- Determine the purpose and structure of the process analysis essay.
- Understand how to write a process analysis essay.
The Purpose of Process Analysis in Writing
The purpose of a process analysis essay is to explain how to do something or how something works. In either case, the formula for a process analysis essay remains the same. The process is articulated into clear, definitive steps.
Almost everything we do involves following a step-by-step process. From riding a bike as children to learning various jobs as adults, we initially needed instructions to effectively execute the task. Likewise, we have likely had to instruct others, so we know how important good directions are—and how frustrating it is when they are poorly put together.
Writing at Work
The next time you have to explain a process to someone at work, be mindful of how clearly you articulate each step. Strong communication skills are critical for workplace satisfaction and advancement. Effective process analysis plays a critical role in developing that skill set.
On a separate sheet of paper, make a bulleted list of all the steps that you feel would be required to clearly illustrate three of the following four processes:
- Tying a shoelace
- Parallel parking
- Planning a successful first date
- Being an effective communicator
The Structure of a Process Analysis Essay
The process analysis essay opens with a discussion of the process and a thesis statement that states the goal of the process.
The organization of a process analysis essay typically follows chronological order. The steps of the process are conveyed in the order in which they usually occur. Body paragraphs will be constructed based on these steps. If a particular step is complicated and needs a lot of explaining, then it will likely take up a paragraph on its own. But if a series of simple steps is easier to understand, then the steps can be grouped into a single paragraph.
The time transition phrases covered in the Narration and Illustration sections are also helpful in organizing process analysis essays (see Table 10.1 “Transition Words and Phrases for Expressing Time” and Table 10.2 “Phrases of Illustration”). Words such as first, second, third, next, and finally are helpful cues to orient reader and organize the content of essay.
Always have someone else read your process analysis to make sure it makes sense. Once we get too close to a subject, it is difficult to determine how clearly an idea is coming across. Having a friend or coworker read it over will serve as a good way to troubleshoot any confusing spots.
Choose two of the lists you created in Note 10.52 “Exercise 1” and start writing out the processes in paragraph form. Try to construct paragraphs based on the complexity of each step. For complicated steps, dedicate an entire paragraph. If less complicated steps fall in succession, group them into a single paragraph.
Writing a Process Analysis Essay
Choose a topic that is interesting, is relatively complex, and can be explained in a series of steps. As with other rhetorical writing modes, choose a process that you know well so that you can more easily describe the finer details about each step in the process. Your thesis statement should come at the end of your introduction, and it should state the final outcome of the process you are describing.
Body paragraphs are composed of the steps in the process. Each step should be expressed using strong details and clear examples. Use time transition phrases to help organize steps in the process and to orient readers. The conclusion should thoroughly describe the result of the process described in the body paragraphs. See Chapter 15 “Readings: Examples of Essays” to read an example of a process analysis essay.
Choose one of the expanded lists from Note 10.54 “Exercise 2”. Construct a full process analysis essay from the work you have already done. That means adding an engaging introduction, a clear thesis, time transition phrases, body paragraphs, and a solid conclusion.
- A process analysis essay explains how to do something, how something works, or both.
- The process analysis essay opens with a discussion of the process and a thesis statement that states the outcome of the process.
- The organization of a process analysis essay typically follows a chronological sequence.
- Time transition phrases are particularly helpful in process analysis essays to organize steps and orient reader.
This is a derivative of Writing for Success by a publisher who has requested that they and the original author not receive attribution, originally released and is used under CC BY-NC-SA. This work, unless otherwise expressly stated, is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
What is performance analysis?
O’Donoghue (2010) defines performance analysis as the investigation of actual sports performance, with the aim being to develop an understanding of sports that can inform decision-making, enhance performance and inform the coaching process (Hodges and Franks, 2002). Within a professional football context, performance analysis has a number of applications, predominantly concerned with tactical and technical evaluation, movement analysis, databasing and modelling and coach and player education (Carling et al., 2005). The volume of information that can be generated via performance analysis has many implications for enhancing the coaching process (Lyle, 2002; Smith et al., 2005).
The need for performance analysis
The coaching process (as illustrated in Figure 1.) is an on-going cycle of performance and practice, within which a coach is required to evaluate, intervene, and feedback information to performers with the ultimate aim of enhancing future performance (Carling et al., 2005; Hughes and Bartlett, 2008). Within this coaching process, feedback is of critical importance if player and team performance is to improve (Carling et al., 2005). Traditionally the feedback process has been based upon a coach’s subjective observation of performance, which can be influenced by bias, emotion and previous experiences (Hughes and Bartlett, 2008). A subjective observation process is known to be unreliable and inaccurate, since even experienced football coaches have been shown to be able to recall just 59.2% of the critical events occurring during 45 minutes of football performance (Laird and Waters, 2008). this lack of accurate recall ability can lead to ‘highlighting’, where a coach’s perception of performance becomes distorted by those events that they can remember (Hughes and Bartlett, 2008). Ultimately this results in a lack of accuracy within both coaching feedback and decision-making, which can be improved with the use of objective, unbiased and comprehensive information performance analysis is capable of providing (James, 2006; Hughes and Bartlett, 2008).
Enhancing feedback with performance analysis
Accurate and timely feedback is critical within the coaching process in professional sporting environments and has driven the uptake of performance analysis systems (Guadagnoli, 2002; McGarry and Franks, 2003; Groom and Cushion, 2011). Two-dimensional video-analysis systems enable both player and coach to review performance numerous times after the event, reducing observer bias and increasing the quality and accuracy of information, as well as providing numerous options for feedback provision (Ives et al., 2002; Stratton et al., 2004; Hughes and Bartlett, 2008). Performance analysis feedback may be quantitative through the application of statistical analysis of team and player performance, or qualitative through the use of video and relate to technical (passing, shooting, heading etc), tactical, behavioural (‘game sense’, decision-making, concentration, emotional state) and physical (movement, work-rate) aspects of performance (Carling et al., 2005). However the effect of feedback may not always be positive and player skill level must be considered. To facilitate improvements in performance, skilled players require more detailed feedback than those less skilled, however there is a balancing act, since if feedback is too detailed performance can be negatively affected (Hughes and Franks, 2004). Skill level and experience also influences a player’s ability to interpret two-dimensional video feedback as a three-dimensional image, with more experienced players better able to do so (Hughes and Franks, 2008).
Timing of feedback
Data and video can be collated on opponents to highlight areas of strength and weakness in all aspects of the game to provide a comprehensive picture of what can be expected in upcoming matches (Carling et al., 2005). This not only prepares the players but allows the coach to formulate a strategy to counteract the opposition and exploit their weaknesses, which can be worked on in training prior to the match. Some teams will also analyse training session to assess the effectiveness of aspects of performance being tested in training (such as set pieces, different formations etc) and evaluate behavioural aspects (such as attitude and commitment)(Carling et al. 2005), which can influence team selection.
Contemporary performance analysis systems allow matches to be coded live, with statistical information and specific video instances shared between devices for review by coaches in real-time, and players at half-time. Whilst the Football League rules prohibit the streaming of video instances directly to the technical area, instances can be streamed elsewhere within the stadium. One such method could utilise Apple devices to create a wireless network and stream footage and statistical outputs to an iPad in the stands, which is then reviewed by a coach prior to giving a half-time team talk. Alternatively an analyst could go to the dressing room and show a coach clips and stats in person at half-time. Such processes provide a coach with objective information to inform in-game decision-making.
A lot of time is devoted to analysis after a match has been played in order to review team and individual performance in detail, evaluate performance and plan future training (Carling et al., 2005). Post-match analysis feedback sessions should play an integral role in the coaching process (Thelwell, 2005) although care must be taken to ensure the process is integrated rather than detracting form the time spent training (Gasston, 2004).
Wider integrated sports science support
Whilst the coaching culture within professional football has traditionally been cautious towards the sports sciences, the contemporary environment has become more welcoming with the implementation of a more systematic, multi-disciplinary approach as the value added by sports science support becomes increasingly clear (Reilly, 2006). Football clubs at the elite level will typically employ the service of physiologists, psychologists, nutritionists and performance analysts, although the structure of sports science support is not uniform between clubs (Reilly, 2006). The sports sciences play an important role in improving sports performance, informing critical features of the coaching process such as devising training sessions and monitoring performance (Maille, 1999), and whilst performance analysis typically focuses on the tactical and technical element of team sport performance (Hughes and Bartlett, 2002), it also has implications for wider sports science support, contributing vital information to other sports science disciplines (Maille, 1999).
Performance analysis can contribute to the medical department via movement analysis to detect injury mechanisms and identify injury risk factors in players. The overall risk of injury to professional footballers has been reported to be approximately 1,000 times greater than for high-risk industrial occupations (Drawer and Fuller, 2002), which is reflected in the increasing relevance given to two and three-dimensional technique analysis for injury prevention (Bartlett, 1999). Typically functional movement screening occurs during pre-season with posture, gait, muscle length and joint flexibility, neuromuscular assessment and functional-specific testing being carried out (Spurrier, 2012), supplemented by video and annotated images for feedback if technique analysis software is applied. The screening of older players can allow them to prolong their careers, whilst the screening of younger players can identify issues caused by developmental changes that can predispose them to injury. The application of analysis software within injury prevention screening can assist medical staff in identifying risk factors and developing performance plans in collaboration with a strength and conditioning coach to correct any issues. Such performance plans based upon injury screening feedback have been implemented with positive results (Hewett et al., 1997; Hewett et al., 2005; Soligard et al., 2008).
Strength and Conditioning
Player tracking systems such as Prozone 3 can collect physical data, including distance covered, number of sprints and high-intensity distance covered (Figure 2.), indicating the demands of match play which strength and conditioning can use to devise individualised training schedules preparing players for these demands (Reilly, 2007; Carling et al., 2009). The detail provided by these systems allows the identification of position specific demands and the factors that can influence variability in work-rate profiles between players of the same position, such as fatigue (Mohr et al., 2003; 2004; 2005; Krustrup et al., 2006; Reilly, 2007), quality of opposition (Rampinini et al., 2007), playing style (Rienzi et al., 2000; Reilly, 2003; Carling et al., 2008), environmental conditions (Ekblom, 1986; Reilly, 2003) and game state (O’Donoghue and Tenga, 2001; Redwood-Brown, 2008).
Furthermore, a longitudinal evaluation of physical data may reveal a trend of deteriorating physical performance in the latter stages of matches, indicating a training need (Carling et al., 2009) or injury risk (Carling et al., 2008). In the case of injury risk, physical data may indicate inadequate recovery time between games, or overtraining. An example of physical data influencing decision-making could be seen in Arsene Wenger’s regular substitution of Dennis Bergkamp in the last twenty minutes of matches during the 2002 English Premier League season, which was based on physical data that indicated the player was performing An example of physical data influencing decision-making could be seen in Arsene Wenger’s regular substitution of Dennis Bergkamp in the last twenty minutes of matches during the 2002 English Premier League season, which was based on physical data that indicated the player was performing fewer high-intensity activities after the 70th minute of matches (Kuper, 2011).
Training loads can also be monitored, using GPS devices or electronic tracking systems that can collect data relating to position, time, speed and heart rate in real-time (Di Salvo et al., 2006; Edgecomb and Norton, 2006; Carling et al., 2008; GPSports, 2011). The information provided allows the coach to adjust volume and intensity for individual players in real-time based on the information available; ensuring the training goal of the session is achieved in terms of the energy systems being stressed. In the case of players returning from injury, benchmark figures based on their pre-injury training performance can be used to determine when they have recovered sufficiently to be considered for selection (Carling et al., 2008).
Video feedback can be used to evaluate psychological aspects of performance such as attitude, commitment or errors of attentional focus, which can be shown to a team or individuals to assist a sport psychologist in advising players on psychological skills (O’Donoghue, 2006). Motivational movies demonstrating positive performance with motivational music for a team or individual players can also be created. Reviewing video of successful performances has been recognised as a highly motivating factor (Dorwick, 1991), increasing player and team confidence (Jenkins et al., 2007). Individual player videos have been demonstrated to be particularly effective if they can include training performance and match footage to recognise the hard work and dedication a player has shown to produce good performances (O’Donoghue, 2006).
Talent identification and recruitment
Talent identification is a multidimensional process (Williams and Reilly, 2000; Figure 3.) in which performance analysis can play a considerable role. Many coaches and scouts consider that they can ‘see a good player’ (Williams and Reilly, 2000) leading to decisions being made on signing players based upon a subjective evaluation of the player (Carling et al., 2005). There are even instances where players have been signed when a coach has not personally observed the player performing (Carling et al., 2005). Performance analysis can provide objective data and video footage to assist and guide player recruitment, utilising match data relating to technical, tactical and physical performance (Carling et al., 2005). Prozone, Opta and AMISCO all provide a comprehensive scouting or recruitment package, with Opta claiming to have a database covering 15 European and South American competitions since 2000 (Fleming, 2011). An example of the use of data within player recruitment is provided by Manchester City, whose recruitment of Carlos Tevez, David Silva, Adam Johnson and Yaya Toure was guided by the finding that the top four clubs in the English Premier League consistently had the highest final third pass completion success (Kuper and Szymanski, 2012). Within 6 months of recruiting these players, the team’s ability to retain possession in the final third increased by 7.7% (Kuper and Szymanski, 2012). A further example can be seen in Liverpool’s acquisition of Stewart Downing during the summer of 2011, which was in part guided by the finding that he was one of the most prolific dribblers and chance creators in the Premier League the previous season, responsible for 17% of Aston Villa’s ‘overall club production’ (Kuper and Szymanski, 2012). However Downing did not have a particularly successful first season at Liverpool (neither scoring or making an assist in 20 appearances), which demonstrates that performance data should be used as a guide rather than an absolute measure when recruiting players.
Figure 3. Multi-dimensional process of talent identification (Williams and Reilly, 2000).
With regard to the identification of talented young players, children’s physical potential can be judged using a physical testing protocol and comparing performance against established normative profiles in a computer database (Cross and Brewer, 1999; Balmer and Franks, 2000; Williams and Reilly, 2000; Carling 2001). Databases can also be used to benchmark and reference the match performance of youth players, classifying performance as above average, average and below average (Carling et al., 2009), which may also indicate whether or not a player is ready to progress into the reserve or first team setup.
Within published coaching literature much attention has been paid to the effectiveness of training sessions for learning and performance (Smith et al., 2005), with the amount of time spent practicing being particularly important for the development of expertise (Ericsson et al., 1993; Schmidt and Lee, 1999). As a result maximising practice time in the face of the many factors that can disrupt training sessions is an important skill distinguishing between novice and expert coaches (Baker et al., 2003). Performance analysis systems can be applied to training sessions to evaluate their quality as part of a coach’s professional development.
Although the coaching culture within professional football has traditionally been cautious towards the application of sports science, the acknowledgement that sports science can enhance the coaching process has led to a more multi-disciplinary approach being favoured (Reilly, 2006), with performance analysis playing a key role (Lyle, 2002) due to its implications for other disciplines (Maile, 1999). However there are still a number of barriers that make the integration of sports science support problematic. Some such as time and cost are borne out of circumstance, whilst others may be caused by the coach themselves. Although it is clear that the specialist expertise of sports science support staff can extend beyond that of the coach in their particular areas, for sports science to maintain its currency in the professional football environment the relationship between the coach and sports science practitioners is critical (Lyle, 2002). Sports scientists require a coach-centred approach to gain an insight into how the coach operates, so that data can be provided in a way that the coach can understand enabling their expertise (Morgan, 2011), whilst also possessing multi-disciplinary knowledge in order to understand the impact of their discipline on others and the implications for the coaching process. A key skill of a successful coach is the ability to co-ordinate sports science support so that it is integrated into the coaching process to facilitate performance enhancement (Wright, 2012).
Baker, J., Horton, S., Robertson-Wilson, J., and Wall, M. (2003). Nurturing sport expertise: factors influencing the development of elite athlete. Journal of Sports Science and Medicine, 2(1), 1-9.
Balmer, N., and Franks, A. (2000). Normative values for 5 and 15 metre sprint times in young elite footballers. Insight – The Football Association Coaches Journal, 4(1), 25-27.
Bartlett, R. (1999). Sports Biomechanics: Reducing Injury and Improving Performance. London, UK: E & FN Spon.
Carling, C. (2001). Sports science support at the French Football Federation. Insight – The Football Association Coaches Journal, 4(4), 34-35.
Carling, C., Williams, A.M., and Reilly, T. (2005). The Handbook of Soccer Match Analysis. London, UK: Routledge.
Carling, C., Bloomfield, J., Nelsen, L., and Reilly, T. (2008). The role of motion analysis in elite soccer: contemporary performance management techniques and work rate data. Sports Medicine, 38(10),839-869.
Carling, C., Reilly, T., and Williams, A.M. (2009). Performance Assessment for Field Sports. London, UK: Routledge.
Cross, N., and Brewer, B. (1999). Coaching children. In N. Cross and J. Lyle (Eds.), The Coaching Process: Principles and practice for sport, (pp. 155-173). Edindurgh, UK: Butterworth-Heinemann.
Di Salvo, V., Collins, A., McNeill, B., and Cardinale, M. (2006). Validation of Prozone: a new video-based performance analysis system. International Journal of Performance Analysis in Sport, 6(1), 108-119.
Dowrick, P.W. (1991). Practical guide to using video in behavioural sciences. In T. Reilly, J. Hughes and M. Hughes (Eds.), Science and Football III (pp. 267-278). London, UK: E & FN Spon.
Drawer, S., and Fuller, C.W. (2002). Evaluating the level of injury in English professional football using a risk based assessment process. British Journal of Sports Medicine, 36(6), 446-451.
Edgecomb, S.J., and Norton, K.I. (2006). Comparison of global positioning and computer-based tracking systems for measuring player movement distance during Australian football. Journal of Science and Medicine in Sports, 9(1), 25-32.
Ekblom, B. (1986). Applied physiology of soccer. Sports Medicine, 3(1), 50-60.
Ericsson, K.A., Krampe, R.T., and Tesch-Romer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100(3), 363-406.
Fleming, M. (2011). Click and buy: How scouting embraced the 21st century, [online], http://www.independent.co.uk/sport/football/news-and-comment/click-and-buy-how-scouting-embraced-the-21st-century-2326368.html. [Accessed 3 June 2012].
Franks, I.M., Goodman, D., and Miller, G. (1983). Analysis of performance: qualitative or quantitative. Sports. March.
Gasston, V. (2004). Performance analysis during an elite netball tournament: experiences and recommendations. In P.G. O’Donoghue and M. Hughes (Eds.), Performance Analysis of Sport VI (pp. 8-14). Cardiff, UK: CPA Press UWIC.
GPSports. (2011). SPI Pro X, [on-line], http://gpsports.com/gpsports_website/index.php?category=3&page=16. [Accessed 10 November 2011].
Groom, R., Cushion, C., and Nelson, L. (2011). The delivery of video-based performance analysis by England youth soccer coaches: towards a grounded theory. Journal of Applied Sport Psychology, 23(1), 16-32.
Guadagnoli, M., Holcomb, W., and Davis, M. (2002). The efficacy of video feedback of learning the golf swing. Journal of Sports Sciences, 20(8), 615-622.
Hewett, T.E., Lindenfeld, T.N., Riccobene, J.V., and Noyes, F.R. (1997). The effect of neuromuscular training on the incidence of knee injury in female athetes. A prospective study. American Journal of Sports Medicine, 27(6), 699-706.
Hewett, T.E., Myer, G.D., and Ford, K.R. (2005). Reducing knee and anterior cruciate ligament injuries among female athletes: a systematic review of neuromuscular training interventions. The Journal of Knee Surgery, 18(1), 82-88.
Hodges, N.J., and Franks, I.M. (2002). Modelling coaching practice: the role of instruction and demonstration. Journal of Sports Sciences, 20(10), 793-811.
Hughes, M.D., and Bartlett, R.M. (2002). The use of performance indicators in performance analysis. International Journal of Performance Analysis in Sport, 20(10), 739-754.
Hughes, M., and Bartlett, R. (2008). What is performance analysis? In M. Hughes and I.M. Franks (Eds.), The Essentials of Performance Analysis: An introduction (pp. 8-20). London, UK: Routledge.
Hughes, M.D., and Franks, I.M. (2004). Notational Analysis of Sport: systems for better coaching. London, UK: Routledge.
Ives, J.C., Straub, W.F., and Shelley, G.A. (2002). Enhancing athletic performance using digital video in consulting. Journal of Applied Sport Psychology, 14(3), 237-245.
James, N. (2006). Notational analysis in soccer: past, present and future. International Journal of Performance Analysis in Sport, 6(2),67-81.
Jenkins, R.E., Morgan, L., and O’Donoghue, P. (2007). A case study into the effectiveness of computerised match analysis and motivational videos within the coaching of a league netball team. International Journal of Performance Analysis in Sport, 7(2), 59-80.
Krustrup, P., Mohr, M., Steensburg, A., Bencke, J., Kjaer, M., and Bangsbo, J. (2006). Muscle and blood metabolites during a soccer games: implications for sprint performance. Medicine and Science in Sports and Exercise, 38(6),1165-1174.
Kuper, S. (2011). A football revolution, [online], http://www.ft.com/cms/s/2/9471db52-97bb-11e0-9c37-00144feab49a.html#axzz1eknAhhld. [Accessed 21 November 2011].
Kuper, S., and Szymanski, S. (2012). Soccernomics. London, UK: HarperSport.
Laird, P., and Waters, I. (2008). Eyewitness recollection of sports coaches. International Journal of Performance Analysis in Sport, 8(1), 76-84.
Lyle, J. (2002). Sports Coaching Concepts: A framework for coach’s behaviour. London, UK: Routledge.
Maile, A. (1999). Applied physiology in sports coaching. In N. Cross and J. Lyle (Eds.), The Coaching Process: Principles and practice for sport, (pp. 91-112). Edinburgh, UK: Butterworth-Heinemann.
McGarry, T., and Franks, I.M. (2003). The science of match analysis. In T. Reilly and A.M. Williams (Eds.), Science and Soccer (pp. 265-275). New York, USA: Routledge.
Mohr, M., Krustrup, P., and Bangsbo, J. (2003). Match performance of high-standard soccer players with special reference to development of fatigue. Journal of Sports Sciences, 21(7), 519-528.
Mohr, M., Krustrup, P., and Bangsbo, J. (2005). Fatigue in soccer: a brief review. Journal of Sports Sciences, 23(6), 593-599.
Mohr, M., Krustrup, P., Nybo, L., Nielsen, J.J., and Bangsbo, J. (2004). Muscle temperature and sprint performance during soccer matches – beneficial effects of re-warm-up at half time. Scandinavian Journal of Medicine and Science in Sports, 14(3),156-162.
Morgan, S. (2011). “Empirical Coaching”: Guiding Principles in Enabling Coach Expertise. Report from Dagstuhl Seminar 11271: Computer Science in Sport – Special emphasis: Football.
O’Donoghue, P. (2006). The use of feedback videos in sport. International Journal of Performance Analysis in Sport, 6(2), 1-14.
O’Donoghue, P. (2010). Research Methods for Sports Performance Analysis. Abingdon, UK: Routledge.
O’Donoghue, P.G., and Tenga, A. (2001). The effect of score-line on work rate in elite soccer. Journal of Sports Sciences, 19(1), 25-26.
Redwood-Brown, A. (2008). Passing patterns before and after goal scoring in FA Premier League Soccer. International Journal of Performance Analysis in Sport, 8(3), 172-182.
Reilly, T. (2003). Environmental stress. In T. Reilly and A.M. Williams (Eds.), Science and Soccer (2nd ed.) (pp. 165-184). London, UK: E. & F.N. Spon.
Reilly, T. (2006). Journal of Sport Science and Physical Education (Bulletin 47, 2006). Introduction: Football – The Beautiful Game as a Field of Study. http://www.icsspe.org/bulletin/drucken_a4b0b68a.php.html
Reilly, T. (2007). Science of Training: Soccer. London, UK: Routledge.
Rienzi, E., Drust, B., Reilly, T., Carter, J.E.L., and Martin, A. (2000). Investigation of anthropometric and work-rate profiles of elite South American international soccer players. Journal of Sports Medicine and Physical Fitness, 40(1), 162-169.
Schmidt, R.A., and Lee, T.D. (1999). Motor Control and Learning: A Behavioral Emphasis. Champaign, Illinois, USA: Human Kinetics.
Smith, T., Hammond, J., and Gilleard, W. (2005). The use of performance analysis technology to monitor the coaching environment in soccer. International Journal of Performance Analysis in Sport, 5(3), 126-138.
Soligard, T., Myklebust, G., Steffen, K., Holme, I., Silvers, H., Bizzini, M., Junge, A., Dvorak, J., Bahr, R., and Andersen, TE. (2008). Comprehensive warm-up programme to prevent injuries in young female footballers: cluster randomised controlled trial. British Medical Journal, 337, doi: 10.1136/bmj.a2469
Spurrier, D. (2012). Pre-season screening and injury prevention, [online], http://www.ausport.gov.au/sportscoachmag/safety/pre-season_screening_and_injury_prevention. [Accessed 6 June, 2012].
Stratton, G., Reilly, T., Williams, A.M., and Richardson, D. (2004). Youth Soccer: From science to performance. London, UK: Routledge.
Thelwell, K. (2005). Forward. In C. Carling, A.M. Williams and T. Reilly (Eds.), Handbook of Soccer Match Analysis: A systematic approach to improving performance (pp. XVII). London, UK: Routledge.
Williams, A.M., and Reilly, T. (2000). Talent identification and development in soccer. Journal of Sports Sciences, 18(9), 657-667.
Wright, I. (2012). Coaching performance swimmers: The individualisation of training programmes in Great Britain, [online], http://www.coachesinfo.com/index.php?option=com_content&view=article&id=110:swimming-performance-swimmer&catid=49:swimming-coaching&Itemid=86. [Accessed 3 June, 2012].