this structure over 50% of the time. The 5
man lineout was the next structure to be used more frequently with every team
having used this structure 16% of the time or more, Australia used this structure
for 50% of their lineouts during the pool stages with New Zealand close behind
with 45% and Argentina 40%.
49
Figure 4.24 below illustrates the number of lineouts won and lost for each of the
16 teams during each game.
14
12
10
8
6
4
2
0
16
14
12
10
8
6
4
2
0
2
0
0
0
8
Tonga
10
Canada
NZ Won
11
Japan
9
3
8
3
4
2
6
18
16
14
12
10
8
6
4
2
0
1
8
4
0
Japan
France
Canada Won
Tonga
11
Tonga
Japan
NZ
France Lost
2
4
10
6
0
14
6
NZ
Canada
Canada Lost
Japan Won
France
Tonga
Japan Lost
14
1
1
10
3
1
12
10
8
6
12
2
NZ
14
12
Canada
France Won
3
8
1
1
6
NZ Lost
6
1
13
France
12
10
1
0
5
8
11
11
4
10
10
6
4
2
2
0
0
Romania Argentina Georgia Scotland
England Won
4
0
12
7
8
7
Scotland England Romania Georgia
England Lost
Argentina Won
50
Argentina Lost
16
14
12
10
8
6
4
2
0
2
4
1
3
12
8
9
7
14
12
10
8
6
4
2
0
Argentina Scotland England Romania
Georgia Won
18
16
14
12
10
8
6
4
2
0
1
2
7
10
7
6
4
Scotland Argentina England
Georgia Lost
Romania Won
Georgia
Romania Lost
12
10
16
10
9
1
3
8
2
1
4
6
2
4
5
2
9
7
9
7
0
Italy
Russia
Ireland Won
16
14
12
10
8
6
4
2
0
3
Australia
USA
Ireland Lost
1
Russia
11
Ireland
USA Won
9
Italy
Ireland
Australia Won
4
12
USA
2
8
18
16
14
12
10
8
6
4
2
0
Australia
Australia Lost
7
5
12
3
5
6
6
Australia
USA
Italy
Russia Won
51
Russia
5
Ireland
USA Lost
Italy
Russia Lost
18
16
14
12
10
8
6
4
2
0
3
3
2
1
9
11
7
Wales
Fiji
SA Won
16
14
12
10
8
6
4
2
0
14
2
Namibia
Samoa
11
SA
Samoa Won
1
3
15
10
8
Namibia
Samoa
Wales Won
3
Wales
2
SA Lost
4
12
18
16
14
12
10
8
6
4
2
0
6
7
Namibia
Fiji
16
14
12
10
8
6
4
2
0
8
SA
Fiji
Wales Lost
6
3
4
9
9
8
Samoa
Wales
SA
1
7
Fiji
Samoa Lost
1
Namibia Won
Namibia Lost
The graphs above indicate the amount of lineouts each team won and lost during
each of their matches throughout the pool stages. From the results two findings
arose, the top two teams in each pool lost more lineouts to the teams in the
bottom two half of the pool, Argentina lost the highest percentage of lineouts to
teams below than anybody else, losing all 9 of their unsuccessful lineouts to teams
below them. Also the bottom two teams from each pool lost more lineouts to the
pool winners than anybody else, Georgia lost 7 of their 10 lineouts to England
their match, giving them a 30% success rate. The USA, Samoa, Japan and
Canada also lost the highest percentage of their lineouts to the pool winner.
52
CHAPTER FIVE
DISCUSSION
5.0 Discussion
The aim of this study was to analyse the lineout performance and the use of
lineout possession between the top two and bottom two teams from each of the
Pool Stages of the Rugby World Cup 2011. The results section illustrates the
differences between the top two and bottom two teams from each pool but also
considers each individual team.
From observing the pie charts illustrating the lineout success rate between the top
two and bottom two teams (Figures 4.3 and 4.4) the results show a significant
difference between the top and bottom two teams in each pool. The top two teams
won an average of 86% of their lineouts whilst the bottom two teams won an
average of 75% of their lineout possession. Within the top two teams all the
players are full time professional rugby players. This gives them more time to
practise as a team and go through each call until no errors occur along with being
fitter, stronger, more mobile and psychologically prepared to meet the requirement
asked of them in the lineout. Not every player playing for the teams that finished in
the bottom two of the pool stages are full time professional players, for example
Romania, only 10 of their 30 man squad are full time professional rugby players,
20 players from their squad play semi-professional rugby in the Romanian national
league the Divizia Naţională (Wikipedia, Romania National Rugby Team, 2012.)
This would affect them training as a team and being able to perfect their lineout
calls and moves and more importantly the throw itself. The main differences
between the top two and bottom two teams from these results are that the top two
team’s lineout success rate was better than the bottom two teams by 11% giving
them the more dominant lineout.
As demonstrated in figure 4.17 the bottom two teams from each pool tended to
lose lineouts in the opening and closing quarter of their matches, they lost 34% of
their lineouts in the opening quarter of matches (0-20 minutes) and 35% of their
lineouts in the final quarter (60-80 minutes). Greenwood (2003) describes an
unsuccessful lineout as a lapse in concentration by the different players in the
lineout from the jumper to the thrower. Greenwood (2003) also states that every
player has a specific role at the lineout and it’s the player’s responsibility to
understand the call/move for the lineout to be successful. Following on from this,
53
as not all the players from the teams in the bottom two of the pool stages are not
full time professional rugby players their fitness levels won’t be as high as the
players that are full time professionals, this could cause them to be tired in the
latter half of the second and fourth quarter relating to a lapse in concentration and
a drop in performance levels leading to unsuccessful lineouts. The reason the
bottom two teams lost so many lineouts in the first quarter could be down to
anxiety of playing at such a big occasion and the players being nervous. The main
differences between the top and bottom two teams from each pool in this section
is that the bottom two teams tend to lose their lineouts at important times during
matches, the first and last 20 minutes are the most crucial ones, they lost a total of
69% of their unsuccessful lineouts in the opening and closing quarters of their
matches, compare that to the top two teams who lost a total of 48% their
unsuccessful lineouts during these two quarters. The top two teams of each pool
lost their lineouts over a more even time range, with not one section over 26%.
The International Rugby Board (2008) state that a successful lineout is considered
successful when the attacking team throws the ball into the lineout and regain
possession of the ball and the ball or ball carrier exits the lineout.
After analysing the pie charts in figure 4.18 one statistic stands out from the rest,
the two teams during the pool stages which had the highest percentage of lineout
success were New Zealand and France, these two teams would eventually play
each other in the final of the Rugby World Cup 2011. Therefore, does having a
high percentage of lineout success lead to a successful team? Previous analysis
focusing on previous Rugby World Cups conducted by the IRB, highlight that
during the 2007 rugby world cup eventual winners South Africa had the highest
percentage of lineout success with 89%, also, in the 2003 World Cup England
(88%) and New Zealand (89%) finished with the highest percentage of lineout
success throughout the tournament. England eventually won the World Cup and
New Zealand finished third. Following on from this the IRB also identified that 26%
of all the tries scored during the tournament were scored following use of the ball
from the lineout (IRB, 2003). Linking this into the study conducted by Saski et al
(2007) who focused on scoring profiles in Japanese national rugby. He also found
that a high percentage of points were scored from the use of possession from the
54
lineout, he found that over 50% of tries were scored from the use of the ball from a
successful lineout.
Figures 4.6 and 4.7 identify the number of times the top two and bottom two teams
of each pool used a specific player as a jumper. From observing the graphs it is
apparent that the most frequent players to jump at the lineout were the two second
row players (number 4 and 5). The top two teams used number 4 and 5 to jump
59% of the time leaving number 6, 7 and 8 being used as the jumper 41% of the
time. The bottom two teams were very similar with them using number 4 and 5
57% of the time as the jumper, leaving the back row players being used as
jumpers 43% of the time. The team’s use of the second row players (number 4
and 5) as their primary jumpers reiterates Greenwoods (2003) impression of the
second row to be a tall, strong and agile whilst being lifted to secure possession of
the ball at the lineout. Figure 4.20, displays how many times each team
individually used each specific player to jump at the lineout. As demonstrated in
figure 4.20 almost all the teams used number 4 and 5 as their primary jumpers
with some teams using them nearly three times as much as any other player to
jump. Wales used their number 4 to jump 41% of the time in the lineout, apart
from number 5 the next player to be used was number 6 who was used to jump
18% of the time during the pool stages. This illustrates that teams tend to rely
dramatically on their second row players to be their primary jumpers. During the
course of the pool stages player 8 was used the least amount of times to jump
with him being used 62 times by all 16 teams involved in this study. From the
results three exceptions arose Ireland, France and the USA, as you can see in the
bar charts in figure 4.20 Ireland used number 4 and number 8, more than double
any other player along with France who used number 7 43% of the time , 18%
more than any other French player. The French were the only team during the
pool stages to use a back row player more than a second row player as their
primary Jumper. Whilst the USA used number 6 30% of the times as a jumper,
18% more than any other player including number 4. There were no real
differences between the player used to jump at the lineout between the top two
and bottom two teams from each pool, the main differences were between three
55
teams Canada, France and Ireland. These teams used back row players (player 6,
7, 8) to jump more than second row players (player 4 and 5).
The bottom two teams of each pool tended to lose possession of the ball when
throwing to the back of the lineout and a back row player was used as a jumper,
the bottom two teams used back row players as a jumper a total of 33%, for the
bottom two teams to be successful they must improve their success rate for the
ball being thrown to the back of the lineout with a back row player being used as a
jumper. This may consist of developing lineout calls which include back row
players to be positioned in the lineout to increase the percentage of them winning
or at least competing for the ball at the lineout. It may not be all down to the
jumper himself, the hooker who is in charge of the throw may be to blame of even
the lifters.
Greenwood (2003, pg., 198) states that “getting good quality clean ball from the
lineout is becoming a relatively hard task and more critical to the winning of
matches”, Wedd (1997, pg. 42) also states that “we want to be able to 100%
guarantee ball on our own throw and regain possession of the ball”. These two
statements support why different teams use a variety of variations in their lifting
pods, this keeps the opposition always thinking and guessing.
From the analysis of the player’s involvement in the lifting pod at the lineout,
similar results were highlighted between the top and bottom two teams as
illustrated in figure 4.14 and 4.15. The main lifters for the majority of the teams
were number 1 and 3 with it then being spread out evenly between the rest of the
players involved (number4, 5, 6, 7 and 8), South Africa used number 1 and 3 to lift
more than double the amount of any other player, number 3 lifted at the lineout
27% of the time for South Africa, the closest player to that not including number 1
was number 8 who lifted 12% of the time as shown in figure 4.19. This indicates
that most the teams believe player 1 and 3 to be an important lineout player and of
great importance to the function of their lineout. Two teams were exception to
this, Australia and England, both these teams used their second row (number 4)
nearly double the amount any other player was used to lift in the lineout including
one of their props which in more cases than not are the main lifters in the lineout.
It was surprising that the bottom two teams used such a variety of players in their
56
lifting pod instead of using 1 or 2 key players each time which was surprising. This
also makes the lineouts less predictable and more difficult to contest.
During the course of the pool stages both the top and bottom two teams as a
whole used the same delivery type an equal percentage of the time, as shown in
figure 4.12 and 4.13 the amount each delivery type is used is significantly close
with the top two teams using catch and drive 42% and the bottom two teams using
it 41% of the time, this also corresponds to the other delivery types with off the top
being used 40% of the time by the top two teams and 37% of the time by the
bottom two teams. Every team used at least three different variations of delivery
type during the course of the pool stages, as shown in the individual team analysis
of each team in figure 4.21. Three teams exceled themselves and used 5 different
delivery types, Catch and drive, Catch and give, Off the top, Quick lineout and
Long throw. These three teams, New Zealand, France and England were also
among the top four teams with the highest success rate during the pool stages.
After breaking down the delivery type of each team individually it becomes more
apparent that the dominant delivery type used was not the catch and drive (CAD),
although 9 out of the 16 teams involved did use this as their main option during
the pool stages. The off the top (OTT) attacking option was used by the other 7
teams as their number one attacking weapon. From the results gathered 1 team
used each the Catch and drive (CAD) and off the top (OTT) more than anyone
else, Georgia used the catch and drive (CAD) for 56% of their successful lineouts
whilst Russia used the off the top (OTT) option for 52% of their lineouts. Only one
team showed a relatively equal correlation between the amounts each delivery
type was used, South Africa, they used the Catch and drive 34%, Off the top 27%,
Catch and give 24% and the Quick lineout option 15% of the time. Field position
played a part in the decision to use each delivery type, teams with lineouts within
their own 22 meter line used the Catch And Drive option to give them more
chance of securing the ball, Off The Top delivery type was used more in the
attacking third of the pitch to give the teams a good attacking platform. Also,
teams losing during matches used lineout options to increase the tempo of the
game to give them an attacking platform instead of slow ball.
From the results gathered an interesting factor arose, the four teams from the top
two of each pool that used the off the top ball the most also made it the furthest
57
during the tournament, New Zealand, France, Australia and Wales used OTT over
43% of the time, Greenwood (2003) states that using off the top ball (OTT) allows
you to play a wide expansive quick game structure which could have let their
success, the other four teams that finished in the top two of each pool ,England,
Argentina, South Africa and Ireland used catch and drive as their main option, this
option slows the game down not giving the attack much tempo, this could have
been one of the factors leading to these teams getting knocked out in the quarter
final.
From the information displayed in figure 4.24 it is apparent that the top two teams
from each pool lost more lineouts against the teams that did not qualify from the
pool stages. Argentina lost 5 lineouts to Scotland and 4 to Georgia whilst not
losing a single lineout to England. Australia also lost more lineouts to the teams in
the bottom half of the table, they lost 4 lineouts to Russia who finished bottom, 1
to the USA and 1 to Italy. New Zealand lost their only two lineouts from the pool
stages to the team who finished bottom of their pool, Japan. On the other hand the
bottom two teams tended to lose more lineouts to the pool winners than any other
team, for example Georgia lost 7 out their 10 lineouts against England during their
encounter giving them a staggering 30% lineout success rate for that match.
Japan, the USA and Samoa also lost the highest percentage of their lineouts
against the team who won their group. Another interesting statistic arose from this
information was that some teams from the bottom of each pool had their highest
success rate when they played each other, the USA had a 100% lineout success
rate when they played Russia in their encounter, also Japan only lost 2 out of their
16 lineouts when they played Tonga and lost only 2 of their 12 lineouts against
Canada, comparing that to their game against New Zealand when they lost 4 out
of their 10 lineouts, giving Japan is much better success rate against teams
around them at the bottom half of their group. The differences from this section
between the top and bottom two teams are that the top teams tended to lose more
lineouts to the teams at the bottom of their pools, also the teams in the bottom half
of the pool tended to lose the highest percentage of their lineouts to the eventual
pool winners.
58
Figures 4.8 and 4.9 highlights the combined percentage that the top two and
bottom two teams from each pool used each lineout structure during the pool
stages. As shown in the pie charts the top two teams from each pool showed a
trend in variation in their use of their lineout structure throughout the pool stages,
using the full lineout 49% of the time, 5 man lineout 36% of the time, 6 man lineout
7% of the time, 4 man lineout 5% of the time and the 3 man lineout 3% of the time.
The bottom two teams from each pool tended to rely heavily on the full lineout
using this structure 63% of the time. Figure 4.23 shows how many times each
team used each lineout structure individually. As highlighted in the pie charts
every team involved in this study used the full lineout structure over 32% of the
time, two teams, France and Romania used the structure the most using it for over
75% of their lineouts throughout the pool stages. 63% of teams involved in this
study used the full lineout structure 50% of the time or more. The 5 man lineout
structure was used by every team 16% of the time or more, three teams used the
5 man lineout structure over 40% of the time during the pool stages, Australia
(50%), New Zealand (45%) and Argentina who used it 40% of the time.
59
CHAPTER SIX
CONCLUSION
6.0 Conclusion
The main focus of this study was to analyse and investigate the lineout actions of
the top two and bottom two teams of each Pool during the 2011 Rugby World
Cup. The main objective was to highlight any similarities between the top and
bottom teams in world rugby and then asking a further question does a successful
lineout lead to a winning team. The results gathered during this study provides
evidence that a link exists between having a successful lineout and having a
successful team.
In conclusion, the results from this study show a relatively big difference between
the top two teams and the bottom two teams from each pool throughout the pool
stages of the Rugby World Cup 2011. It was apparent that the top two teams of
the pool stages won most of their lineout possession winning 86% of all lineouts
while the bottom two teams only managed to win 75% of their overall lineouts
(figure 4.3 and 4.4). Nevertheless, remarkably the top two teams of each pool lost
more lineouts to the teams at the bottom of the pools, also the bottom teams of
each pool lost more lineouts to the pool winners. Therefore, showing an
agreement with Hypothesis 1.
Following the data gathered hypothesis 2 needs to be discussed. The top two
teams of each Pool strongly agreed with this hypothesis, do successful teams
employ a large variation in their delivery type to the less successful teams. A trend
occurred between the amount each delivery type was used by the top two teams
of each Pool and the bottom two teams of each Pool. The top two teams of each
pool tended to use a variation of delivery types which makes it hard for the
opposition to defend. The bottom two teams of each pool varied their delivery type
slightly but not as much as the top two teams of each pool, this made their lineouts
predictable and easy to defend. The bottom two teams tended to use the same
delivery type more consecutively than the top two teams of each Pool. Therefore,
Hypothesis 2 can be accepted.
During the course of the pool stages both the top and bottom two teams from each
Pool used similar delivery types an equal percentage of the time, as shown in
figure 4.12 and 4.13 the amount each delivery type is used is significantly close
with the top two teams using Catch and drive (CAD) 42% and the bottom two
60
teams using it 41% of the time, this also corresponds to the other delivery types
with Off the top (OTT) being used 40% of the time by the top two teams and 37%
of the time by the bottom two teams. Every team used at least three different
variations of delivery type during the course of the pool stages, as shown in the
individual team analysis of each team in figure 4.21. The field position of the
lineouts also played a big factor in the delivery type chosen, most teams when
defending within their 22m line tended to use the CAD option to secure the ball,
teams playing in the attacking third of the pitch tended to use the OTT option to
give them a stable attacking platform.
When considering the time frame that lineouts were lost during the matches, there
was a big difference in which quarter of the game lineouts were lost. The bottom
two teams lost more lineouts in the first and fourth quarter of each game, losing a
combined amount of 69% of their lineouts in these two quarters, whereas the top
two teams had more even results over the four quarters. Therefore, showing an
agreement with Hypothesis 3.
Similar results were produced between both the top two and bottom two teams of
each pool when focusing on the players used to lift in the lineout. Almost every
team involved in this study used every forward player (1 to 8) to lift over the course
of the pool stages, predominately using player 1 and 3, these two players were
used over 20% of the time, player 1 was used 26% of the time and player 3 used
24% of the time over the course of the Pool stages by all 16 teams involved in this
study. Another surprising result that cropped up was that England and Australia
used their second row player number 4, to lift almost double the amount of any
other player (figure 4.17). As a result of the teams not varying the lifters during the
lineout, Hypothesis 4, (pg2) cannot be accepted.
Focusing on the lineout area specifically is a very complex process which to be
successful needs to be done with efficiency throughout. Another vital step during
the lineout process is to frequently change the variation of jumper, lifters, zone
throwing too and also delivery type to keep the opposition always thinking and not
make your lineout predictable. In the modern day of rugby union the lineout is a
vital aspect of the game which can relate to being a successful team or not.
61
As there is a lack of published research specifically on the lineout process itself,
numerous studies based on this area could be conducted to offer additional
information and understanding into the difficult environment which is the lineout
process and its performance variables linking into lineout success. Studies looking
to focus on individual clubs over a prolonged time using the template created for
this study (figure 3.3) would open a pathway for coaches and players to gain
detailed analysis on their successful and unsuccessful lineouts.
Being able to analyse a variation of tournament e.g. the Six Nations, Tri Nations
and Churchill Cup etc. would deliver additional information to be analysed
regarding the lineout process between most of the teams involved in this study.
Analysing these extra tournaments would offer additional information on the
lineouts of the teams involved in this study to gather information and notice any
substantial differences between their performances in the biggest tournament of
them all, the World Cup and other tournaments or matches which are deemed not
as big. Also this would allow us to see if any differences arise between the options
teams used in certain countries, playing home or away and the different weather
conditions.
One or two recommendations to improve this study arose throughout conducting
and evaluating the process used, firstly the analysis conducted during this study
was done by hand notation system, to gain more in depth analysis, video analysis
systems could be used, video analysis would enable you to use video clips and
detailed statistics for each individual indicator, programmes such as Sports code
and Dartfish could be used. Another improvement would be to compare in more
detail lineouts from previous World Cups against each other to see if there is any
similarities between winning and losing teams and how they used the lineout and
to see if the teams lineouts have become better over time, also to see how any
changes in the rules of the lineout have effected its use.
62
REFERENCE LIST
Agnew, M, S, B. (2006) Game Analysis in Rugby Union. [Online]. Available
from: http://aut.researchgateway.ac.nz/handle/10292/30. [Accessed
05/12/2012].
Atkinson, G. (2003). Does size matter for sports performance researchers?
Journal of Sports Sciences, 21, 73-74.
Bartlett, R. (2001). Performance analysis: can bringing together biomechanics
and notational. International Journal of Performance Analysis in Sport. 1
(1), pp. 122-126(5).
Bartlett, R., Wheat, J., & Robins, M. (2007). Is movement variability important
for sports biomechanics? Sports Biomechanics, 6, 224–243.
Boddington, M and Lambert. M. (2004). Quantitative and Qualitative Evaluation
of Scoring Opportunities by South Africa in World Cup Rugby 2003.
International Journal of Performance Analysis in Sport. 2 (1), pp. 32-35
Brackenridge, L. and Alderson, G.J.K. (1985) Match Analysis. National
Coaching Foundation. White Line Press, pp.1-7.
Carter, A. and Potter, G. (2001). The 1995 World Cup Finals. Where does all
the time go? In Hughes, M. (Ed.) Notational Analysis of Sport III. UWIC,
Cardiff.
Franks. I.M. and Goodman. D. (1986). A systematic approach to analysing
sports performance. Journal of sports science, 4, 49-59.
George Giatsis and George Tzetzis,(2003). International Journal of PA in sport,
volume 3.
Greenwood. J. (1997). 4th ED, Think rugby, a guide to purposeful team play.
63
Greenwood. J. (2003). 5th ED, Fifteen man rugby for coach and player, Total
Rugby. A and C Black, London.
Hughes, M and Franks, I,M (2004). Notational analysis of sport. 2nd eition.
Great Britain: Routledge.
Hughes, M and Franks, I,M (2008). The essentials of performance analysis an
introduction. New York: Routledge.
Hughes, M. & Barlett, R. (2002). The use of performance indicators in
performance analysis. Journal of Sports Sciences, 20, 739-754.
Hughes, M. (2004). Notational analysis – a mathematical perspective..
International Journal of Performance Analysis in Sport. 2 (1), pp. 97139(43)
Hughes, M. and Bartlett, R. M. (2002). The use of performance indicators in
performance analysis. Journal of Sports Sciences, 20, pp. 739-754.
Hughes, M. and Franks, I.M. (1997). Notational Analysis of Sport. London: E &
FN.
Hughes, M.D. and White, P. (1997). An analysis of forward play in the 1991
rugby union World Cup for men. In Notational Analysis of Sport - I and II
(edited by M.D. Hughes), pp. 183-191. Cardiff: University of Wales
Institute, Cardiff.
Hughes, M.D., Evans, S. and Wells, J. (2001). Establishing normative profiles
in performance analysis. International Journal of Performance Analysis in
Sport, 1, a1-26.
Hughes. M. and Franks. I.M. (1997). Notational analysis of sport. 2nd edition.
System for better coaching and performance in sport.
64
Hunter, P. and O’Donoghue, P. (2001). A match analysis of the 1999 Rugby
Union World Cup. In Pass.com: Fifth World Congress of Performance
Analysis of Sport (edited by M.D. Hughes and I. Franks), pp. 85-90.
Cardiff: University of Wales Institute, Cardiff.
International Rugby Board (2003). RWC 2003: Statistical review and match
analysis (Accessed January 2nd, 2012) from:
http://www.irb.com/newsmedia/mediazone/gameanalysis/index.html22F8
1C38D/0/RWC_2003.pdf).
International Rugby Board Playing Charter. Laws of the Game of Rugby Union.
As Framed by the International Rugby Board. (2005 edition).
International Rugby Board. (2003). Review of the Game, Dublin: IRB Game
Analysis.
Jones, N.M.P., Mellalieu, S.D. & James, N. (2004). Team performance
indicators as a function of winning and losing in rugby union. International
Journal of Performance Analysis in Sports, 4, 61-71.
Journal of Human Kinetics volume 25 2010, 85‐91 Section III – Sport, Physical
Education & Recreation Performance in Team Sports: Identifying the
Keys to Success in Soccer
Laird, P and Lorimer, R. (2004). An examination of try scoring in rugby union: a
review of international rugby. International Journal of Performance
Analysis in Sport.. 1 (1), pp. 72-80(9)
Landis, J. R., Koch, G. G. (1977). The measurement of observer agreement for
categorical data. Biometrics 33:159-174.
Lim, E Lay,B Dawson, B Wallman, K and Aanderson, S. (2009). Development
of a player impact ranking matrix in Super 14 rugby union. International
Journal of Performance Analysis in Sport. 3 (1), pp. 354-367(14).
Long, R. and Hughes, M. (2004). Performance profiles of back row forwards in
elite men’s rugby union, before and after the introduction of
professionalism.
Lyle, J (2002). Sports coaching concepts. Oxon: Routledge.
65
Lyons. K. (1998). What is in a name? Are we all performance analysts?, Book
of Abstracts for the World Congress of Notational Analysis of Sport IV,
Porto, Portugal.
O’Donoghue, P. (2005). Normative Profiles of Sports Performance.
International Journal of Performance Analysis in Sport.. 1 (1), pp. 104119(16).
O’Donoghue, P. (2006). The use of feedback videos in sport.. International
Journal of Performance Analysis in Sport. 2 (1), pp. 1-14.
O’Donoghue, P. (2008). Principal Components Analysis in the selection of Key
Performance. International Journal of Performance Analysis in Sport. 3
(1), pp. 145-155(11)
O’Donoghue,P. and Hughes, M. (2004). Performance Analysis of Sport VI.
Cardiff, UWIC. pp 130-148.
Prim, S. Van Rooyen, M. Lambert, M. (2006). A comparison of performance
indicators between the four South African teams and the winners of the
2005 Super 12 Rugby competition. What separates top from bottom?.
International Journal of Performance Analysis in Sport. 2 (1), pp. 126133(8).
Sasaki, K Furukawa, T Murakami, J Shimozono, H Nagamatsu, M Miyao, M
Yamamoto, T Watanabe, I Yasugahira,H Saito,T Ueno,Y Katsuta, T and
Kono, I (2007). Scoring profiles and defense performance analysis in
Rugby Union. International Journal of Performance Analysis in Sport.
Sayers, M. (2004). A three-dimensional analysis of lineout throwing in rugby
union. Journal of Sports Sciences, 22, 498–499.
Tredwell. P.J. (1992). The predictive potential of match analysis systems for
rugby union football.
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APPENDECIES