A comparison between men s and women s elite football

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1 Cardiff School of Sport DISSERTATION ASSESSMENT PROFORMA: Empirical 1 Student name: Programme: Sophie Scherschel Student ID: SPE Dissertation title: Supervisor: A comparison between men s and women s elite football Adam Cullinane Comments Section Title and Abstract (5%) Title to include: A concise indication of the research question/problem. Abstract to include: A concise summary of the empirical study undertaken. Introduction and literature review (25%) To include: outline of context (theoretical/conceptual/applied) for the question; analysis of findings of previous related research including gaps in the literature and relevant contributions; logical flow to, and clear presentation of the research problem/ question; an indication of any research expectations, (i.e., hypotheses if applicable). Methods and Research Design (15%) To include: details of the research design and justification for the methods applied; participant details; comprehensive replicable protocol. Results and Analysis (15%) 2 To include: description and justification of data treatment/ data analysis procedures; appropriate presentation of analysed data within text and in tables or figures; description of critical findings. Discussion and Conclusions (30%) 2 To include: collation of information and ideas and evaluation of those ideas relative to the extant literature/concept/theory and research question/problem; adoption of a personal position on the study by linking and combining different elements of the data reported; discussion of the real-life impact of 1 This form should be used for both quantitative and qualitative dissertations. The descriptors associated with both quantitative and qualitative dissertations should be referred to by both students and markers. 2 There is scope within qualitative dissertations for the RESULTS and DISCUSSION sections to be presented as a combined section followed by an appropriate CONCLUSION. The mark distribution and criteria across these two sections should be aggregated in those circumstances.

2 your research findings for coaches and/or practitioners (i.e. practical implications); discussion of the limitations and a critical reflection of the approach/process adopted; and indication of potential improvements and future developments building on the study; and a conclusion which summarises the relationship between the research question and the major findings. Presentation (10%) To include: academic writing style; depth, scope and accuracy of referencing in the text and final reference list; clarity in organisation, formatting and visual presentation

3 CARDIFF METROPOLITAN UNIVERSITY Prifysgol Fetropolitan Caerdydd CARDIFF SCHOOL OF SPORT DEGREE OF BACHELOR OF SCIENCE (HONOURS) SPORT AND PHYSICAL EDUCATION A comparison between men s and women's elite football (Dissertation submitted under the discipline of Performance Analysis) Sophie Scherschel ST

4 A COMPARISON BETWEEN MEN S AND WOMEN S ELITE FOOTBALL

5 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). Word count: 8194 Name: Sophie Scherschel Date: 20/03/2014 Certificate of Dissertation Supervisor responsible I am satisfied that this work is the result of the student s own effort. 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.

6 Table of Contents Page No: Acknowledgements ABSTRACT i ii CHAPTER ONE: INTRODUCTION 1.1 Association Football Principles of Play Match Analysis Women s Football 2 CHAPTER TWO: LITERATURE 2.1 Performance analysis of sport Applications of Performance Analysis Performance Analysis within the Coaching Process Performance Indicators Performance analysis in football 7 CHAPTER THREE: METHOD 3.1 Research Design Matches used for analysis Performance Indicators 11 Comment [U1]: Need to add in the two additional matches for mens and womens? 3.4 Operational Definitions System Design (Template Design) Data Processing Reliability Data Analysis 22

7 Page No: CHAPTER 4: RESULTS 4.1 Possession Passing Shooting and crossing Challenges, errors and fouls committed 29 CHAPTER FIVE: DISCUSSION 5.1 Introduction Possession Origins of possession Passing Shooting Crossing Challenges, errors and fouls 34 CHAPTER SIX: CONCLUSION 6.1 Conclusion Recommendations for future research 37 REFERENCES 38 APPENDICIES APPENDIX A: Ethics Status APPENDIX B: Raw Data APPENDIX C: Statistical Testing

8 LIST OF TABLES Table Title Page No 1 Matches used for analysis 10 2 Possession origin operational definitions 12 3 Shootig operational definitions 12 4 Shot area operational definitions 13 5 Passing operational definitions 13 6 Crossing operational definitions 13 7 Final third entry operational definitions 14 8 Challenge operational definitions 14 9 Kappa strength of agreement measurement (Altman, 1991) Absolute Mean Difference of reliability test Mean and total passing sequences 26

9 LIST OF FIGURES Figure Title Page No 1 Performance analysis in a coaching context 6 2 Example of text label buttons 13 3 Example of code buttons 13 4 Activation link 13 5 Exclusive link 13 6 Draft sportscode template 16 7 Final Sportscode template 17 8 Activation links used in template 18 9 Matrix Organiser Reliability of performance indicators Reliability of passing Mean number of possessions per game Mean number and percentage of possession origin areas Percentage of possession origin Women s final third entries Men s final third entries Percentage of passing sequences Women s shot location Men s shot location Women s attempts on goal Men s attempts on goal Women s crossing type Men s crossing type Challenge type Mean number of errors Mean number of fouls 30 Comment [U2]: Insert Meyes et al Diagram here. Apologies it b

10 Acknowledgements I would like the thank the following people for their help, support and guidance throughout this study: Adam Cullinane for his expertise and support throughout the year. My parents for their emotional and financial support i

11 Abstract The vast range of men s performance analysis research available is utilised by elite football clubs throughout the world. The recent rise in women s participation has seen research increase however the differences between the two genders overall have not had a huge focus. Post event analysis of 10 matches (5 women and 5 men) from the 2012 London Olympics was undertaken including a range of national teams. Sportscode was used to record a range of performance indicators for both teams in each match. Reliability procedures conducted included an intra-observer test producing a kappa statistic which indicted all the performance indicators had a very good strength of agreement. The performance indicators recorded revealed a majority of similarities between the genders. The differences identified were within the possession origins, revealing two significant differences. The non-parametric Mann-Whitney U test revealed that men achieved significantly more possession origins from contests and free kicks (p<0.05). Non significant differences (p>0.05) were found within the following variable categories; possession, final third entries, challenges, errors, fouls committed, passing and attempts on goal. In conclusion the majority of performance indicators within the genders were found to not be significantly different. ii

12 CHAPTER ONE: INTRODUCTION 1.1 Association Football Association Football was established in 1863 (Reilly, 1996) and has since become the most popular sport in the world. Suggested reasons for its popularity include its attractiveness stemming from the freedom of movement and natural flow between attack and defense (Wade, 1996). Due to the heavy reliance on tactical performance within football the majority of literature is focused on tactical aspects of the game with a dearth of research within technical aspects. 1.2 Principles of Play The principles of play most widely referred to were proposed by Wade (1996), who states there are three principle phases within football; Attack, Defense and Preparation (also referred to as mid-field play). Within these the principles are split with attacking principles consisting of penetration, width, mobility and improvisation. Defensive principles include delay, concentration, balance and control/restraint. The principle of depth is found under both attacking and defending strategies. These principles suggested by Wade (1996) are necessary to underpin and support the systems of play and tactics implemented by coaches. Wade (1996) stresses the importance of fitting systems to players as opposed to forcing players to play in a certain way in which their creativity and technical ability is neglected. Wade (1996) also looks at the game of football from an individual perspective concluding performance is affected by individual skill and technique, understanding (intelligence), and mental and physical fitness. He advises that players should not underestimate each of these aspects as a player lacking in one will have an effect on the other two factors, establishing them as interdependent. 1.3 Match analysis Hughes and Bartlett (2008) found a common purpose of performance analysis stating they aim to improve performance by drawing lessons from previous performance. Match analysis is undertaken to provide coaches and players knowledge of performance, however a research and practice gap has been identified (Olsen and Larsen, 1997) and ways to be able to apply analysis undertaken to the coaching process are under transition. 1

13 Previous research is plenty in football due to its popularity with studies ranging from patterns of play (Bate, 1988) to specific incidents within matches such as penalty kick studies (Hughes and Wells, 2002). Most of the studies undertaken are of an applied nature based on observational research (Tenga, 2013, p 323) aiming to provide information about past performances (descriptive function) and also used to generate data as a predictive function. Significant amounts of research have been undertaken in Men s football and it has a long history of performance analysis (Reep and Benjamin, 1968) however in comparison the literature for the Women s game is severely lacking. 1.4 Women s Football A significant lack of research in the area of women s football highlights that this vital tool has not been utilised fully in both genders of the sport. Women s football has previously struggled in development compared to men s football, facing problems such as a ban from participation in 1921 (Fasting, 2006), which lasted until the early 1970 s. The ban was due to the FA feeling the popularity of female football becoming a threat to the masculinity of game (Williams, 2006). As the sport is quite young it lacks performance analysis research compared to the men s game especially. With the high numbers of participation and current growth rate in the popularity of the game there should be an increased need and demand for analysis of the female game. However the sport is still struggling in development for example the suspension of the women s professional soccer league in America in 2012 (ESPN, 2012). The competition the women s game faces from the men s can be it s downfall as seen for Santos FC Women s team who were forced into folding due to a lack of funding because the men s team wanted to keep Neymar, a young football star (LSE Blogs, 2012). 2

14 CHAPTER TWO: LITERATURE REVIEW 2.1 Performance analysis of sport Performance analysis is an essential part of modern day sport, its rise in use in recent years can be explained by the increase in research proving its benefits for improving performance. O Donoghue (2010) states it s an investigation of actual sports performance or performance in training, though its implementation varies widely depending on sport, situation and equipment available. Broadly, it is a process that can be used to aid the production of quantitative and qualitative information provided to coaches and athletes to enhance sports performance (Hughes, 2007). Interdisciplinary in nature, performance analysis can bring together multiple support mechanisms to become a bridge between coaches, athletes and sports scientists through effective communication (Sampaio, McGarry and O Donoghue, 2013). Traditionally, when asking coaches to recall events from a performance or game research identifies that they often don t remember or incorrectly remember events (Franks and Miller, 1986 and 1991). This is also supported by Laird and Waters (2008) who found UEFA-qualified coaches recalled 59 percent of critical events. This alone highlights the limitations of observational feedback and cements the need for performance analysis as a tool for improving performance in sport. Within the learning process athletes can gain intrinsic feedback from their performance of a skill but with performance analysis advances it is possible to provide extrinsic feedback through video footage. 2.2 Applications of Performance Analysis Hughes and Franks (2008) stated that the applications of performance analysis can be categorised as: Tactical evaluation Technical evaluation Analysis of movement Development of a database and modeling Educational use with coaches and players Tactical evaluation and analysis is an important and ever evolving application of performance analysis due to sports being played at a variety of different levels, by different genders and on different surfaces therefore not all aspects of tactics have been analysed at all levels and genders (O Donoghue, 2010). Tactical analysis involves looking at pace, 3 Comment [U3]: I would add a little more in here regarding tactical asspects of play and analysis, doesnt need to be specifically football.

15 space, fitness and movement and how performers use these to their advantage over their opponent. An example of this from within sport is within tennis where if a player has a perceived strength of fitness over their opponent then they will aim to create longer rallies to tire their opponent, looking at the shots-per-rally indicator can identify this. Technical evaluation can be undertaken, with the majority being biomechanical in nature to analyse movement patterns and psychological analysis of cognitive and experienced dimensions (Poizat et al. 2010). Qualitative analysis can also be through video feedback which has the potential to display an individuals performance compared to other athletes (Liebermann and Franks, 2004). Poizat, Séve, and Saury (2010) discuss the recent infiltration of qualitative research causing it to be difficult to distinguish between qualitative and quantitative studies. Technical evaluation is involved with the quality of skills and can be analysed using a quality rating similar to Hughes and Probert (2006) who analysed technical effectiveness in soccer using rating from -3 to +3. O Donoghue (2010) suggested further application of performance analysis also includes areas such as technical effectiveness, decision making and behavior/psychological assessment. Alongside this performance analysis should consider movement/physiological analysis as well, with the implementation of time motion analysis (TMA) and/or GPS. Time motion analysis is concerned with the analysis of movement and investigates player activity during competition, it seeks to develop understanding of physical and physiological requirements.. Greater understanding of work-rate and movement types is beneficial in the planning and design of training Programmes. Performance analysis is undertaken to be able to investigate the above areas, highlight necessary and significant factors in performance and then through a coaching process result in an improved performance. Professionally it is involved in tactical strategising, performance preparation, feedback mechanisms, and the formation of training interventions (Groom et al., 2011; Groom et al., 2012; Nelson & Groom, 2012; Nelson, Potrac, & Groom, 2011). Due to the extensive uses and applications of performance analysis in sport it is evident there is a specific role and need for a dedicated performance analyst within sporting teams and individual sports also. The main goal in performance analysis is to provide the coach appropriate information on player or team performance which will then be used to help plan the next practise, in order to improve performance (Lemmink and Frencken, 2013). Performance analysts are typically employed by professional organisations to provided 4

16 video and statistical support to players and coaches (Carling et al. 2005), however the application stretches beyond this wide range of uses not just for players and coaches. Greene (2008) suggests it is also used by high performance directors within the monitoring and assessment of athletes performance such as in the planning and structuring of training programmes. Wiltshire (2010) discusses the importance of undertaking analysis that will facilitate change and should have a clear outcome. He suggests high performance managers are in charge of this and can manage the improvement of performance by creating and nurturing self-sufficient athletes. As well as this in some sports replays of footage are used for judging such as figure skating, gymnastics and diving (O Donoghue, 2010). Furthermore, statistics produced from performance analysis processes are often used by the media to report on games or sports contests. 2.3 Performance Analysis within the Coaching Process Performance analysis allows for feedback to be given after performance which is key as the role of feedback is central in the performance improvement process (Hughes and Franks, 2008, p9). Feedback is one of the most important variables that affects learning and performance, Maslovat and Franks (2008) discuss the sources of feedback as intrinsic/inherent feedback and extrinsic feedback. Intrinsic feedback is formed from an athletes sensory sources such as sight and touch, often the more experienced an athlete the more detailed the feedback. Complimentary to this extrinsic feedback can be provided, typically from a coach who observes the performer with the aim to improve their skill level. Performance analysis is a tool that can be used by coaches to provide a more detailed level of feedback to individuals or teams. It is suggested that this will nullify any bias from the coach or inability to correctly recall events (O Donoghue and Mayes, 2013). Feedback can be provided in various ways, all of which have their advantages and potential fallbacks within the learning process. Demonstrations and instructions may result in an unintended strategy being conveyed due to individuals finding it difficult to extract the correct information from complex tasks (Hughes and Franks, 2004). Various models of feedback have been proposed in performance analysis literature including Winkler (1988), Franks (1997), and Mayes, O Donoghue, Garland, and Davidson (2009) with the role of feedback and how it is communicated developing as more research is undertaken and technology advancing such as video feedback and the use of internet within feedback. One of the most recent models in the athlete centered model be Mayes et al., (2009) which includes internet video streaming within the model and allows the players 5

17 to log on to an internet server and view the feedback, allowing them to reflect individually before collaborating with the coaches and rest of the team. Fig 1. Performance analysis in a coaching context The analysis of team sports is different from individual sport. There are a number of priority elements that are advised to be collected to improve team performance (Hughes and Franks, 2004). Franks et al. (1983) suggested these should be guided by coaching philosophy, primary objectives of the game and database of past games. Knowing how, when are where goals/points were scored, training can be tailored towards events that are most likely to happen. Comment [U4]: Insert Meyes et al Diagram here. Apologies it b 2.4 Performance Indicators A performance indicator is a selection, or combination, of action variables that aims to define some or all aspects of a performance. (Hughes and Bartlett, 2002, p739). They are selected by coaches to produce key information about their team. Hughes and Bartlett (2002) state that within invasion games there are four types of indicators: Match classification indicators, which are indicators that define and describe performance such as shots on and off target. Technical indicators are items such as accuracy in passing, and are used to assess technical competence. They should be normalised and applied in terms of total action frequency for example shots on target should be analysed with regards to total shots. The third type of performance indicators look to assess the importance of teamwork, pace, fitness and movement (Hughes and Bartlett, 2002, p748) examples include pace of attack and passing distribution. The analysis must look at failed attempts as well as successful attempts to judge fairly the effectiveness of a tactical 6

18 indicator. Finally biomechanical indicators which focus on the technique of a skill such as kicking in set pieces. Depending on the aim of a research project or a coach s specification the performance variables should be selected accordingly to produce the results required. For example an analysis of penalty kicks in football by Sforza et al., (1997) looked at the biomechanical indicators for their research whereas Analysis of goals scored in the 2006 World Cup (Acar et al., 2009) used tactical and technical indicators. 2.5 Performance analysis in football Charles Reep can be credited with undertaking the earliest forms of notational analysis research in association football (Pollard, 2002). Since then areas of research have included time motion analysis and physiological assessment (O Donoghue and Parker, 2001; Bloomfield, Polman, & O Donoghue, 2004). Noticeably, vast amounts of research have explored patterns of play, often assessed through the investigation of passing patterns, possession and goal scoring strategies (Hughes and Franks, 2005; James, Jones & Mellalieu, 2004; Scoulding, James and Taylor, 2004; Wright et al., 2011). Match analysis is used in various ways from evaluating patterns of play, analysing team and player performance and providing biomechanical feedback (Olsen and Larsen, 1997). The analysis of performance is an essential tool for coaches to use to improve performances in teams and also individual players. Within Mckenzie and Cushion s (2012) review, the dearth of research in PA that is applied in coaching is highlighted, alongside a theory-practice gap. They suggest the application of PA research is key and therefore future research must be transferable and appropriate to practice. Previously men s and women s football has been compared only several times in research. The majority of the research has been from a physical viewpoint as opposed to a tactical or technical viewpoint. Physically it has been suggested that women run a shorter overall distance during matches but at high intensities, and display fatigue in the second half more than men. Other suggestions are that women s matches tend to be slower due to anatomical limitations and also more attacking due to there being more space on the pitch as women are generally smaller in size. Although the men s and women s game is played under the same rules, previous research has found some differences between the two games. A time analysis of Men s and Women s soccer was completed by Miyamura, Seto and Kobayashi (1997). The focus of 7

19 the research was comparing the time variables of women s football at different levels, it was also compared to previous data gathered from the men s game. The aim was to help with the development of specific coaching and training programmes for women s soccer (Miyamura et al., 1997, p251). The comparison with the men s data lacked depth focusing on the comparison between women s football at different levels, however the findings showed women do not sustain passing moves as long as men, and men take longer to on average to restart after injury or goal. These findings were attributed to lower technical and movement skills of women, however the matches analysed were from tournaments before 1997 and it is likely that women s football would have advanced from 16 years ago therefore there is a gap in research for more modern and up to date analysis. Another study comparing men s and women s football focused on stoppages within games. The study by Siegle and Lames (2012) analysed which factors influenced number and length of stoppages in football and compared men s league and world cup games with women s league and world cup games. The findings were aimed to be used by coaches and referees but with no specific application was specified, the results have limited use and a limited furthering of knowledge. The main findings did show a difference between men s and women s football. The number of throw ins in the women s game was higher than in the men s games analysed, the authors discussed reasons being a difference in playing styles but stated a full explanation for this was difficult; therefore this highlights an area for further research. Another finding showed the length of time for kick offs was significantly more in men s football compared to women s due to the environment and the higher number of fans at men s games resulting in longer celebrations. This is good interpretation of results but has little practical application from a coach s point of view. Considering the range and depth of men s football performance analysis research available it leaves the question of whether this analysis has its use in the women s game. Recent research is available for the women s game such as Match activities and fatigue development of elite female soccer players at different levels of competition (Krustrup et al., 2009) and Analysis of actions ending with shots at goal in the Women s European Football Championship (England 2005) (Bergier et al., 2009). However unless compared to similar research in the men s game it is not possible to determine the differences and similarities between the two genders football play. A previous study that has compared levels of football but not gender includes Partridge et al., (1993) who undertook a comparison study of the 1990 world cup and the 1990 intercollegiate soccer tournament. They successfully statistically compared the two levels 8

20 of football and found significant differences within several areas of performance including crossing, possession loss, passing and completed passes. However no significant difference was found in shooting between the two levels. They applied their findings to coaching and suggested collegiate teams may not benefit from using world cup teams as a model for performance as the nature of collegiate play suggested it is too congested and compacted for this style of play. The application of this knowledge is a significant strength of this research and useful for future research, it also highlights the importance of this study. The performance indicators used by the researchers showed a wide range of technical and tactical elements allowing a well-rounded comparison of the two levels. Due to the lack of comparison between genders in previous research it is evident that this is an area for future research. Considering this insufficient amount of research, the purpose of this study will be to compare men s and women s football using selected performance indicators and asses the level of similarities and differences in the technical/tactical areas of match analysis. From the results there will be an indication of the level of appropriateness for transferring men s football research directly to the women s game. This will allow the ability to tailor men s and women s football coaching more specifically to the gender if the analysis proves this to be necessary. It has the potential to be implemented into how men s and women s tactics and training are carried out. 9

21 CHAPTER THREE: METHOD 3.1 Research Design A selection of men s (n=6) and women s (n=6) matches from the 2012 Olympic Games tournament were analysed using a post event analysis system. This give the researcher the opportunity to pause, rewind and re watch any of the game, reducing error within the data recording. The number of matches analysed is appropriate as Hughes, Evans and Wells (2001) suggest 6 matches are a reasonable number to represent performance. The performance indicators recorded were the same for all the matches, allowing a comparison between the men s and women s game. Mckenzie and Cushion (2013) suggest international tournaments are non-representative scenarios, with findings only applicable to that specific tournament. Acknowledging this, but also recognising the dearth of research offering comparisons between men s and women s football, using a major international tournament of this nature was suitable for this research. The computerised video analysis system SportsCode V8 (Sportstec, Australia) was used to collect the data as it speeds up the data collection process by allowing for easier data input through to data processing. Carling et al. (2005, p32) attributes this to user-friendly computer interfaces and advanced inputting tools. 3.2 Matches used for analysis Table 1. Matches used for analysis Comment [U5]: Need to add in the two additional matches for mens and womens? Men s Women s M1 Great Britain Vs Senegal (1:1) W1 Japan Vs Canada (2:1) M2 Mexico Vs South Korea (0:0) W2 Sweden Vs South Africa (4:1) M3 Brazil Vs Egypt (3:2) W3 Great Britain Vs New Zealand (1:0) M4 Spain Vs Japan (0:1) W4 Cameroon Vs Brazil (0:5) M5 Belarus Vs New Zealand (1:0) W5 Columbia Vs North Korea (0:2) The matches used in the analysis were selected from the group stages of the competition and were a representation of the mixed strength of the teams involved. The matches took place between the 25th August 2012 and 31st August 2012, in Cardiff, London, Coventry, Manchester or Glasgow. 10

22 3.3 Performance Indicators The performance indicators were selected after consultation from a number of sources, these included previous academic research and informal discussions with coaches of both the men s and women s football teams at the university. The combined knowledge from these coaches coupled with the game understanding and playing experience of the researcher aided the validity and scope of data collected. This allowed comparisons between men s and women s technical ability as well as tactical play and style of play. Dr Kerry Harris - Lecturer and Football Development Officer, BSc (Hons) Sports Coaching, MSc Sports Coaching, PhD and UEFA A License Candidate. Christian Edwards - Lecturer in Coaching Science, MSc Coaching Science, BSc (Hons) Sports Development, UEFA B Licensed Football Coach. As well as 4 full Welsh caps and a professional player for 14 years with Swansea City ( ), Nottingham Forest ( ) and Bristol Rovers ( ). The performance Indicators selected for the study were grouped under categories relating to: Possession (Number of possessions, length of possessions, origin and outcome). Passing sequences (Number of passes) Challenges (Aerial/Floor) Final Third Entries (Area of entry) Crossing (Deep/Short) Shooting (Success/attacking opportunities) Set Pieces (Type) 3.4 Operational Definitions Ideally the performance indicators used by the system operator should be defined with a level of precision that makes their meaning unambiguous (Williams, 2009) however this level of precision is often unrealistic. The variables were defined and understood by the researcher before undertaking the data recording. Table 2. Possession origin operational definitions 11

23 Possession Origin - The action that resulted in a change of possession between teams Operational Definition From Kick Off From Interception From Throw-In From Goal Kick From Turnover From Contest From Free Kick When the possession starts from kick-off either at the beginning of the game, half time or after a goal is scored When a player wins the ball by intercepting it from an oppositions pass When possession is started from a throw-in When the possession starts from a goal-kick When the ball is lose or given away to the other team When a player wins the ball by competing for it against the opposition When the possession starts from a free-kick Table 3. Shooting operational definitions Shooting - When a player attempts a shot on goal Operational Definition On Target Off Target Attacking Opportunity A shot on goal that either results in a goal or a save. A shot that results in a goal kick or hits any woodwork. An opportunity to score a goal that does not result in a shot. Table 4. Shot area operational definitions 12

24 Shot Area - The location on the pitch where the shot was attempted Operational Definition Inside Box Outside Box A shot taken within the 18-yard box. A shot taken anywhere outside the 18-yard box. Table 5. Passing operational definitions Passing - How the ball is transferred from one player to another. Hughes and Probert (2006). Operational Definition No pass recorded When no successful pass is completed 1-5 Successful passes between 1 and Successful passes between 6 and Successful passes between 11 and Successful passes over 16 Table 6. Crossing operational definitions Crossing - From wide areas when a player plays a lateral pass into the opposition penalty area to create a goal scoring opportunity. Operational Definition Deep When the ball is played into an area past the nearest post 13

25 Short Blocked When the ball is played into an area before the nearest post When the cross does not get past the defender Table 7. Final third entry operational definitions Final Third Entry When the ball successfully enters the attacking third of the pitch under control of the attacking team Operational Definition Left Middle Right Entrance into the final third of the attacking pitch on the left hand side Entrance into the final third of the attacking pitch through the middle Entrance into the final third of the attacking pitch on the right hand side Table 8. Challenge operational definitions Challenge When an attempt is made to win the ball off the opposition Operational Definition Aerial Floor Challenging to win possession of the ball in the air when a player is off the ground Challenging to win possession of the ball whilst on the ground 14

26 3.5 System Design (Template Design) The code window was designed using Sportscode (v.8) on an Apple imac computer. It was important to be able to capture each variable identified as performance indicators. For this to be achieved a variety of different buttons were created and programmed to work in different ways. Three types of buttons were used; Fig 2. Example of text label buttons Text label buttons (identified by a blue circle) were used to identify and activity that occurred such as possession origin, set piece, and crossing. Fig 3. Example of code buttons Code buttons (identified by a green diamond) were used to identify the type of challenge that had occurred. Fig 4. Activation link Activation links were created between buttons within the template for the actions that are linked. For example when the on target button was pressed this would automatically record an attempt on goal. Fig 5. Exclusive link Exclusive links ensure that two buttons cannot be one at the same time, these were used within the template within the possession zones to ensure as one zone is entered the other zone is turned off. A pilot study was conducted to ensure the template created was able to function correctly and collect the information intended. Pilot studies allow any unforeseen problems to be experienced and rectified before data collection commences ( O Donoghue, 2010, p. 142) therefore highlighting it s importance in this study. From the pilot study some minor errors were highlighted and changes were made. The categories for passing were adjusted as 15

27 the groupings were beyond the level of precision needed for this study, the categories went from six groupings cut down to four. Also a button was added for a possession origin coming from kick-off as this was previously omitted. Fig 6. Draft sportscode template 16

28 Fig 7. Final Sportscode template 17

29 Fig 8. Activation links used in template 18

30 3.6 Data Processing The data recorded was exported from the Sportscode software using Instance Frequency Reports and a Matrix Organiser (Fig 9.) Fig 9. Matrix Organiser 3.7 Reliability An intra-operator reliability test was undertaken to ensure the researcher could produce the same results on numerous occasions. An appropriate amount of time was left between recordings to lessen the possibility of retention of knowledge of the content of the footage (Davidson and Trewarth, 2008, p.5). The first half of Japan vs Morocco from the same tournament as the rest of the sample was analysed twice by the same operator and the kappa reliability test was used to test the two sets of data to determine the proportion of points that were agreed between the first and second occasions. The kappa statistic assesses the percentage of occasions where observers agree, and address the chance of agreement by guessing. The kappa scores were interpreted using Altman s (1991, p.404) strength of agreement measurement which shows is good and is very good. This measure was previously used in Medicine to assess the reliability of individual assessments. Considering this the results overall show the reliability of the system to be good, with four of the seven variables being very good. 19

31 Table 9. Kappa strength of agreement measurement (Altman, 1991) For assessing the variable number of passes it was appropriate to use the weighted version of kappa (Cohen, 1960), which considers the fact that there is a difference between errors in categorical data to errors in ordinal scale variables. In an ordinal scale the weighted kappa gives credit to neighboring values and is not as harsh as the unweighted kappa. Possession origin Attempt on goal outcome Attempt on goal area Set Piece Cross Final Third Entry Challenge Kappa Statistic Fig 10. Reliability of performance indicators 20

32 Passing Kappa Statistic Fig 11. Reliability of passing To test the reliability of the timing of the operator the absolute mean difference was calculated. The most significant differences occurred in the time difference between the time spent in each third of the pitch, with the middle third being the largest difference. Although it is quite a large difference it can be explained by the fact that the middle third has the option of the ball being transferred to both the attacking third or the defensive third. As well as this the differences in timing were affected by the camera views, as the footage is from television it involves close ups and replays which effect the view of the pitch and made it difficult to judge the zone and possession at times. Table 10. Absolute Mean Difference of reliability test ABS Dif (In Secs) Team_1 Def 71.1 Team_1 Mid 132 Team_1 Att Team_2 Def Team_2 Mid Team_2 Att Team_1 POSS 24.6 Team_2 POSS

33 3.8 Data Analysis The final data produced will be statistically tested using the Mann Whitney U Test, to compare the women s data with the men s data. From this significant differences will be analysed and reasons for these potential differences discussed. The similarities and differences between the two genders will allow for conclusions to be made into how far men s research can be applied in women s football, and potentially visa-versa. This will contribute to coaches as it opens up a whole range of research to use and allows knowledge of whether opposite genders can be used as a model of performance for teams. The tests are undertaken using SPSS 22.0 and the significant results are presented within the following section, the full testing data can be found in Appendix A. 22

34 Number of possessions CHAPTER 4: RESULTS The data collected is presented below in a serious of descriptive graphs, tables and figures. The range of performance indicators are displayed and explained as well as the results for each performance indicator being individually statistically tested. 4.1 Possession Women Men Fig 12. Mean number of possessions per game Fig 12 displays an overview of the mean number of overall possessions comparing women s and men s, it shows there are more overall possessions for women than men. Despite this the statistical testing found no significant difference (p>0.05) between the genders. WOMENS MENS % 54% 18% % 49% 22% Fig 13. Mean number and percentage of possession origin areas 23

35 Percentage Fig 13 shows the mean number of possessions for all the women s games analysed and all the men s games. This highlights small differences in the areas of possessions, with the largest difference being 5% more possessions gained in the middle third in the women s game although due to more possessions overall in the mens game there were still more possession origins in the middle third in the men s results (134 for men compared to 126 for women). Another difference highlighted from Fig 13 is that 4% more possessions were gained in the attacking third for men (60 for men and 41 for women). Despite these differences highlighted from the figure, the statistical testing showed no significant difference (p>0.05) From Contest From FK From GK From Intercepti on From KO From T/O From Throw In Women Men Fig 14. Percentage of possession origin Fig 14 compares the breakdown of origins of possession through percentage. It identifies some key differences in how possession is won between the genders. Contests and freekicks contribute to more of men s possession origins than womens with a significant differences found (p<0.05)., and there are also more possessions from goal kicks although this was not found to be significant statistically (p>0.05). The women s possession origins are higher than men from interception, kick off, turn overs and throw ins however no significant difference was found (p>0.05). 24

36 Percentage (%) 38% 36% 30% 28% 31% 36% Fig 15. Women s final third entries Fig 16. Men s final third entries Figures 15 and 16 show the percentage of final third entries in each area, either left middle or right. No significant differences were found between the location of final third entries, however the women s entries are highest on the left side of the pitch with 38% whereas the men s are split equally between left and right both with 36% No Pass Recorded P1-5 P6-10 P11-15 P Women Men Fig 17. Percentage of passing sequences 25

37 4.2 Passing Fig 17 demonstrates the percentage of passing sequences for both genders. The main differences indentified are the higher number of 1-5 passes for women and a higher percentage of longer passing sequences for men with the 16+ bracket being larger. All of the passing sequences were not significantly different (p>0.05). Table 11. Mean and total passing sequences No Pass P1-5 P6-10 P11-15 P16+ Recorded W MEAN W TOTAL M MEAN M TOTAL Fig 19. Men s shot location 26 60% 40% Total = 96 Mean = 10 Fig 18. Women s shot location 46% 54% Total = 134 Mean = 13

38 49% 51% Off Target Total = 35 Mean = 4 On Target Total = 37 Mean = 4 Fig 20. Women s attempts on goal 49% 51% Off Target Total = 51 Mean = 5 Fig 21. Men s attempts on goal On Target Total = 53 Mean = 5 27

39 4.3 Shooting and crossing From Fig 18 and Fig 19 it is observable that there are more mean attempts on goal per game for men although this difference is not significant (p>0.05). As well as this there is a larger percentage of shots from within the 18 yard box for women with 60 percent, compared to the mens 46 percent, again no significant difference was found. The results from the percentage of shots on and off target shown in Fig 20 and Fig 21 were the same for both the women and men. Similarly the percentage type of cross was the same for both genders as seen in Fig 22 and Fig 23. No significant differences were found, although differences can be identified from descriptive results in the mean per game between the genders with women having a higher mean of blocked crosses and men having a higher number of deep and short crosses. Blocked 13% Short 18% Deep 69% Deep Short Blocked Mean Total Fig 22. Woen s crossing type 28

40 Blocked 13% Short 18% Deep 69% Deep Short Blocked Fig Mean 23. Men s 11.9 crossing type Total Challenges, Errors and Fouls There is only a minor difference between the types of challenge in relation to the gender shown by Fig 24. The mean averages for women were 25 floor challenges compared to the men s 24 floor challenges showing a difference of 1. Similarly with aerial challenges which showed the women s mean to 35 and the men s one higher at 36. Neither of these showing a statistical significant difference (p>0.05) in the Mann Whitney U test. A difference between the numbers of errors per game is evident where errors are shown to be higher for women at a mean of 13 and men showing a mean of 11. Oppositely the mean number of fouls was higher for men at 11 compared to women with 8. 29

41 Mean number of fouls Mean number of Errors 100% 90% 80% Floor Floor 70% 60% 50% 40% 30% Ariel Ariel 20% 10% 0% Women Men Floor Ariel Fig 24. Challenge type Women Men Fig 25. Mean number of errors Women Men Fig 26. Mean number of fouls 30

42 CHAPTER FIVE: DISCUSSION 5.1 Introduction The aim of the study was to determine the similarities and differences between Men s and Women s elite level football and identify any significant differences between the genders. To achieve this a variety of performance indicators were recorded to give a general overview of the matches. The results presented will be discussed in the following section with an explanation for the identified similarities and differences. 5.2 Possession Fig 12 shows the number of overall possessions on average for the women s and men s matches analysed. Overall women had a higher number of possessions, suggesting that the ball was turned over between the teams more frequently. Reasons for this could be due to a lower overall technical ability in the women s game and men having longer possessions due to better movement and technical skill. These findings would be supported by previous research by Miyamura, Seto and Kobayashi (1995) who found that lower technical ability in females resulted in shorter possessions. Similarly in a study by Partridge, Mosher and Franks (2008) which compared elite football to collegiate football, they found the lower technical ability of the collegiate players resulted in more frequent possession changes. The area of the pitch where possession is won can be significant in terms of scoring goals. The ability to win the ball back in the attacking third has been shown to be of importance in winning games (Miller, 1994). In the present investigation it was found men gained 22% of their possession in the attacking third with women winning 18% comparatively. This demonstrates the tactical advances within the male game as it indicates the teams were applying pressure as far up the field as possible, which is a strategy claimed by Hughes (1990) to be very effective. This is supported by Bate (1988) who found that 50-60% of all movements leading to shots on goal originated in the attacking third. More recently Acar et al. analysed the goals from the 2006 world cup and concluded 54% (79 goals) of the goals scored were from 4 or less passes. A higher number of entries in to the final third proves better tactical and technical awareness of the game, to increase this coaches should look to encourage playing the ball forward as often as possible, reducing square and backwards passes and playing the ball into space behind defenders as early as possible (Bate, 1987). 31

43 Entering the final third is of high importance within football as this is where the majority of goals are scored. Fig 15 and Fig 16 show the percentage of where the teams entered the attacking third of the pitch. Overall the women entered using the wide areas 69% of the time, whereas men used the wide channels 72%. The use of width is a principle of play used to create gaps in oppositions defence when they are heavily concentrated (Wade, 1996) therefore the higher use of width by the men s team suggests this could be a tactical advancement in the male game. The male players could be encouraged to use the wings, as they know its advantages in attacking play. 5.3 Origins of possession The origins of possession for the two genders found some significant differences (p<0.05). Firstly possession was gained by men through contesting more than women (28±5.9 for women compared to 40±7.2 for men). This signifies that the men are more physical and successful in their attempts to win the ball. Another reason is that due to a suggested higher technical ability men are not losing possession from errors such as misplaced passes but instead through good defending and tackling from the opposing team. Possessions from free kicks also showed a significant difference with the women s mean at 2±1.5 and the men s mean at 5±2.4. Reasons for these differences stems from the fact that men commit more fouls than women due to the physicality of their style of play which in turn rises from their anatomical differences. No significant differences were found in the remaining possession origins showing similarities in the number of possessions gained from goal kicks, interceptions, kick off, turnovers and throw-ins. Despite this the minor differences found can be explained through technical and tactical differences between the genders. More interceptions were recorded in the women s matches than men s being the result of potential poor passes by individuals or better predicting where the ball will be played. This result indicates a better tactical knowledge from women. A larger number of possessions started from kick-off in the women s game simply due to more goals being scored ad the game having to restart from a kick-off. The higher number of goals has some indication towards the quality of shots as well as the quality of goalkeepers. It may be that the women scored more because they were better at shooting or potentially due to less technically gifted goal keepers, this can not be concluded from this study but is an area for future research. 32