VIDEO ANALYSIS AND PERFORMANCE PROFILING AS TOOLS FOR COACHES

Systems such as SportsCode and Focus are capable of providing the fast and efficient feedback that Hughes and Franks (1997) identified as a pressing need within coaching.

The successful application of these systems, however, depends upon the manner in which they are used (e.g. clearly determining what to analyse) as the quality of the output, although reliant on the information input, is without question. Additionally, the flexibility of the SportsCode system allows the coach to review performance and provide feedback both during and after the event. Figure 9.6 represents a flow-diagram modified from the work of Hughes and Franks (1997: 16), which illustrates such usage, thus locating notational analysis firmly within the coaching process.

Through such structured programmes of analysis, coaches are able to access vast amounts of detailed information not only on their own team and players but also on the opposition.

Hence, the statistical data and video feedback gathered can be used to build up a database over a number of matches or even an entire season (Partridge and Franks 1993). This could potentially be made available to players and coaches across a network of computers.

Indeed, the Welsh Rugby Union and a number of other national governing bodies and professional clubs are currently employing such systems to aid player development. This is because notational analysis, particularly through the use of video, gives coaches a chance to record, observe, reflect and check performances accurately through a medium that captivates both themselves and athletes (Lyons 1988).

The early work of Sanderson and Way (1979) and Hughes (1986) highlighted that a database of matches from sports such as football, rugby, hockey and netball could provide information regarding patterns of play that could be considered representative of the subjects used. The subsequent formation of profiles of different groups of players is proving to be a very powerful tool for coaches in their attempts to understand their respective sports better. As such, a number of studies over the years have attempted to profile both different player groups and aspects of sport. For example, Hughes et al. (2000) sought to answer the question of how many games should be observed before it could be concluded that a definite pattern had emerged. They replicated the earlier study of Hughes (1986) but used female squash players of three different standards as their subjects. They

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Figure 9.6 A modified flow-diagram illustrating the use of video feedback within the coaching process

compared the profiles from databases containing eight, nine and ten matches to investigate when the profiles had become normative, that is stable. Statistical tests were used to ascertain the overall match totals, and distribution (i.e. location) of shots. They found that recreational players did not establish a normative playing pattern but county and elite players did. There was a difference, however, in the number of matches it took for the county and elite players’ profiles to become normative. For county players it took eight to nine matches while for elite players it took six. However, more data were produced during the elite matches due to their longer duration, which could explain why the profiles of elite players stabilised more quickly. What is more likely is that as players improve in standard they are able to sustain set patterns of play due to their greater skill level. The opposite is true of recreational players, who generally are not skilful enough to play to fixed tactical patterns and so their profiles do not stabilise as quickly. The study showed that creating normative profiles is highly dependent on the nature of the data being collected and the ability of the performers. Such contextual factors, then, need to be considered carefully by coaches before they commission and/or interpret given data. Similarly, one would assume that the greater the number of matches in a database the more reliable the profile produced (Potter and Hughes 2001). However, recent work has suggested that as a database grows it becomes less sensitive to changes in playing patterns, and so becomes less accurate (Hughes et al. 2001). This, then, is currently a point of debate.

The number of recent research papers examining how a picture of athlete performance can be constructed demonstrates that this is an interesting and constantly evolving area of investigation. No doubt, methods of establishing how data stabilise leave a lot to be desired (Hughes et al. 2001), but at least they do give us some early signs of when performance-related patterns emerge. Additionally, the recent work of James et al. (2005) and O’Donoghue (2005) point the way to alternative ways of recognising and expressing patterned data, which could well bear fruit in future. Needless to say, the more accessible and understandable the data, providing its complexity is not lost, the better for the coach in the quest to improve athlete performance.

CONCLUSION

Systematic notational instruments provide a method of collecting accurate, in-depth descriptive data on athlete performance. These data can be analysed and processed in a variety of ways thus providing a basis for detailed feedback regarding that performance.

Furthermore, advances in both computer and video technology have recently made this observation process increasingly efficient. This chapter has attempted to illustrate how such systems and technology can help coaches. In this respect, through their careful and considered use, accurate and relevant data can be gleaned on any aspect of athletic competition. Such information is crucial in many ways, but particularly so in helping coaches to understand the performances of their own athletes and players, while developing realistic game plans to deal with future opposition.

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1. What are the principal purposes of notational analysis? For what can the data gathered primarily be used?

2. Imagine you are charged with developing a new notational analysis system for an under-researched sport. Where do you start? Which factors should be taken into account in your thinking? Why?

3. Draw a flow-chart for any element of performance in a sport of your choice.

4. What is meant by ‘performance profiling’?

5. When can a database of a racket player’s actions become accepted as a profile?

What are the factors that need to be considered when deciding this?

REVIEW QUESTIONS