Περί Ψυχολογίας (2)
ΤΟΥ COACH ΔΙΑΜΑΝΤΑΚΟΥ ΙΩΑΝΝΗ
Καλή ψυχολογία, κακή ψυχολογία, στροφή της ψυχολογίας, η ψυχολογία στα ύψη, ψυχολογικό ντοπάρισμα......πρόκειται για εκφράσεις που ακούγονται καθημερινά. Δεν θα εξετάσουμε το αν είναι δόκιμες ή όχι, απλά θα θέλαμε να σταθούμε στο πόσο γενικόλογες έως και αφηρημένες ηχούν πολλές φορές.
Αν θεωρήσουμε 'οτι η προπονητική στηρίζεται σε τρείς βασικούς άξονες (προπόνηση φυσικής κατάστασης, προπόνηση τεχνικής-τακτικής-, ψυχολογική προετοιμασία), εύκολα παρατηρούμε ότι για τους δύο πρώτους, μια σειρά ανθρώπων και διαδικασιών χρησιμοποιούνται προκειμένου να στηθούν και να λειτουργήσουν στο ύψος και τις ανάγκες των περιστάσεων. Το πρώτο μέλημα τους είναι να μετρήσουν, να ελέγξουν, να αξιολογήσουν (οι έννοιες δεν είναι ταυτόσημες, αλλά πολύ σχετικές) και με βάση τα αποτελέσματα των παραπάνω διαδικασιών να προχωρήσουν στη κατάρτιση του προπονητικού πλάνου και προγραμματισμού. Σε κάθε στάδιο του προπονητικού κύκλου, ιδιαίτερα στην αρχή της αγωνιστικής σεζόν, λαμβάνουν χώρα μετρήσεις, σχετικά με το επίπεδο της φυσικής τους κατάστασης σε εργομετρικά κέντρα, υπόκεινται σε αξιολογήσεις σχετικά με το επίπεδο της τεχνικής τους κατάρτισης, οι προπονητές επιχειρούν να αποκωδικοποιήσουν τα στατιστικά αυτών, χρησιμοποιούνται εργαλεία όπως το TENDEX για παράδειγμα, ακόμα και σε τμήματα υποδομής ένας προπονητής σίγουρα θα πει στους νεαρούς παίκτες "πάρτε σφυγμό'...Ολες αυτές οι διαδικασίες ελέγχου, αποτελούν βασική προϋπόθεση για να πάμε στο επόμενο βήμα.
Αυτά σε ότι αφορά στους δύο πρώτους άξονες της προπονητικής...τι συμβαίνει όμως με τον τρίτο; Τον ψυχολογικό; την ψυχολογική προετοιμασία; Υπάρχει έλεγχος, μετρήσεις, αξιολόγηση; Αν ναι, πολύ ορθώς (αν και διατηρούμε τις επιφυλάξεις μας για το αν υπάρχει....), αν όχι όμως πως μπορούμε να μιλάμε για καλή και κακή ψυχολογία; και το σημαντικότερο..πως μπορούμε να καταρτίσουμε πλάνο προετοιμασίας σχετικά με αυτό τον παράγοντα;
Θα μπορούσαν κάποιοι σε αυτό το σημείο να αναρωτηθούν..τι μπορούμε να μετρήσουμε; Η απάντηση είναι πως μπορούμε να μετρήσουμε πολύ περισσότερα από όσα αρκετοί φαντάζονται και αυτό διότι η αγωνιστική επίδοση καθορίζεται και είναι κορεσμένη (ο όρος χρησιμοποιείται και με την κυριολεκτική αλλά και με τη στατιστική του διάσταση) στον ψυχολογικό παράγοντα. Η επιστημονική κοινότητα μας παρέχει ένα πλήθος ψυχομετρικών εργαλείων και μεθόδων που μας επιτρέπουν να αξιολογήσουμε την προσωπικότητα κάθε αθλητή (θεωρούμε σημαντικότατο να γνωρίζει ο κάθε προπονητής την προσωπικότητα των αθλητών του και τις ιδιαίτερες πτυχές αυτής), διάφορες ψυχοκινητικές παραμέτρους, όπως, το χρόνο αντίδρασης, το χρόνο πρόβλεψης, την συγκέντρωση της προσοχής, την δυναμική ισορροπία, την οπτικό-κινητική συναρμογή, την αντίληψη, την κινητική μνήμη, ή ακόμα τα επίπεδα άγχους του κάθε αθλητή, την αγωνιστική του συμπεριφορά, το τι είδος παρακίνησης προτιμά (έμμεση ή άμεση) και η αναφορά θα μπορούσε να συνεχίσει...
Να λοιπόν γιατί ο παράγοντας Ψυχολογία δεν μπορεί να περιοριστεί μόνο και μόνο στην παρακίνηση και την κατάσταση 'ροής'. Εκτελώντας τις παραπάνω διαδικασίες εκτός του ότι μπορούμε πλέον να καταρτίσουμε ένα πλάνο ψυχολογικής προετοιμασίας, εκτός του ότι διαθέτουμε μια σημαντική βάση δεδομένων που θα μας βοηθήσει στη διαχείριση του ανθρώπινου δυναμικού (ομάδας), παράλληλα θα μας δώσει χρήσιμες πληροφορίες σε δύο βασικά ερωτήματα κατά τη ανάλυση της αγωνιστικής απόδοσης: "πώς συμβαίνει;" και 'τι συμβαίνει;'...στο μπάσκετ αρκετές φορές τίθεται και ένα άλλο ερώτημα: 'γιατί συμβαίνει;", αλλά με αυτό θα ασχοληθούμε σε μελλοντικό άρθρο.
Το σύνολο των διαδικασιών (αλλά όχι μόνο αυτό) που αναφέρθηκε παραπάνω, βρίσκεται αρκετά κοντά σε αυτό που στην Δυτική Ευρώπη αλλά και στις Η.Π.Α ονομάζουν Sports Performance Analysis μια νέα διάσταση της προπονητικής επιστήμης που έχει ως στόχο την μεγιστοποίηση της αγωνιστικής απόδοσης μέσω της αγωνιστικής ανάλυσης.
Στη συνέχεια θα δανειστούμε ένα άρθρο από το διαδίκτυο προκειμένου να περιγράψουμε την έννοια Sports Performance Analysis
Performance analysis: What is Performance Analysis, and how can it be integrated within the coaching process to benefit performance?
In any sporting situation, especially team games, it is difficult, if not impossible, for coaches to notice and remember all the key events occurring within a training session or match, equipped only with their knowledge of the sport in question and their innate powers of observation(1). Yet analysis based on accurate observation and recall is a key tool for improving future performance.
That’s where the relatively new discipline of performance analysis comes in. Established over the last decade and facilitated by advances in IT and digital photography, performance analysis (PA) is now acknowledged as an aid to performance enhancement at all levels.
Essentially, PA is about creating a valid and reliable record of performance by means of systematic observations that can be analysed with a view to facilitating change.
The process relies on two distinct sports science disciplines:
• notational/match analysis, which uses means to record aspects of team performance;
• biomechanics, which revolves around the sporting impact of body movements.
The two disciplines use similar methods to collect data and both rely on IT for data analysis. But the main thing they have in common is the use of measured observation during or after an event to quantify performance in an accurate, reliable and valid way.
Coaches may want to question the need for PA as a separate activity, given that observation and analysis clearly form a crucial part of the coaching process as outlined in figure 1 below.
The fact is, though, that while coaches are expected to be experts at observing and analysing performance, research has pointed to severe human limitations within these processes.
Two key studies have highlighted memory retention problems, with coaches able to recall only 30-50% of key performance factors they had witnessed, even with special training in observation(3,4).
The coaching process itself is not necessarily flawed, but it is obvious that the observation and analysis phases of this process have severe limitations. Although many great coaches are able to anticipate events and make appropriate changes to influence performance, even the best are prone to human error, leading to wrong decisions; hence the need for a systematic PA approach within coaching practice, using valid and reliable performance data to monitor and evaluate performers.
Without such an approach, coaches are liable to form biased opinions of their athletes’ or players’ performances, leading to potentially incorrect substitution decisions or training prescriptions.
Technological advances and declining costs have given coaches access to laptop computers, digital cameras and analysis software, making the whole process of PA simpler and less arduous.
This process can be used to identify and measure a range of ‘performance indicators’ that have a real bearing on the outcome of any given sport, so providing a better understanding of how success can be achieved at all levels of performance.
These include:
• tactical indicators (patterns of play);
• technical indicators (technique/performance);
• physiological indicators (intensity profiles);
• psychological indicators (arousal, motivation).
Before deciding which performance indicators you wish to focus on in analysing the performance of your athletes, it is a good idea to consult a technical expert in your particular sport or study past research to identify indicators that are known to contribute to successful performance(5). Because the chosen indicators should guide how the system will be designed, you need to make these decisions first.
The first step is to create a logical structure to the game itself. This means defining the range of possible actions in the game and linking these actions with possible outcomes, thus describing the sequential path the performance can take. This process is described in more detail in the example analysis of the football club presented below (see figures 2 and 3).
Performance analysts have tended to focus on tactical and technical indicators and, in so doing, have contributed to our understanding of the physiological, psychological and tactical demands of many sports(6). For example, in basketball one aspect of a team’s performance may be appraised by the ratio of shots taken to baskets scored, while in golf, performance may be assessed by the number of greens hit in regulation.
Indicators provide simple information that can be used to describe and define a particular performance. But it is important to be careful over how the data is presented since, in isolation, these can give a distorted impression of performance.
For example, if two football strikers have each scored four goals over four games, it would be easy to assume that both are performing well. However, if striker A has had 16 shots on goal to striker B’s eight shots, the former’s success ratio is 4:1 compared with a much more impressive ratio of 2:1 for the latter.
Comparing performances between teams, team members and within individuals is often easier and more accurate if the performance indicators are expressed in terms of ratios, such as possession to turnovers, winners to errors, and passes taken to passes completed.
An individual’s performance profile can become distorted if the correct comparisons are not made, since profiles may differ according to the opposition. For example, presenting an individual soccer midfielder’s performance could be misleading without comparison with the opposing player’s or team’s data.
Performance data for an individual can be presented in three ways to evaluate success(6):
1. In relation to the opponent’s data. This allows for a direct comparison with the opposition, but could be misleading if the players are not of a similar standard;
2. In relation to players of the same standard. This allows for comparison between equals, which is useful providing data of this nature is available or can be compiled;
3. In relation to their own profiles of previous performances. Over the course of a number of competitive matches, a normative profile of a player or team can be created for comparative purposes. A player can then be assessed against his own normative profile to assess the relative merits of his latest performance.
Performance can be analysed in two ways within team sports:
• Individual assessment of players within the team, for example strikers in football;
• Assessment of an aspect of performance for the whole team, eg monitoring of scoring effectiveness in basketball.
There are two main methods of coding the observations made within a sporting situation: ‘live coding’ and post-play coding. The former requires a high degree of competency in coding a sporting situation, with video footage fed directly into a laptop and coded via the keyboard as events unfold within the training session or game. With post-play coding, the video footage is again fed into a laptop and the information coded via the keyboard, with the advantage that the footage can be slowed down or reviewed more than once to ensure the observations are accurate.
To show how this process can work in practice, I would like to present an example of one of my own performance analyses – an assessment of strikers for an English Nationwide League Division Three Football Club.
My first priority was to find out what the club wanted to gain from the analysis. The outcome was confirmation that it wished to improve the feedback to coaches and players on individual and team performances.
It was agreed that the first stage of the analysis would focus on the role and function of the strikers within the team, and that two full games would be filmed in similar fashion to a ‘player cam’. The players themselves were kept in the dark about what was happening to ensure they played normally rather than acting up for the cameras.
The first step in designing the analysis system was to gain a logical understanding of the strikers’ involvement within the team’s tactics. The plan that emerged was that on gaining possession of the ball, it was to be played into the strikers and then laid off to the midfield players, who would try to spread the play to the wings, resulting in a cross or through ball for the strikers to achieve a shot on goal. The coaching staff realised that this form of tactical play relied heavily on what the strikers did with the ball when played into them, and was essentially the key to the attacking strategies. We decided that this would be the focal point of the analysis.
The pre-analysis consultation also highlighted the club’s interest in identifying a performance profile for its strikers. This was built on the path outlined in figure 2 (above) and based on movement sequences which would expose the strengths and weaknesses of individual players (see figure 3, above).
I made my observations with a computerised notational match analysis software package called Nordulus Observer Pro, and the two matches were coded manually post-competition. The results obtained from the analysis were then relayed to the club’s coach, who then fed them back personally to the players, along with recommendations for improvement.
The following is an example of part of an individual striker’s performance profile built up in the manner described above.
The main emphasis was on how this player used possession of the ball, when played into feet, head or chest. The ball was played into feet 27 times during the game, of which the player:
• held the ball and distributed 10 times, six in midfield and four in the attacking third;
• played the ball off one touch six times, three in midfield and three in the attacking third;
• rolled the defender twice, in midfield and the attacking third;
• lost possession nine times, four times in midfield, four times in the attacking third and once in the defensive third.
The analysis also identified the number of headers won/lost, shots on and off target and number of times possession was won and lost, as follows:
• 10 headers won, of which four in midfield, four in attack and two in defence;
• nine headers lost, of which four in midfield and five in attack;
• five attempts on target, two with the head and three with the foot, with one successful strike;
• two attempts off target, from a header and a strike;
• possession won seven times, five times through closing down and twice by winning tackles;
• possession lost twice in midfield through being closed down.
The performance profiles identified the personal strengths and weaknesses of the individual players, providing a technical focus for future training sessions. For example, it showed the coach needed to:
• work on the players’ ability to maintain possession of the ball when played into the chest;
• improve the link-up play with the strikers and midfield players to help decrease the number of possessions lost and maintain fluency within the attack;
• work to the strikers’ strengths of making successful use of possession when the ball is played into their feet.
The players were also given individual goal-setting plans aimed at overcoming their weaknesses. To establish the value of the whole process, another full game was analysed in the same way four weeks later. The results showed significant improvement by the strikers and substantial progress towards their individual goals.
The club agreed that the project had been successful and that it had highlighted weaknesses they hadn’t been aware of. The players responded well to the feedback and targets. And the whole process gave rise to a second project involving the central midfielders.
The second practical example I would like to present is a performance analysis I carried out for a National Junior League Under-18 basketball team.
As coach of the junior men’s basketball team, I and the rest of the coaching team wanted to identify areas of weakness within the whole team’s performance, providing objective measures to explain some recent poor performances. The team have four different plays (structured offence/attack) that are practised for use within game situations, but despite reinforcement from the coaching team, they did not seem to be using these plays consistently in match situations. When they did run a structured offence, as practised, they seemed to enjoy more success than when they fell back on a more freely structured approach.
A performance analysis process was used to provide an objective analysis of the team’s offence, producing a ratio of the number of plays run to the number of unstructured offences, and the success ratio for each type of offence. As with the previous example, four games were filmed for analysis and observations were made with the same system.
The results of the analysis are shown in figure 4, below.
Figure 4: basketball team analysis
Analysis results Game 1 Game 2 Game 3 Game 4
Plays:unstructured offences 35:115 32:102 46:94 57:76
Percentage contribution 23% 23.8% 32% 42.8%
Play success ratio Success:unsuccessful offences 23:12 18:14 31:15 37:20
Percentage success 65.7% 56.5% 67% 64%
Unstructured success ratio Success:unsuccessful offences 14:101 19:102 16:78 10:66
Percentage success 12% 18.6% 17% 13.2%
The analysis confirmed the coaching team’s belief that the plays were not being run as requested, and also showed that the success rate of the plays were much higher than those of unstructured offences. Using this material, the coaches were able to present their players with an objective demonstration of the value of using the plays practised in training. Filming four games in succession – two after the analysis – enabled the coaches to track progress and provide positive feedback to the players. The results of the analysis can be retained for future reference and as the basis for further analyses. All in all, a very positive result.
Dan Bishop
References
1. Coleman, S (1998) Biomechanics and its application to coaching practice. In Cross, N & Lyle, J (Eds). The Coaching Process: Principles and Practice for Sport (pp131-141). Reed Educational and Professional Publishing Ltd: Oxford
2. Robertson, K (2000) Observation, Analysis and Video. The National Coaching Foundation: Leeds, UK
3. Journal of Sports Science (1991), 9 (3) pp285-297
4. Journal of Sport Behaviour (1986), 9, pp34-45
5. Hughes, MD & Franks, IM (1997). Notational Analysis of Sport, E & FN SPON: London
6. Journal of Sports Science (2002) 20, pp739-754
performance analysis, coaching, training
In any sporting situation, especially team games, it is difficult, if not impossible, for coaches to notice and remember all the key events occurring within a training session or match, equipped only with their knowledge of the sport in question and their innate powers of observation(1). Yet analysis based on accurate observation and recall is a key tool for improving future performance.
That’s where the relatively new discipline of performance analysis comes in. Established over the last decade and facilitated by advances in IT and digital photography, performance analysis (PA) is now acknowledged as an aid to performance enhancement at all levels.
Essentially, PA is about creating a valid and reliable record of performance by means of systematic observations that can be analysed with a view to facilitating change.
The process relies on two distinct sports science disciplines:
• notational/match analysis, which uses means to record aspects of team performance;
• biomechanics, which revolves around the sporting impact of body movements.
The two disciplines use similar methods to collect data and both rely on IT for data analysis. But the main thing they have in common is the use of measured observation during or after an event to quantify performance in an accurate, reliable and valid way.
Coaches may want to question the need for PA as a separate activity, given that observation and analysis clearly form a crucial part of the coaching process as outlined in figure 1 below.
The fact is, though, that while coaches are expected to be experts at observing and analysing performance, research has pointed to severe human limitations within these processes.
Two key studies have highlighted memory retention problems, with coaches able to recall only 30-50% of key performance factors they had witnessed, even with special training in observation(3,4).
The coaching process itself is not necessarily flawed, but it is obvious that the observation and analysis phases of this process have severe limitations. Although many great coaches are able to anticipate events and make appropriate changes to influence performance, even the best are prone to human error, leading to wrong decisions; hence the need for a systematic PA approach within coaching practice, using valid and reliable performance data to monitor and evaluate performers.
Without such an approach, coaches are liable to form biased opinions of their athletes’ or players’ performances, leading to potentially incorrect substitution decisions or training prescriptions.
Technological advances and declining costs have given coaches access to laptop computers, digital cameras and analysis software, making the whole process of PA simpler and less arduous.
This process can be used to identify and measure a range of ‘performance indicators’ that have a real bearing on the outcome of any given sport, so providing a better understanding of how success can be achieved at all levels of performance.
These include:
• tactical indicators (patterns of play);
• technical indicators (technique/performance);
• physiological indicators (intensity profiles);
• psychological indicators (arousal, motivation).
Before deciding which performance indicators you wish to focus on in analysing the performance of your athletes, it is a good idea to consult a technical expert in your particular sport or study past research to identify indicators that are known to contribute to successful performance(5). Because the chosen indicators should guide how the system will be designed, you need to make these decisions first.
The first step is to create a logical structure to the game itself. This means defining the range of possible actions in the game and linking these actions with possible outcomes, thus describing the sequential path the performance can take. This process is described in more detail in the example analysis of the football club presented below (see figures 2 and 3).
Performance analysts have tended to focus on tactical and technical indicators and, in so doing, have contributed to our understanding of the physiological, psychological and tactical demands of many sports(6). For example, in basketball one aspect of a team’s performance may be appraised by the ratio of shots taken to baskets scored, while in golf, performance may be assessed by the number of greens hit in regulation.
Indicators provide simple information that can be used to describe and define a particular performance. But it is important to be careful over how the data is presented since, in isolation, these can give a distorted impression of performance.
For example, if two football strikers have each scored four goals over four games, it would be easy to assume that both are performing well. However, if striker A has had 16 shots on goal to striker B’s eight shots, the former’s success ratio is 4:1 compared with a much more impressive ratio of 2:1 for the latter.
Comparing performances between teams, team members and within individuals is often easier and more accurate if the performance indicators are expressed in terms of ratios, such as possession to turnovers, winners to errors, and passes taken to passes completed.
An individual’s performance profile can become distorted if the correct comparisons are not made, since profiles may differ according to the opposition. For example, presenting an individual soccer midfielder’s performance could be misleading without comparison with the opposing player’s or team’s data.
Performance data for an individual can be presented in three ways to evaluate success(6):
1. In relation to the opponent’s data. This allows for a direct comparison with the opposition, but could be misleading if the players are not of a similar standard;
2. In relation to players of the same standard. This allows for comparison between equals, which is useful providing data of this nature is available or can be compiled;
3. In relation to their own profiles of previous performances. Over the course of a number of competitive matches, a normative profile of a player or team can be created for comparative purposes. A player can then be assessed against his own normative profile to assess the relative merits of his latest performance.
Performance can be analysed in two ways within team sports:
• Individual assessment of players within the team, for example strikers in football;
• Assessment of an aspect of performance for the whole team, eg monitoring of scoring effectiveness in basketball.
There are two main methods of coding the observations made within a sporting situation: ‘live coding’ and post-play coding. The former requires a high degree of competency in coding a sporting situation, with video footage fed directly into a laptop and coded via the keyboard as events unfold within the training session or game. With post-play coding, the video footage is again fed into a laptop and the information coded via the keyboard, with the advantage that the footage can be slowed down or reviewed more than once to ensure the observations are accurate.
To show how this process can work in practice, I would like to present an example of one of my own performance analyses – an assessment of strikers for an English Nationwide League Division Three Football Club.
My first priority was to find out what the club wanted to gain from the analysis. The outcome was confirmation that it wished to improve the feedback to coaches and players on individual and team performances.
It was agreed that the first stage of the analysis would focus on the role and function of the strikers within the team, and that two full games would be filmed in similar fashion to a ‘player cam’. The players themselves were kept in the dark about what was happening to ensure they played normally rather than acting up for the cameras.
The first step in designing the analysis system was to gain a logical understanding of the strikers’ involvement within the team’s tactics. The plan that emerged was that on gaining possession of the ball, it was to be played into the strikers and then laid off to the midfield players, who would try to spread the play to the wings, resulting in a cross or through ball for the strikers to achieve a shot on goal. The coaching staff realised that this form of tactical play relied heavily on what the strikers did with the ball when played into them, and was essentially the key to the attacking strategies. We decided that this would be the focal point of the analysis.
The pre-analysis consultation also highlighted the club’s interest in identifying a performance profile for its strikers. This was built on the path outlined in figure 2 (above) and based on movement sequences which would expose the strengths and weaknesses of individual players (see figure 3, above).
I made my observations with a computerised notational match analysis software package called Nordulus Observer Pro, and the two matches were coded manually post-competition. The results obtained from the analysis were then relayed to the club’s coach, who then fed them back personally to the players, along with recommendations for improvement.
The following is an example of part of an individual striker’s performance profile built up in the manner described above.
The main emphasis was on how this player used possession of the ball, when played into feet, head or chest. The ball was played into feet 27 times during the game, of which the player:
• held the ball and distributed 10 times, six in midfield and four in the attacking third;
• played the ball off one touch six times, three in midfield and three in the attacking third;
• rolled the defender twice, in midfield and the attacking third;
• lost possession nine times, four times in midfield, four times in the attacking third and once in the defensive third.
The analysis also identified the number of headers won/lost, shots on and off target and number of times possession was won and lost, as follows:
• 10 headers won, of which four in midfield, four in attack and two in defence;
• nine headers lost, of which four in midfield and five in attack;
• five attempts on target, two with the head and three with the foot, with one successful strike;
• two attempts off target, from a header and a strike;
• possession won seven times, five times through closing down and twice by winning tackles;
• possession lost twice in midfield through being closed down.
The performance profiles identified the personal strengths and weaknesses of the individual players, providing a technical focus for future training sessions. For example, it showed the coach needed to:
• work on the players’ ability to maintain possession of the ball when played into the chest;
• improve the link-up play with the strikers and midfield players to help decrease the number of possessions lost and maintain fluency within the attack;
• work to the strikers’ strengths of making successful use of possession when the ball is played into their feet.
The players were also given individual goal-setting plans aimed at overcoming their weaknesses. To establish the value of the whole process, another full game was analysed in the same way four weeks later. The results showed significant improvement by the strikers and substantial progress towards their individual goals.
The club agreed that the project had been successful and that it had highlighted weaknesses they hadn’t been aware of. The players responded well to the feedback and targets. And the whole process gave rise to a second project involving the central midfielders.
The second practical example I would like to present is a performance analysis I carried out for a National Junior League Under-18 basketball team.
As coach of the junior men’s basketball team, I and the rest of the coaching team wanted to identify areas of weakness within the whole team’s performance, providing objective measures to explain some recent poor performances. The team have four different plays (structured offence/attack) that are practised for use within game situations, but despite reinforcement from the coaching team, they did not seem to be using these plays consistently in match situations. When they did run a structured offence, as practised, they seemed to enjoy more success than when they fell back on a more freely structured approach.
A performance analysis process was used to provide an objective analysis of the team’s offence, producing a ratio of the number of plays run to the number of unstructured offences, and the success ratio for each type of offence. As with the previous example, four games were filmed for analysis and observations were made with the same system.
The results of the analysis are shown in figure 4, below.
Figure 4: basketball team analysis
Analysis results Game 1 Game 2 Game 3 Game 4
Plays:unstructured offences 35:115 32:102 46:94 57:76
Percentage contribution 23% 23.8% 32% 42.8%
Play success ratio Success:unsuccessful offences 23:12 18:14 31:15 37:20
Percentage success 65.7% 56.5% 67% 64%
Unstructured success ratio Success:unsuccessful offences 14:101 19:102 16:78 10:66
Percentage success 12% 18.6% 17% 13.2%
The analysis confirmed the coaching team’s belief that the plays were not being run as requested, and also showed that the success rate of the plays were much higher than those of unstructured offences. Using this material, the coaches were able to present their players with an objective demonstration of the value of using the plays practised in training. Filming four games in succession – two after the analysis – enabled the coaches to track progress and provide positive feedback to the players. The results of the analysis can be retained for future reference and as the basis for further analyses. All in all, a very positive result.
Dan Bishop
References
1. Coleman, S (1998) Biomechanics and its application to coaching practice. In Cross, N & Lyle, J (Eds). The Coaching Process: Principles and Practice for Sport (pp131-141). Reed Educational and Professional Publishing Ltd: Oxford
2. Robertson, K (2000) Observation, Analysis and Video. The National Coaching Foundation: Leeds, UK
3. Journal of Sports Science (1991), 9 (3) pp285-297
4. Journal of Sport Behaviour (1986), 9, pp34-45
5. Hughes, MD & Franks, IM (1997). Notational Analysis of Sport, E & FN SPON: London
6. Journal of Sports Science (2002) 20, pp739-754
performance analysis, coaching, training
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