CARDIFF METROPOLITAN UNIVERSITY Prifysgol Fetropolitan Caerdydd CARDIFF SCHOOL OF SPORT DEGREE OF BACHELOR OF SCIENCE (HONOURS) SPORT PERFORMANCE ANALYSIS 2015-6 A comparative assessment of elite level football: highlighting final third entries, 50:50 challenges and goalkeeper distributions (Dissertation submitted under the Performance Analysis of Sport area) Bradley Wood
A comparative assessment of elite level football: highlighting final third entries, 50:50 challenges and goalkeeper distributions
Cardiff Metropolitan University Prifysgol Fetropolitan Caerdydd Certificate of student By submitting this document, I certify that the whole of this work is the result of my individual effort, that all quotations from books and journals have been acknowledged, and that the word count given below is a true and accurate record of the words contained (omitting contents pages, acknowledgements, indices, tables, figures, plates, reference list and appendices). I further certify that the work was either deemed to not need ethical approval or was entirely within the ethical approval granted under the code entered below. Ethical approval code: 13/01/01L Word count: Name: Bradley Wood Date: 10/03/16 Certificate of Dissertation Supervisor responsible I am satisfied that this work is the result of the student s own effort and was either deemed to not need ethical approval (as indicated by 'exempt' above) or was entirely within the ethical approval granted under the code entered above. I have received dissertation verification information from this student. Name: Date: Notes: The University owns the right to reprint all or part of this document.
Table of contents Acknowledgements Abstract i ii CHAPTER ONE: INTRODUCTION 1 1.1 Introduction 2 1.2 Rationale of the Study 2 1.3 Aim of the Study 3 1.4 Null Hypothesis 3 1.5 Limitations 3 1.6 Delimitations 4 1.7 Glossary of terms 4 CHAPTER TWO: LITERATURE REVIEW 5 2.1 Performance Analysis in Sport 6 2.2 Analysis Methods 6 2.3 Match Analysis 8 2.4 Strategy and Tactics 9 2.5 Performance Indicators 12 2.5.1 Goal Scoring 12 2.5.2 Passing 14 2.5.3 Final Third Entries 15 2.5.4 Possession 16 2.5.5 Goalkeeper Distribution 18 2.5.6 50:50 Challenges 18 2.6 Literature Review Rationale 19 CHAPTER THREE: METHODS 20 3.1 Research Design 21 3.2 Sample 3.2.1 Justification of Sample 21
3.3 Operational Definitions 21 3.3.1 50:50 Challenge Definitions 22 3.3.2 Final Third Definitions 23 3.3.3 Goalkeeper Distribution Definitions 26 3.4 Computerised Notation System 27 3.5 Pilot Study 29 3.6 Procedure 29 3.7 Equipment 31 3.8 Reliability 31 3.9 Data Analysis 32 CHAPTER FOUR: RESULTS 33 4.1 Overview of Results 34 4.2 Goalkeeper Distributions 35 4.3 50:50 Challenges 37 4.4 Final Third Entries 37 CHAPTER FIVE: DISCUSSION 43 5.1 Introduction 44 5.2 Goalkeeper Distributions 44 5.3 Final Third Entries 45 5.4 50:50 Challenges 50 5.5 Limitations 51 5.6 Implications of Findings 52 CHAPTER SIX: CONCLUSION 53 6.1 Summary of Findings 54 6.2 Future Research 55 REFERENCES 56 List of Tables
Table Title Page No. 1 A basic hand notation tally sheet to record frequency 7 counts to create a success/failure index (Carling et al, 2009) 2 Wade s (1996) Principles of Team Play 10 3 Successful and Unsuccessful Chosen Sample 22 4 Operational Definitions for Location of 50:50 Win 22 5 Operational Definitions for Possession Origin Location 23 from resulting Final Third Entry 6 Operational Definitions for Possession Origin action from 24 Final Third Entry 7 Operational Definitions for Passing Sequences inside the 24 Final Third 8 Operational Definitions for Location of Final Third Entry 24 9 Operational Definitions for Performance and General 25 Outcomes 10 Operational Definitions for Goalkeeper Distribution Type 26 and Outcome 11 Percentage Agreement scores from Reliability Testing 32 12 Mean and Standard Deviation Overview of Results 34 List of Figures Figure Title Page No.
1 The Coaching Cycle Model (Carling et al. 2005) 9 2 Model of Tactics and Strategy (Hibbs and O Donoghue, 2013) 11 3 Pitch Layout to illustrate locations in which 50:50 Challenges 23 can be won 4 Location of Final Third Entry split into three zones 25 5 Model illustrating interlinking possibilities for selected 27 Performance Indicators 6 Code Window with activation and deactivation links 28 7 Analyst view in coding each game 28 8 Workflow of analysis events in the current study 29 9 A schematic workflow example for coding Final Third Entries 30 10 Mean Goalkeeper Short Release values 35 10.1 Mean Goalkeeper Short Releases that entered the Final Third 36 10.2 Mean Goalkeeper Long Release values 36 10.3 Mean Goalkeeper Long Release that entered the Final Third 36 11 Mean 50:50 Challenge Wins in each Pitch Zone 37 12 Mean Values for Final Third Entries alongside Location of Entry 38 12.1 Mean Values for Positive Outcomes per game in relation to 38 Final Third Entry Location 12.2 Percentage Mean Values of Final Third Location Entry 39 12.3 Mean Values for General Outcomes in Final Third Entries 40 12.4 Mean Value scores for Origin Location of Final Third Entry 40 12.5 Mean Values for Possession Origin Action in Final Third Entry 41 12.6 Pass Sequence frequency averages per game, per Final Third 42 Entry 12.7 Mean Values for Positive Outcomes for each Passing 42 Sequences List of Appendices
Appendix Title Page No. A Group standings for 2012 European Championships A1 B Mann Whitney U tests recovered from SPSS. B1 C Percentage Error Raw Calculations C1
Acknowledgements I d like to thank my supervisor Darrell Cobner, Family and Friends for their constant support and encouragement throughout the study. i
Abstract The purpose of the study was to examine performance variable differences between teams deemed successful and unsuccessful in matches (n=18) at the 2012 European Football Championships. The areas of performance were: final third entry, 50:50 challenges and goalkeeper distribution. These performance variables were further explored, looking at factors such as locations, types and outcomes. Through the use of StudioCode (Sportstec, Australia), a specific code window was created in order to capture events, post-event onto a timeline for later analysis. Percentage (%) error agreement was conducted to support the reliability of the study, alongside a pilot study. Operational definitions were included to diminish any uncertainty when coding events. With the use of a statistical window, independent and combined variable data was exported to Microsoft Excel and IBM SPSS 20 for further statistical analysis. Nonparametric Mann Whitney-U tests were conducted to compare the mean differences between the two independent mean samples: Successful and Unsuccessful. Successful teams displayed dominance in the majority of the performance variables. In favour of successful teams, significant differences (p<0.05) were found for short goalkeeper releases, 50:50 challenges in the middle third zone of the pitch, positive final third outcomes, and 4-5 or 6 plus passing sequences in the final third. Successful teams also showed statistical differences (p<0.2) in six other performance variables in comparison to unsuccessful teams. Unsuccessful teams only recorded one significant (p<0.05) result in their favour, which was for long goalkeeper releases. The main findings of the study suggest that successful teams consist of individual players with superior skill level, and show great variability when attacking, whilst maintaining a defensive structure that remains compact. Results also suggest a differentiation in playing styles, with successful teams indicative of possession based and slow build-up strategy, whereas unsuccessful teams are considered to have a direct approach to cover as much distance per pass. Limitations arose in the study as teams of various rankings competed against each-other. Future research into these variables could define the sample into those teams in the knock-out stages as average rank will be lower, allowing for a truer reflection of performance. ii
CHAPTER ONE INTRODUCTION 1
1.1 Introduction Played and watched by millions, football is considered a complex sport, requiring a repetition of various actions. In football, the interaction of tactical, technical, mental and physiological factors collaborate to define match performance (Drust, Atkinson and Rielly, 2007). Lanham (2005) stated that scoring and conceding goals are important performance indices in international/national professional standard football; the views of Hughes (2004) are aligned to Lanham s, stating that scoring and conceding goals coincide with many other variables to determine the outcome of performance. It can be argued that due to the nature of the sport, there are many more factors to take into account when assessing performance. The performance variables used in the current study are selected through a review of existing literature, and will assist in building an assessment of any potential trends that occur between successful and unsuccessful teams in the 2012 European Championship. It has been said that football is continuously evolving in nature, and if teams fail to rapidly adapt through certain strategies and tactics, they will be surpassed by opposing teams (Nelson, 1962). Whilst this statement was made over 50 years ago, strategy of play commands added importance in modern day football due to technological, coaching and training advancements (Tenga and Larson, 2003). 1.2 Rationale of the Study The competitiveness of football creates the need for new innovate tactics and strategies to combat opposition play, this is especially apparent in international football as teams have become increasingly defensive in essence (Nawrat and Hutchings, 1996; Hughes and Petit, 2001). The importance of attacking play in the final third has been illustrated in existing literature (Hughes and Snook, 2006; Tenga et al, 2010), which highlights the beneficial effects of goal scoring on match outcomes from final third positions. Possession play has been widely recognised as a determinant of success in modern-day football (Hughes and Churchill, 2004; Tenga and Sigmundstad, 2011). Whilst high levels of possession is considered as a contributor of success, the act of repossession should be regarded equally pivotal in a team s performance. In order to retain ball possession, low-risk passes are required in a 2
patient manner. Goalkeeper s distributions can be seen to influence the tempo and type of attack through their chosen method of release: short or long. Based upon the review of literature, performance indicators will be selected to assist in identifying and understand factors that contribute to a successful performance. 1.3 Aim of the Study The aim of this study is to conduct notational analysis to examine three main performance indicators between successful and unsuccessful teams in the 2012 European Championships. The study will investigate 18 games, looking specifically at final third entries, 50:50 challenges and goalkeeper distributions. With the findings of the study, results will be statistically compared to generate effective evaluative feedback that can influence tactics and playing styles in elite level competitions. 1.4 Null Hypothesis Based upon existing literature, the following hypothesis are included: H1 Successful teams will perform a higher number of final third entries in comparison with unsuccessful teams. H2 - Successful teams will perform a higher number of 50:50 challenge wins in comparison with unsuccessful teams. H3 - Successful teams will perform a higher number of short releases from goalkeepers in comparison with unsuccessful teams. 3
1.5 Limitations 1. Footage is not directly recorded by the researcher, and therefore is unable to use features such as the zoom and/or change camera angle. 2. Opposition effects should be considered when drawing conclusions form the analysis of a sample of performances (O Donoghue et al. 2008). Research states that trends are existent within performance variables when teams compete of different levels (e.g FIFA rankings). As resources are unavailable, opposition effects cannot be accurately analysed due to the various factors that contribute to performance. 1.6 Delimitations 1. As participants are all international level male football players, the data would not be entirely supportive for any external populations (women s, youth) or competitions. 1.7 Glossary of terms Performance indicator/key performance indicator (KPI) technical and/or tactical variables that define areas of performance Successful teams the four teams that reach the semi-finals: Portugal, Spain, Italy and Germany. Unsuccessful teams the four teams that finished bottom of each group: Sweden, Republic of Ireland, Netherlands and Poland Computerised Notation System A self-designed computerised system used to efficiently input data. 4
CHAPTER TWO LITERATURE REVIEW 5
2.1 Performance Analysis in Sport Performance analysis in sport is defined by O Donoghue (2010) as the supplement of objective feedback to a team/individual as a method of aiding the coaching process to further improve performance. The role of performance analysis within the coaching process is to provide quantitative reports of performance, and highlight areas of performance which require attention (O Donoghue and Mayes, 2013). The feedback engineered from the use of performance analysis can be quantitative through statistical representation of team/player performance; it can also be presented in a qualitative manner, using a video-format to provide technical, tactical, behavioural and physical aspects of performance (Carling et al., 2005). It has been said that notational analysis has focused upon three categories for performance analysis: general match indicators, tactical indicators and technical indicators (Hughes and Bartlett, 2002). The use of these categories allow an investigation of the technical aspects of performance through recording behaviour patterns and outcomes (Taylor et al. 2008). 2.2 Analysis Methods O Donoghue (2008) stated that real-time systems require performance indicators for output, and that it s necessary to have an optimal set of performance indicators to produce future, sufficient information to players and coaches to support the coaching process. Prior to technological advances and introduction of computerised systems, hand notation systems were the only known form of measurement for performance analysis. It is thought several early sporting notation researchers did not publish their work (Hughes and Franks, 2004), although, the first sport-specific notation system was devised by Messersmith and Corey (1931), whom explored movement patterns in Basketball. One of the most extensive examples of hand notation analysis, was the work of Reep and Benjamin (1968) and their 15 year analysis of world cup matches from 1953-1968. Hughes and Franks (2004) described three types of hand notation forms that can be used within a system for observational analysis: Scatter diagrams, 6
Frequency tables (Table 1) and Sequential systems. It is said that a system can include any or all of these forms of analysis to aid the coaching process and provide feedback for player/team development. Table 1. A basic hand notation tally sheet to record frequency counts to create a success/failure index (Carling et al, 2009) Successful actions Unsuccessful actions Tackle / / / / / / Header / / / / / Interception / Clearance / / / / Free kick (won/conceded) / / / Total 7 12 Computerised systems are now more common in performance analysis and offer a range of data analysis packages. Computerised systems are said to be the most effective way of creating an accomplished analysis system (Toledano et al., 2001). The advancement of technology has allowed observations to capture data with the use of camera equipment, and analyse performance in a frame-by-frame process using analysis software such as SportsCode, Dartfish, NacSport and many more. Advantages and disadvantages do exist for computerised notation; most notably, a computerised system can quickly generate statistical information within a click of a button. On the other hand, a computerised method may not be accessible to all levels of sport, due to its cost. Also, issues of system complexity can arise, leading to confusion in the coaching process. Both methods of analysis have their pros and cons, for example, some studies may be more suited for hand notation; Hughes and Wells (2002) conducted a study on penalty kicks, focusing on the approaches, placement and outcomes. The simplicity of this study would be well suited to a hand notation approach. Hughes (1993) acknowledges the accuracy and low-pricing advantages of a hand notation system, but also states that disadvantages do appear, highlighting that masses of data is 7
collected on paper, increasing the amount of time to process, hindering the coaching process. Computerised notational systems assist the match analysis process at two significant levels; data input and data output. Carling et al., (2009) identifies the advantages of computerised systems in comparison to manual hand notation systems: 1. Learning time is quicker and easier for inputting data. 2. Systems can be autonomous in providing indications of team and individual strengths and weaknesses, furthermore, proposing specifically adapted training methods. 3. Allow greater detail of data and advanced statistical analysis of performance. 4. Statistics can be combined with match analysis allowing immediate access to any moment of the game. 5. Systems can create quick and effective presentation of data (graphs). 2.3 Match Analysis Match analysis is used to provide feedback to players upon performance, and is extensively used in modern day football to better educate coaches (Ianiro, Lehmann- Willenbrock and Kauffeld, 2014), players (Tenga et al. 2010) and referees (Dawson and Dobson, 2010) of their performances. Hughes (1996) identifies the four main purposes of match analysis as: 1. Analysis of Movement measurement of velocities, time spent in different activities and individual work rates. 2. Technical Evaluation quantification and assessment of technical skill. 3. Tactical Evaluation assessment of and qualification of tactical skills in a particular game. 4. Statistical Compilation combination of both technical and tactical information for quantitative evaluation. 8
In football, match analysis is utilized to analyse, evaluate and prepare players and teams in their development. The use of match analysis enhances the scientific approach to the sport, providing a platform for coaches to quantify performances and aid development (Olsen and Larsen, 1997); performance is observed and analysed in order to influence and stimulate the development (Figure 1) (Carling et al, 2005). Patterns of play can be assessed through match analysis, with researchers highlighting the importance the understanding of how elite football teams play, for basis of implementing training and coaching strategies to increase chances of success (Garganta et al, 1997; Early, 2014). Figure 1. The Coaching Cycle Model (Carling et al. 2005) 2.4 Strategy and Tactics Wade (1996) proposed that a successful performance is acquired through effectively performing the three fundamental phases of play: Attack, Defence and Preparation (also known as midfield play). These three phases contribute to employ width, improvisation, mobility and support whilst attacking, in addition to delaying, concentrating and controlling the play whilst defending (Table 2). 9
Table 2. Wade (1996) principles of team play Attack Defence Penetration Width Mobility Improvisation Delay Concentration Balance Control/Restraint Depth (both phases) These fundamental phases are performed in alignment with specific tactical intentions in order to successfully execute phases of play. Teams will naturally adjust their intended playing style whilst remaining to execute these phases is a relevant nature (e.g width of attack in a 4-3-3 formation). Arguments have been made to the criterion of success in relation to strategies of play, with researchers stating that a direct play provides increased goal scoring opportunities (Reep and Benjamin, 1968; Bate, 1988). Whereas, a build-up play approach has also been linked to a successful performance (Yiannakos and Armatas, 2006; Castellano et al., 2012; Araya and Larkin, 2014). In contrast to Reep and Benjamin (1968) and Bate (1988), studies show that direct play is apparent more so in teams of a lower rank and lower player ability (Reep 1971; Hughes 1990; Olsen and Larsen, 1997; Hughes and Franks, 2005). It has been indicative that over-time, a possession based style of play has been commonly implemented by teams in more recent competitions by successful teams: at Euro 2000 (Hook and Hughes, 2001), Copa America 2001 (Hughes and Churchill, 2004), 2002 World Cup (Lawlor et al., 2004) and the 2010 World Cup (Prozone, 2010). Hughes and Franks (2005) concluded that despite supporting the views of a direct style of play, longer passing sequences possessed higher frequencies of shots per 1000 possessions. This statistic can be an encouraging determinant factor for styling of play, as shooting at goal is regarded as the most important feature of the game, to influence the match score (Jinsham et al, 1993). As a result, studies investigating this area of performance and playing styles, are indicating a shift away from the use of direct play at elite level football. 10
As strategic and tactical decisions are underpinned by various internal and external factors, Hibbs and O Donoghue (2013) proposed a model of tactics and strategy (Figure 2). The model includes strengths and weaknesses of individuals, and their opponents when observing behaviour patterns. Hibbs and O Donoghue (2013) state the importance of relating these two factors together as a relative weakness against one opponent may be a relative strength against another, therefore a balance has to be found. Figure 2. Model of Tactics and Strategy (Hibbs and O Donoghue, 2013) The proposed model incorporates situational variables that are apparent in affecting sports performance (Gomez et al, 2013; Bloomfield et al, 2005; Jones et al, 2004; O Donoghue, 2001; Sasaki et al, 1999). Assumptions have been made of home advantage in existing literature, with Jamieson (2010) conducting a meta-analysis on individual and team sports, providing evidence that home advantage does in fact exist. Whilst top level international competitions will only consist of one team commanding the home advantage, performance is still affected by situational variables in elite level 11
Basketball (Mexas et al, 2005), Football (Sainz de Baranda and Lopez Riquelme, 2012) and Rugby (Vaz et al, 2010). These authors highlight the importance of decision making in international competitions due to playing against the best players in the world, and should be informed by tactical options (Figure 2) built up from observations of behaviour. 2.5 Performance Indicators In a world where sport is continually developing, there is a need for new and innovate techniques to enhance and improve performance. Emphasis has been placed upon the use of technical specific support to aid the coaching process (James et al., 2005). The use of performance indicators in recording performance instances is seen as an effective method to gather reliable data, Hughes and Bartlett (2002) state that researchers should be focused upon the development of performance indicators to define performance. These indicators constitute a gold standard profile that can be used to predict future behaviour in a given sporting activity (O Donoghue, 2005). A performance indicator is an objectively measured performance variable or a combination of such performance variables (Hughes and Bartlett, 2002). Performance indicators and the influence of such on performance has been studied across a number of sports, including: Netball (O Donoghue et al., 2008), Handball (Oliveira et al., 2012), Basketball (Sampaio et al., 2010), Volleyball (Mesquita et al., 2011) and others. All of the studies established an interaction in which match situation and quality of opposition resulted in alterations in tactical and technical behaviours in order to succeed (O Donoghue et al., 2008; Oliviera et al., 2012; Sampaio et al., 2010; Mesquita et al., 2011). 2.5.1 Goal Scoring The primary objective in a game of football is to win the match, and in order to do so, a team must outscore the opposition. The creation of goal scoring opportunities and scoring goals is the pinnacle determinant of success, in which a broad review of literature has been conducted (Jones et al. 2004). The effectiveness of football strategies is mainly constituted by how goals are scored, and comparisons between 12
successful and unsuccessful teams (Reep and Benjamin, 1968; Carling et al., 2005; Hughes and Franks, 2005; Lawlor et al., 2004). Since Reep and Benjamin s (1968) ground-breaking longitudinal study, goal scoring in football has been extensively covered in literature. A number of studies (Partridge and Franks, 1989; Hughes and Franks, 2005; Reep and Benjamin, 1968) addressed that generating goal-scoring chances is an essential factor to actually scoring a goal. Supporting the importance of goal scoring in football, Mellalieu (2004) stated that it has received commodious attention from notational research as this act distinguishes success from defeat. It is claimed that goal scoring is influenced by two factors: the quality of the opportunities created, and the ability of the finisher (Tenga and Sigmundstad, 2011). Tenga and Sigmundstad (2011) conducted a 3 year study of the Norwegian Professional League, looking at how a sample of 997 goals were scored under four possession variables (type, passes per possession, possession duration and possession starting zone). Results shown that teams at the top end of the table scored more goals where possession starts in the midfield, in comparison to lower ranked teams. This could be an indication for increased numbers of interceptions, tackles and headers won in the middle third. The study concluded that the quality of opportunities created and ability of the finisher affects the act of goal scoring, for example, if the quality of opportunity is poor, and the ability of the finisher is poor, then the chance of scoring a goal will be significantly lower in comparison to a qualitycrafted opportunity, accumulated alongside a player with great finishing ability (Tenga and Sigmundstad, 2011). In a study of match statistics differentiations between successful and unsuccessful for world cup teams in 2002, 2006 and 2010, Castellano, Casamichana and Lago (2012) categorised and analysed two variables: attacking play, and defensive play. This multivariate analysis produced descriptive results and univariate differences between winning, drawing and losing teams over the three world cups. Shots-on-target commanded the most discriminatory power between winning and losing teams; This concluding statement can be seen as a reoccurring trend for some of Europe s top competitions: Spain (Lago-Ballesteros and Lago, 2010), Italy (Rampinini et al., 2009), 2002 World Cup (Lawlor et al., 2003). Hypothetically, a team that shoots more at goal will score more, but, studies into shooting variables alters this perspective (Szwarc, 13
2004; Yamanaka et al., 1993; Bishovets et al., 1993). Szwarc s (2004) study of the 2002 World Cup analysed variables as mean values through an effectiveness index, found that whilst there were no hugely significant difference in the number of actions, it was the effectiveness of them that differentiated winning and losing teams. Szwarc s (2004) results shown that on average over the 12 games, winning teams only recorded four more shots (n=18) than losing teams (n=14), although, the effectiveness of winning teams (14%) was over three times higher than losing teams (4%). 2.5.2 Passing The ability to pass is considered as one of the most important and relevant skills to a players performance (Olsen, 1988). Passing is a technical skill within football that contributes to the tactical intentions of a team. Many studies have been conducted to assess the technical effectiveness of passing sequences, and in particular, styles of play (Pollard et al. 1988; Scoulding et al. 2004). Ball retention (possession play) has generally been linked to greater overall team success (Hook and Hughes, 2001). Early studies (Reep and Benjamin, 1968; Bate 1988) investigated passing sequences of elite level competitions, and found similar results that 80% of goals were scored from 4 or fewer passes. Both studies conclude that an ideal performance should include a direct approach; covering as much of the pitch possible, per pass. Although these studies provide valid results, it can be argued that the studies are too simplistic to create a generic performance-enhancing hypothesis and require further technical evaluation. In a study of the 1990 and 1994 World Cup, Hughes and Franks (2005) assessed passing sequences of 116 games over the two tournaments. Findings of this study were distinctly similar to the results of Reep and Benjamin (1968); that 84% of goals in the 1990 competition derived from a team possession of four passes or fewer. Results for the 1994 competition showed a 4% decrease, with 80% of goals deriving from a team possession of four or fewer passes. Grant et al., (1999) found that successful teams (that reached the semi-finals) in the 1998 World Cup recorded more shots-on-target from passing sequences of four or more, as well as completing more passes on average per game than unsuccessful teams (eliminated from group stages). 14
A prime example for a modern day style of play is that of Spain s performance in the 2010 World Cup. As champions of the tournament, Spain recorded an average of 527 passes per game, which dominated the tournament average of 343. They also took the accolade for the highest passing success rate of 89% (Prozone, 2010). In conjunction with Hughes and Franks (2005) views that longer passing sequences per possession results in a higher shot count, as well as Jinsham et al s (1993) views that shooting at goal is perceived as the most influential factor upon match score; The new modern style of play performed by Spain, known as tiki taka, has commanded themselves as one of the greatest international football teams ever (Mitra, 2014). 2.5.3 Final Third Entries The whole idea of a direct style of play is to cover a high distance with few passes possible, with optimal accuracy. This is to get the ball into the attacking third of the pitch, aiming to score a goal. Research has gone into the area of effectiveness in the final third and its importance of executing physical and technical abilities within this area of the pitch. Ruiz-Ruiz et al., (2013) found a relationship between this variable and the performance of FC Barcelona in the 2004 2005 season. They concluded that the greater the difference between entries into the opponent's penalty area and entries into FC Barcelona's own penalty area, the better FC Barcelona performed. Interaction in the final third of the pitch is an area of sport that needs to be addressed as high importance as it is an offensive tactic with high potential goal scoring outcomes. Ruiz- Ruiz et al, (2013) supports Reep and Benjamin (1968) views of advancing possession into the attacking third of the pitch in order to influence the match score. Final third entries are seen as the most influential factor in generating goal scoring opportunities (Reep and Benjamin, 1968; Partridge and Franks, 1989; Hughes and Franks, 2005); in a study by Hook and Hughes (2001) on the 2000 European Championships, successful teams scored once every seven shots (ratio of 1:7) in comparison to unsuccessful teams of one every seventeen shots (ratio of 1:17). These findings support the work of Jankovic et al. (2011), which investigated successful attacks in the 2010 World Cup between successful and unsuccessful teams. Successful attacks were defined as those that resulted in either a shot-on-goal or a goal scored. Significant differences (p<0.05) were found in favour of successful teams. Similar results were found in analysis of the 2008 European Championship (Roxburg, 2008), 15
Italian Serie A (Rampinini et al, 2009) and the Greek super league (Armatas et al. 2009). These findings indicate that whilst a higher final third entry count results in a greater likelihood of scoring, the technical and tactical requirements are still a prerequisite for scoring goals and affecting match outcomes. 2.5.4 Possession Possession is thought of as central to success in modern football, but questions remain about its impact on goal scoring outcomes (Bate, 1988; Hughes and Franks, 2005; Pollard and Reep, 1997; Stanhope, 2001). Reep and Benjamin (1968) define possession as originating from the moment a team gains possession until the time that the team loses ball possession to the opponent. There is a wide opinion (Grant et al. 1999; Hook and Hughes, 2001) that possession football is related to a successful, winning performance; although, it s fair to say that ball retention allows for the defensive team to regroup, resulting in less space for the attacking team to play into. Charles Reep is credited to be the pioneer of notational analysis in football, having studied the influence of possession and passing on scoring goals. Reep and Benjamin (1968) produced very influential data to the world of football for possession and passing variables. Their findings went on to conclude that a more direct style of play could help teams to succeed, and is nowadays categorized as the long ball game, recognized by long balls being played from the back. The long ball strategy encourages the ball to enter the goal scoring positions of the pitch as often as possible, to increase the opportunities of scoring a goal (James, 2006). Twenty years on, Bate (1988) conducted a study on the 1982 World Cup; his findings agreed with Reep and Benjamin s (1968), with 79% of the 106 goals scored coming from 4 or fewer passes. Bate (1988) conducted further analysis of possession, by analysing 16 England International football matches. Results shown that 17 out of the 19 (89%) goals scored were from 4 or fewer passes. Whilst a lot of research has gone into the relationship of possession and scoring opportunities, there is less into the area of the possession origin. Hughes (1986) conducted a study on 16 international matches, assessing the outcomes of possession origins from the three thirds of the pitch (defence, midfield and attack). Findings showed an astonishing result that 9 times more goals were scored from possession originating in the attacking third than anywhere else on the 16
pitch. Bate (1988) supports these results by stating that an important factor in winning football matches is committing players into the attacking third to gain possession. In modern day football, European and world leading teams/nations tactics are not employed to what early research indicates for success. Hughes and Franks (2005) claim this is an indication that there are additional dimensions of play to be explored. Research by Grant et al., (1999) on the 1998 World Cup displayed a relationship between longer ball possession and success. Their study highlighted that teams with less intention for ball retention resulted in an unsuccessful performance. In a similar assessment of possession, Hook and Hughes (2001) looked at performances in the 2000 European championships; results were identical to that of Grant et al. (1999) stating that successful teams dominated possession levels in comparison to unsuccessful teams. Casamichana et al. (2011) conducted a multivariate analysis on the 2010 world cup to identify performance indicators that best discriminated between winning, drawing and losing teams. All 64 matches were analysed from the competition, results shown a significant difference (p<0.05) between ball possessions (%) for winning teams (52.4 ± 6.0*) compared to losing teams (47.8 ± 6.0). Harris and Reilly (1988) say that the attacking aim of a team should be to outnumber the opposition in crucial areas of the pitch, particularly in the final third as it provides attackers a better opportunity to score. Bate (1988) views are parallel to Jinsham et al., (1993) and Harris and Reilly (1988) by stating that playing possession football leads to less penetration to the oppositions final third. Situational variables such as the level of opposition can influence the amount of possession a team has; studies show that playing against stronger opposition leads to less possession (Lago, 2009; Bradley et al., 2014; Lago-Peñas et al., 2012; Taylor et al., 2008). The quality of the opposition viewed as the most important factor accountable for such variances in performance levels (McGarry and Franks, 1994). O Donoghue and Cullihane s (2011) views are adjacent to McGarry and Franks (1994), as they state that sports performance variables are unstable with opposition quality being the main source of player variability. 17
2.5.5 Goalkeeper Distribution Although the primary role of a goalkeeper has traditionally been to prevent conceding goals, new perspectives have been identified in which goalkeepers should look to use their position to their advantage by seeking positions in front of them to initiate fast and efficient attacking manoeuvers (Wade, 1998). In light of this statement, it can be argued that a direct approach would best suit a successful performance, surpassing as many opponents from the distribution as possible when initiating the attack. It can be said that a goalkeeper s role is also apparent as the first line of attack (Welsh, 1998). Brown (1993) studied the 1992 European Championships, looking specifically at goalkeeper s effectiveness in creating successful attacking manoeuvers. Results shown that teams such as Germany displayed a preference to distributing short releases, indicating a patient possession style of play. Although Germany reached the final with this style of play, these results are arguably invalid in modern day football, as the assessment of play was over 15 years ago, and styles of play have been known to evolve over time. In an altered approach by Wooster and Hughes (2001) on successful and unsuccessful goalkeepers in the 2000 European Championships, the findings suggest an underlying paradigm that incorporates the skill level of opposing teams, and variability of distributions. Results shown that successful teams goalkeepers mix up their distributions, whereas unsuccessful teams stay consistent in their approach, resulting in a form of predictability. Reiterating the fact that football strategies and tactics evolve over time, a perfect example of this is France s performances at the 2000 European Championships, in which their approach encompassed a patient build-up from the back from short releases. The France team won the 2000 competition, but failed to pass the first round of the 2002 World Cup. 2.5.6 50:50 Challenges 50:50 Challenges are associated with repossession actions (tackles, headers) in which both teams are challenging for where neither team commands ball possession. When considering a pitch is divided into three thirds: defensive, middle and attacking zones; it s been suggested that neither team controls the middle third of the pitch (Wade, 1996) due to phases of play such as goal kicks and defensive clearances. Whilst importance has been placed on possession in football (Reep and Benjamin, 1968; Hughes and Franks, 2004), the act of ball repossession is less documented. It 18
has been said that defensive teams are most vulnerable as soon as they lose the ball (Hughes, 1996) due to the time it takes for the team to restructure their formation to defend the incoming attack. As teams are most effective in the final thirds of the pitch, then the act of winning 50:50 balls in these areas should be deemed significantly influential on match score (Reep and Benjamin, 1968). 2.6 Literature Review Rationale From reading relevant existing literature around performance in football, and situational variables, it s evident that this affects levels of performance, and strategies implemented by different teams. When taking match location, status and quality of opposition into account, tactics and strategies are implemented to counter-act any strengths or weaknesses of the opponent in order to succeed. As previous literature has looked upon performance variables in football alongside successful and unsuccessful teams, some areas of performance have been overlooked more so than others such as Goalkeeper Distributions, 50:50 Challenges and Final Third Entries. For coaches to effectively implement training sessions based upon analysed observations, all aspects of performance need to be addressed to further understand determinants of success in football. Therefore, this study will look into group stage performances in the 2012 European Championships, specifically looking at the three variables previously mentioned that are overlooked in previous literature. 19
CHAPTER THREE METHODS 20
3.0 Research Design This study undertakes a post-event analysis of teams deemed successful and unsuccessful at the 2012 European Championships. A performance analysis system was implemented to observe, notate and analyse specific performance variables that may bridge an understanding of determinant factors that promote a successful performance in elite level football. Final third entry, Goalkeeper distribution and 50:50 challenges were the chosen performance indicators, under the pretence that these factors of performance are overlooked in academic literature and could potentially show an impact upon performance outcomes. The data obtained from this researched was then compared and related to previous literature on tactical and technical play in football at elite levels. 3.1 Sample Based on the sample size recommendations by Hughes et al. (2001), 8 teams from 18 matches in the 2012 European Championship group stage were observed and analysed. Spain, Italy, Germany and Portugal were deemed as successful, based upon the fact that they reached the semi-finals of the competition. Poland, Sweden, Netherlands and Republic of Ireland were the other 4 teams and were seen as unsuccessful as they finished bottom of their respective groups. Group-stage matches were selected under the basis that it would reflect a wider range of performance rather than assessing the latter stages of the competition. This was due to the increased external factors that come into play, such as quality of opposition, and more psychological pressures, which could alter the validity and accuracy of results. 3.1.1 Justification of sample Italy, Spain, Germany and Portugal were selected as the four successful teams as they reached the semi-finals of the competition. Sweden, Netherlands, Republic of Ireland and Poland were selected as the four unsuccessful teams as they finished bottom of their groups (Table 3). Full group standings can be found in Appendix A. 21
Table 3. Successful and Unsuccessful Chosen Sample Successful Teams Unsuccessful Teams Portugal Poland Spain Netherlands Germany Republic of Ireland Italy Sweden 3.2 Operational Definitions To organise the performance indicators correctly, operational definitions were used to ensure the accuracy of logging the events in matches and provide further reliability to the study. In accordance with O Donoghue (2007), rigorous operational definitions were applied to create a universal understanding of the variables used; these operational definitions were categorised and defined to provide clear and unambiguous views. The key performance indicators selected for the current study were: 1. 50:50 challenges 2. Final third entry 3. Goalkeeper distribution 3.2.1 50/50 Challenges: Act of ball repossession in which both teams are challenging for. Table 4. Operational Definitions for Location of 50:50 Win Performance Variable Operational Definition 50:50 Defensive Third Win 50:50 battle won in the defensive third zone of the pitch. 50:50 Middle Third Win 50:50 battle won in the middle third zone of the pitch. 50:50 Opposition Third Win 50:50 battle won in the opposition third zone of the pitch. 22
A visual representation of the three zones has been produced for further clarity (Figure 3). Figure 3: visual representation for pitch locations DEF 3RD MID 3RD OPP 3RD Figure 3. Pitch Layout to illustrate locations in which 50:50 Challenges can be won 3.2.2 Final Third Entry Whilst under control of the ball, the offensive team enters the oppositions defensive third of the pitch. Table 5. Operational Definitions for Possession Origin Location from resulting Final Third Entry Performance Variable Defensive Third Win Middle Third Win Opposition Third Win Operational Definition Possession obtained in the defensive third zone of the pitch. Possession obtained in the middle third zone of the pitch. Possession obtained in the opposition third zone of the pitch. 23
Table 6. Operational Definitions for Possession Origin action from Final Third Entry Performance Variable Operational Definition Goalkeeper Distribution Possession originates from goalkeeper distribution, being either a goal-kick, throw or pass. 50:50 Win Where the ball possession is switched via a tackle, interception, misplaced pass to the opponent. Turnover Where the ball possession is gained from a 50:50 challenge. Table 7. Operational Definitions for Passing Sequences inside the Final Third Performance Variable Operational Definition 0-1 0-1 passes inside the final third, result of an instant shot inside the final third. 2-3 2-3 attempted passes inside the final third. 4-5 4-5 attempted passes inside the final third. 6+ 6 or more attempted passes inside the final third. Table 8. Operational Definitions for Location of Final Third Entry Left Centre Right Performance Variable Operational Definition Entry into the final third is located in the left-third side of the pitch. Entry into the final third is located in the central-third of the pitch. Entry into the final third is located in the right-third side of the pitch. 24
For further clarification, a diagram (Figure 4) has been created to illustrate the three locations for final third entries Left Centre Right Figure 4. Location of Final Third Entry split into three zones Table 9. Operational Definitions for Performance and General Outcomes Goal Scored Shot-On-Target Exit Performance Variable Throw-in awarded Positive Neutral 25 Operational Definition Where a positive outcome derives from the final third entry, either a goal scored, or a shot-on-target. Considered a positive outcome, where the ball beats the goalkeeper, crossing the goal-line and awarding a goal to the offensive team. Considered a positive outcome, where the ball is fired on target, forcing a save from the goalkeeper. A neutral outcome from the final third entry, where the team is not in a better or worse position, either from a throw in, free kick, or corner. Considered a neutral outcome, where a team exits the final third showing no signs of attacking intent. Considered a neutral outcome, where a throw in is awarded to the offensive team.
Corner awarded Free-kick awarded Negative Shot-Off-Target Turnover Considered a neutral outcome, where a corner is awarded to the offensive team. Considered a neutral outcome, where a free kick is awarded to the offensive team. A negative outcome where the ball is turned over, or a shot-off-target is recorded. Considered a negative outcome, where the ball is struck goal-wards but misses the target, resulting in a turnover. Considered a negative outcome, where the ball is lost via a tackle, interception or misplaced pass. 3.2.3 Goalkeeper Distribution Table 10. Operational Definitions for Goalkeeper Distribution Type and Outcome Performance Variable Short Release Long Release Opposition Third Type Outcome Operational Definition Where the ball is released short, remaining in the defensive half of the pitch. Where the ball is released long, entering the oppositions half. When the ball enters the final third from the single possession of the goalkeeper distribution. 26
As the performance areas contain their own exclusive contents, there is the chance that they can overlap and interlink in certain phases of play. Figure 5 shows a created model to illustrate the interlinking nature between the areas of performance. An example of this is that the ball is won via a 50:50 challenge from the goalkeeper s distribution, and the ball ends up in the final third of the pitch. Final Third Entry 50:50 Win GK Distribution Figure 5. Model illustrating interlinking possibilities for selected Performance Indicators 3.3 Computerised Notation System The computerised system played a vital role in the data collection process, and therefore required great consideration when constructing its contents. First step was to identify the appropriate and necessary performance indicators to base the analysis. Once the indicators were selected, the system was created accordingly to ensure data was recorded correctly (Figure 6). When creating the system, the coding was driven by using assigned code buttons for the key performance areas: Final Third Entries, Goalkeeper Distribution, and 50:50 s (green diamond seen in figure). Labels were 27
assigned to all the internal variables to the performance indicators (blue dot seen in figure). Buttons were grouped in a sequential process from left to right, to provide a more efficient and easy collection process. Each label was categorised using a grouping variable to asses in later data processing. Figure 7 shows the analysts view when coding each game, with the code window, timeline and video on screen. Figure 6. Code Window with activation and deactivation links Figure 7. Analyst view in coding each game 28