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From Analysis to Coaching – The Need for Objective Feedback Mike Hughes – Centre for Performance Analysis, UWIC, Wales, UK
The coaching process is about enhancing performance by providing feedback about the performance to the athlete or team. Researchers have shown that human observation and memory, wonderful though they are, are not reliable enough to provide accurate and objective information for high-performance athletes. Objective measuring tools are necessary to enable the feedback process. These can take the form of video analysis systems post-event, both biomechanical or computerised notation systems, or the use of in-event systems.
Hand and computerised notation systems provide the same sort of data, both intrinsically being the same process, and they are used for the same purposes: analysis of movement, tactical evaluation, technical evaluation and statistical compilation. The recent developments in both computer and video technologies have transformed the approach of performance analysts and, consequently, their use in the coaching process. To ensure that accurate and reliable data are gathered for analysis for the coach, considerable training of the operatives is necessary, making the application of any of these systems more and more a specialism.
Because of the developing nature of the disciplines involved, not enough fundamental questions have been asked about the processes we apply, but we are hoping that some of these will be addressed in this article.
The essence of the coaching process is to instigate observable changes in behaviour. The coaching and teaching of skill depends heavily upon analysis to effect an improvement in athletic performance. Informed and accurate measures are necessary for effective feedback and improvement of performance. In most athletic events, analysis of the performance is guided by a series of qualitative assessments made by the coach. Franks et al, (1983) defined a simple flowchart of the coaching process (see Fig.1). This outlines the coaching process in its observational, analytical and planning phase. The game is watched and the coach will form a conception of positive and negative aspects of the performance. Often the results from previous games, as well as performances in practice, are considered before planning in preparation of the next match. The next game is played and the process repeats itself. There are, however, problems associated with a coaching process that relies heavily upon the subjective assessment of game action.
During a game many occurrences stand out as distinctive features, ranging from controversial decisions given by officials to exceptional technical achievements by individual players. While these are easily remembered, they tend to distort the coach’s assessment of the total game. Most of the remembered features of a game are those that can be associated with highlighted features of the play.
Fig.1 .Schema of the coaching process (Franks et al, 1983)
Human memory is limited so that it is almost impossible to remember all the events that take place during an entire competition. Franks and Miller (1986) showed that soccer coaches are less than 45% correct in their post-game assessment of what occurred during 45 minutes of a soccer game. While there is considerable individual variability, this rapid forgetting is not surprising, given the complicated process of committing data to memory and subsequently retrieving it. Events that occur only once in the game are not easily remembered and forgetting is rapid. Furthermore, emotions and personal biases are significant factors affecting memory storage and retrieval.
In most team sports an observer is unable to view, and assimilate, the entire action-taking place on all the playing area. Since the coach can only view parts of game action at any one time (usually the critical areas), most of the peripheral play action is lost. Consequently the coach must then base his post-match feedback on only partial information about a team’s, unit’s or individual’s performance during the game. This feedback is often inadequate, so an opportunity is missed to optimise performances of players and teams.
Problems associated with subjective assessments would seem to present the coach with insurmountable difficulties, particularly if improving the performance of the athlete hinges on the observational abilities of the coach. Despite the importance of observation within the coaching process, very little research has been completed into observational accuracy, the little that has clearly demonstrates that coaches cannot expect to remember even 50% of a performance, in most cases considerably less.
One of the coach’s main tasks is to analyse accurately and assess performance. It would seem then that this couldn’t be carried out subjectively. Any hopes for improvement through feedback would be reduced to chance. How can this be rectified?
Objectivity can be obtained through the use of video, biomechanical systems for fine analyses, or notational analysis. Hand notation systems are in general very accurate but have disadvantages: the more complex ones involve considerable learning time. In addition, the data these systems produce can involve many man-hours to process into output that is meaningful to the coach or athlete: for example it can take as much as 40 hours just to process the data from one squash match.
The introduction of computerised notation systems has enabled these two problems, in particular the data processing, to be tackled positively. Used in real-time analysis or, with video recordings, in post-event analysis, they enable immediate easy data access and the presentation of data in graphical and other pictorial forms more easily understood coaches and athletes. The increasing sophistication, and reducing cost, of video systems has greatly enhanced post-event feedback, from playback with subjective analysis by a coach to detailed objective analysis by means of notation systems (see Brown and Hughes, 1995).
and Hughes, 1995).
Computers introduce extra problems, of which system-users and programmers must be aware, such as operator errors (e.g. accidentally pressing the wrong key), hardware and software errors. Such undetected perception-errors, where the observer misunderstands an event or incorrectly fixes a position, are particularly problematic in real-time analysis when the data must be entered quickly.
To minimise these problems, careful validation of computerised notation systems must be carried out. Results from the computerised system and a hand system should be compared to assess the accuracy of the former. Reliability tests must also be performed on both hand and computerised systems to estimate the accuracy and consistency of the data.
Four major purposes of notational analysis are:
. 1 Analysis of movement
. 2 Tactical evaluation
. 3 Technical evaluation
. 4 Statistical compilation
Many of the traditional systems are concerned with the statistical analysis of events previously recorded by hand. The advent of on-line computer facilities overcame this problem, since the game could first be digitally represented first, via data collection directly into the computer, then documented via the response to queries about the game. The major advantage of this method of data collection is that the game is represented in its entirely and stored in ROM or on disk. A database is therefore initiated – a powerful tool once manipulated.
Team sports can benefit immensely from the development of computerised notation; the information derived can be used for several purposes (Franks et al, 1983):
. 1 immediate feedback;
. 2 development of a database;
. 3 indication of areas requiring improvement;
. 4 evaluation;
. 5 as a mechanism for selective searching through a video recording of the game.
All of these are of paramount importance to the coaching process, the initial reason for performance analysis. Database development is crucial. If the database is large enough, it will enable predictive modelling as an aid to the analysis of different sports, subsequently enhancing future training and performance. Knowing when you have enough data to form a true performance profile is not easy, but Hughes et al.(2001) give some guidelines.
Using computer analysis systems accurately and reliably needs a structured training programme that deals with all aspects of the system. There are at least three problems in obtaining objective, accurate data from a system such as the Computerised Coach Analysis System (Franks et al, 1988). The definition of behaviour given to the observer by the experimenter may be vague, subjective or incomplete. The behaviour may be difficult to detect because of its subtlety or complexity, because of distractions, or because of other factors obstructing observation. Finally the observer may be poorly trained, unmotivated or incompetent.
The two fundamental goals of a training programme are teaching the observer the data collecting and recording techniques required by the instrument. The second more difficult task is teaching the observer the behaviour categories, and their operational definitions, defined unambiguously. To be adequately trained, the observer must have knowledge of these definitions, understand them and be able to apply them in varying circumstances. The training programme should train the observers to observe, that is, where and how to look, and what to look for. It should also provide some method of
train the observers to observe, that is, where and how to look, and what to look for. It should also provide some method of evaluating the observer’s progress toward the goals of understanding the definitions and becoming skilled (reliability studies again). In addition, such an evaluation could be used to assess the observer’s understanding of recording techniques (Hughes et al, 1989). Because of their accumulation of these skills, these tasks have become the preserve of specialist performance analysts.
Because of the shortcomings of the human observation system and the fallibility of human memory, it is unrealistic to expect a coach to remember large parts of an athletic performance. By using objective observation systems, coaches can focus their attention on analysing what they perceive to be critical incidents in their athletes’ performances. In this way they can hope to improve the performance of these athletes by planning practices based on these analyses. Hand notation and computerised notation systems and all biomechanical analysis systems have been shown to benefit these processes. The simple model (Fig.1) of the coaching process can now be extended (Fig.2) to include some of these recent developments in computer and video technology.
Fig.2 .A more complex schema of the coaching process
The ultimate problems facing the coach and the analyst now are:
Establishing the reliability of observations, Ensuring that enough data have been collected to define the performance profile fully, and Transforming these data into meaningful interpretations for their sport.
As yet, there are no set paradigms for these processes in Performance Analysis, but these problems will be explored and examples from different sports will be presented in this series of articles over the next few months to highlight good practice.
Brown, D. and Hughes, M. (1995) The effectiveness of quantitative and qualitative feedback in improving performance in squash. In T. Reilly, M.D. Hughes and
A. Lees (Eds), Science and Racket Sports. E & FN Spon: London, pp. 232-237.
Franks, I.M., Johnson, R & Sinclair, G.D. (1988) The development of a computerised coaching analysis system for recording behaviour in sporting
environments. Journal of Teaching Physical Education, 8, 23-32.
Franks, I.M. & Miller, G. (1986). Eyewitness testimony in sport. Journal of Sport Behavior, 9, 39-45.
Franks, I.M., Goodman, D., & Miller, G. (1983). Analysis of performance: Qualitative or Quantitative. SPORTS, March.
Hughes, M., Evans, S. and Wells, J. (2001) Establishing normative profiles in performance analysis. International Journal of Performance Analysis of Sport
(electronic), 1, 4 – 27.
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Hughes, M.D., Franks, I.M. and Nagelkerke, P. (1989 MIKE CITED AS 1992) A video-system for the quantitative motion analysis of athletes in competitive
sport. Journal of Human Movement Studies, 17, 212-227.
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