|  | Current Issues | No.58 January 2010 |
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The Global Sporting Arms Race: an International Comparison of the Sport Policy Factors Leading to International Sporting Success Veerle De Bosscher, Jerry Bingham, Simon Shibli, Maarten van Bottenburg and Paul De Knop |
1. Context From 2004 to 2008, a consortium of research groups initiated an international comparative study on elite sports policies in six nations. Their common purpose was reflected in the name “SPLISS”, which stands for Sports Policy factors Leading to International Sporting Success. The SPLISS study has resulted in a range of new insights into the key success drivers, and the way elite sport policies of nations evolve in an environment of increasing competition (De Bosscher, Bingham, Shibli, Van Bottenburg and De Knop, 2008). As a follow-up, the SPLISS group will continue their project in several directions and invites researchers, governments, Olympic Committees, national sport agencies and national governing bodies/federations to be involved in future studies. More information: veerle.de.bosscher@vub.ac.be 2. Introduction Over the last few decades, the power struggle between nations to win medals in major international competitions has intensified. This has led to national sports organisations and governments throughout the world spending increasing sums of money on elite sport. In their quest for international success in a globalising world, the elite sports systems of leading nations have become increasingly homogeneous. More than ever before, they are based around a single model of elite sports development with only slight variations (Bergsgard, Houlihan, Mangset, Nodland and Rommetvedt, 2007; Green and Houlihan, 2005). The fundamental principle of what has been described as ‘a global sporting arms race’ is that international sporting success can be produced by investing strategically in elite sport. Several nations have indeed shown that accelerated funding in elite sport can lead to an increase in the number of medals won at the Olympic Games. Nevertheless, in spite of increasing competition and the homogenisation of elite sports systems, the optimum strategy for delivering international success is still unclear. This makes it difficult for sports managers and policy makers to prioritise and to make the right choices in elite sports policy. The lack of an empirically-grounded, coherent theory on the factors determining international sporting success lies at the root of this research project. To start with, however, we have carried out an experimental pilot study in six sample nations: the United Kingdom, the Netherlands, Belgium (Flanders and Wallonia separately), Italy, Norway and Canada. This paper presents a summary of some of the results (De Bosscher et al., 2008). The measurement of world competitiveness is routinely used in economic studies to provide a framework to assess how nations manage their economic future (Garelli, 2008, p1). By looking at how competitiveness is measured in the economic sector, the SPLISS study explored a method to assess how nations might manage their future success in international sporting competitions. 3. Conceptual model The development of a theoretical model builds on our earlier work (De Bosscher, De Knop, van Bottenburg and Shibli, 2006). A qualitative exploration of literature, secondary sources and two case studies revealed that all key success drivers which can be influenced by policies can be distilled down to nine key areas or ‘pillars’, as presented in Figure 1. These pillars are situated at two levels: inputs (reflected in pillar 1, as the financial support for sport and elite sport) and throughputs (which are the processes of “what” is invested and “how” it is realised, reflected in pillars 2-9). Throughputs can be seen as a measurement of efficiency of elite sport systems as they describe the way certain inputs may lead to the desired output. Outputs in elite sport can be clearly defined in terms of actual performance and this issue is covered in depth after the methodology. Criteria or critical success factors (CSF) have been developed to operationalise the nine pillars into logically derived and measurable sub-components. 103 CSF have been included in this study to compare elite sport policies in six nations. Figure 1: SPLISS model: a conceptual model of 9 pillars of Sports Policy factors Leading to International Sporting Success (De Bosscher et al., 2006) 4. Methodology Data Collection Research data were collected in two ways. First, all participating nations undertook to survey elite athletes, coaches and co-ordinators (Performance Directors), using written questionnaires, prior to the 2004 Athens Olympics in order to benchmark the 'elite sports climate' and to facilitate cross national comparisons on selected variables common to all surveys. A total of 1090 elite athletes, 253 coaches and 69 performance directors in the six nations responded to the questionnaires. Second, researchers in each nation completed an extensive semi-structured questionnaire with open and closed questions on diverse aspects of nations' overall sport policies with particular reference to elite sport (and its evolution over the past ten years). This questionnaire was known as the 'policy' questionnaire and contained 84 questions, the answers to which ran to in excess of 30 pages per nation. In this regard the SPLISS project is one of the largest data collection exercises of its type ever conducted. The unique feature of the research is that in addition to measuring easily quantifiable variables such as inputs (e.g. money) and outputs (e.g. medals) it has also tried to assess the 'black box' of throughput both in terms of the existence of various system components and also the rating that athletes, coaches and Performance Directors gave to these system components. Data analysis: Development of a Scoring System The data were subsequently transformed into a scoring system to measure the competitive position of nations and thus facilitate the comparison of elite sport policies to be made less descriptively. Reflecting recognised principles of economic competitiveness measurement, scores for each criterion were aggregated into an overall score for each pillar, which in turn has led to the production of an 'at a glance' comparative analysis of each nation against each pillar. 5. Results Output: Measuring Success of Nations IN Elite Sport If nations are adopting a strategic approach to the production of elite athletes, then part of that process must be to evaluate the results achieved (outputs). Table 1 shows that defining success is a tremendously difficult exercise. When a diverse portfolio of 60 sports is analysed (and including other events), using the World Sporting Index, the UK emerges as the most successful sporting nation in the sample largely because of the breadth of sports in which the country participates including non-Olympic and professional sports. If the portfolio of sports is narrowed down - to Summer Olympic sports only - then Italy was the most successful nation until 2004 (Athens) but is passed by the UK in Beijing. The only nation whose performance is clear is Belgium. If there is a relation between policy factors (inputs and throughputs) and performances (outputs), it may be expected that Belgium (both Flanders and Wallonia) does not follow the elite sport developments of the other countries. T able 1: Relative ranking of the sample nations according to different performance measures in Olympic sports, using market share.
| Market share (%)a
Nation | OG Athens | OG Beijing | OG Turin | WSI
Italy | 3.4% (1st) | 2.9% (2nd) | 4.2% (3rd) | 3.2% (2nd)
Great Britain | 3.1 %(2nd) | 5.3 % (1st) | 0.4% (5th) | 6.5% (1st)
Netherlands | 2.1 %(3rd) | 1.9 %(3rd) | 3.4% (4th) | 1.6% (5th)
Canada | 1.3 %(4th) | 1.8 %(4th) | 9.5% (1st) | 3.2% (2st)
Norway | 0.9 %(5th) | < 1.1 %(5th) | 6.2% (2nd) | 2.7% (4rd)
Belgium (Flanders)b (Wallonia) | 0.3 %(6th) (0.17%) (0.13%)> | 0.3 %(6th) (0.2%) (0.1%) | 0.0% (6th) | 0.4% (6th) - -
WSI: World Sporting Index: mixed OG Summer (S)/Winter (W) and includes other events (world level) OG: Olympic Games a Market share: a standardised measure of total achievement in an event whereby total medals won are converted into ‘points’ (gold=3, silver=2, bronze=1) and the points won by a given nation is subsequently expressed as a percentage of the total points awarded (SIRC, 2002) b Belgium: in Athens 1 gold medal was won by a Walloon athlete and 2 bronze medals by a Flemish athlete; in Beijing 1 gold medal was won by a Flemish athlete and 1 silver by a team (mixed Flanders & Wallonia) Inputs and Throughputs:Ratings Against the Nine Pillars In this section, we summarise the overall performance of each nation against the nine pillars using the series of colour coded signals shown in Figure 2 below. Figure 2: The key to pillar rating charts
| Policy area very well developed
| Good level of development
| Moderate level of development
| Limited development
| Little or no development
The following ratings provide an indication of the extent to which each policy area has been developed in each sample nation. The findings are set out in Table 3. It should be noted that these ratings are, in effect, a relative assessment of the elite sport systems of this particular group of nations. Therefore, if more nations were to be added to the sample, it is possible that we might need to adjust our ratings to take account of wider variations in practice. Figure 3: SPLISS evaluation of key success policy factor.s
| ITA | UK | NED | CAN | NOR | FLA | WAL
1(a) Financial support: National expenditure on sport |  |  |  |  |  |  |
1(b) Financial support: National governing bodies |  |  |  |  |  |  |
2. Integrated approach to policy development |  |  |  |  |  |  |
3. Participation in sport |  |  |  | NA |  |  |
4. Talent identification & development system |  |  |  |  |  |  |
5. Athletic and post career support |  |  |  |  |  |  |
6. Training facilities |  |  |  |  |  |  | NA
7. Coaching provision and coach development |  |  |  | NA | NA |  |
8. International competition (organisation events) |  |  |  |  |  |  |
9. Scientific research |  |  |  |  |  |  |
Overall, in Figure 3, there are relatively few areas in which there are significant variations between the sample nations. The absence of such discrimination lends weight to the argument about the largely homogenous approach that different nations appear to be taking to the development of their elite sport systems (Bergsgard, et al., 2007; Houlihan and Green, 2008). A Relationship between Policy and Performance? The key question concerning elite sport development posed at the beginning of this research was whether there is a relationship between the evaluation of each pillar (the inputs and the throughputs) and the output (international performances). The nation whose performance is easiest to understand is Belgium (represented jointly by Flanders and Wallonia), because the policy scores in Figure 3 for Belgium are reflective of its performance standing. The policy-output relation is less clear for the other countries. For example, although Italy performs consistently well across the range of indices we have used to measure success, no policy area in Figure 2 achieves a top rating and development is assessed as no higher than “moderate” in five policy areas. The UK and the Netherlands are within one place of each other on all of the output-indices (except from Beijing). Interestingly, there are also notable similarities in the UK and Dutch scores in our evaluation of policy (Figure 2). The remaining two countries in our sample are those with particular strength in winter sports – Canada and Norway. Of the two, Canada generally does not score as well as Norway in terms of policy evaluation. Although these findings are inconclusive in determining whether there is a relationship between the quality of elite sport systems and national performance in international sport, we have explored whether there are any alternative methods of analysing our data, which may prove instructive. Input-output relation. When we focus on nations’ performance in the Summer Olympics (given that all countries invest in summer sports, though not all do so with respect to winter sports), Italy, the UK and the Netherlands are the best performing nations. In terms of input-output analysis, these nations also allocate the highest absolute amount of funding to elite sport. Possible drivers of an effective system. Looking at these nations as a group (ITA, UK, NED), we see that the policy areas in which they achieved the highest collective rating, and thereby distinguishing themselves from the other sample countries, are Pillar 1b (funding for national sport organisations) and Pillar 7 (only with regard to coaching provision). Furthermore, it seems that all sample countries have invested increasingly in Pillar 5 (‘athletic and post career support’) -except Belgium- and in Pillar 6 (training facilities) over the past few years. It could be argued that these four pillars highlight the importance of these policy areas as key drivers of an effective system. Areas to develop a competitive advantage of nations.Figure 3 also reveals that some pillars are relatively under developed in the sample countries: pillar 4 (talent identification and development systems), Pillar 7 (especially with regard to the provisions for coaches) and pillar 9 (scientific research, with the exception of Norway). Nations may strive for an advantage in these pillars. We have conducted this analysis by plotting the rankings for each nation on each factor against the sample averages using 'radar' graphs. The radar graph for the UK is shown below in Graph 1. Graph 1: Radar graph for the UK. In Graph 1, it can be seen that the UK achieves the maximum score of '5' (policy area very well developed) for four of the ten policy factors. Furthermore, with the exception of slightly below average scores for talent identification and development and for scientific research, the UK meets or exceeds the sample average for eight of the ten policy factors. Where the UK appears to have its greatest advantage is in Pillar 1, support to National governing bodies for which the gap between its score and the sample averages is +2.2. This finding suggests that elite sport in the UK is funded considerably better than in the other sample nations. Cross referencing with Table 5 confirms that the UK is the only nation in the sample with two maximum scores for Pillars 1a and 1b. As a contrast to the UK position, Figure 5 illustrates the performance of Flanders against the sample averages using the same radar style graph used for the UK above. Graph 2: Radar graph for Flanders. Flanders appears to have a relative strength in Pillar 4 (talent identification and development) compared with the sample average. Against the other nine factors, Flanders is equal to the sample average for Pillar 3 (participation in sport) and Pillar 6 (training facilities) and below the sample average for the seven other factors. A similar analysis showing the relative strengths and weaknesses of the other five sample nations is shown in Graphs 3-7. Graph 3: Italy. Graph 4: The Netherlands. Graph 5: Canada. Graph 6: Norway. Graph 7: Wallonia. 6. Concluding Remarks In terms of input-output analysis, the best predictor of output appears to be the absolute amount of funding allocated to elite sport. Relative funding measures such as funding per capita are not really relevant as output (international sporting success) is measured in absolute rather than relative terms. But an input-output model may be too rational and economic. It is possible that elite sporting success appears to be the outcome of a multivariate process involving many variables and relationships that we are yet to discover. Conversely, from a theoretical viewpoint, the analysis also showed that nations that do not perform well in one or a few policy pillars can still be successful in Olympic sports (e.g. Italy). It may, therefore, be argued that there are different models to explain elite sporting success and that it is unrealistic to look for a convenient truth about the successful production of elite level athletes. In this regard, SPLISS will continue its activities on a broader scale: by extending the overall sport policy comparison to more nations in 2011 and by making sport by sport analysis, starting with athletics in 2009. There is a paradox inherent in the discussion throughout this report. That is, increasing global competition is encouraging nations to adopt a more strategic elite sports policy in order to differentiate themselves from other nations with the net result being an increasingly homogenous elite sports development system which is ostensibly based around a near uniform model of elite sports development with subtle local variations. Despite attempts by governments to rationalise elite sport and to treat it like a mainstream area of government policy, the reality is that international sport is a global issue not a national issue. Consequently, the rules of the game are dictated by what rival nations are doing, not on the basis of what an individual nation is doing now compared with what it did in the past. The key question facing all nations taking a strategic approach to elite sport is "to what extent do you wish to be part of this game?" References Bergsgard, N.A., Houlihan, B., Mangset, P., Nodland, S.I. and Rommetveldt, H. (2007). Sport policy. A comparative analysis of stability and change. London: Elsevier. De Bosscher, V., De Knop, P., van Bottenburg, M. and Shibli, S. (2006). A conceptual framework for analysing Sports Policy Factors Leading to international sporting success. European Sport Management Quarterly, 6 (2), 185-215. De Bosscher, V., Bingham, J., Shibli, S., Van Bottenburg, M. and De Knop, P. (2008). The global Sporting Arms Race. An international comparative study on sports policy factors leading to international sporting success. Aachen: Meyer & Meyer. ISBN: 978-1-84126-228-4. (173p). Garelli, S. (2008). Competitiveness of nations: the fundamentals. IMD World Competitiveness yearbook. http://www02.imd.ch/wcc/yearbook. Access ed 2 August 2008. Green, M. and Houlihan, B. (2005). Elite sport development. Policy learning and political priorities. London and New York: Routledge. Houlihan, B. and Green, M. (2008). Comparative elite sport development. Systems, structures and public policy. London: Elsevier. Contact Veerle De Bosscher Vakgroep Sportbeleid en Management (SBMA) Department Sports Policy and Management Vrije Universiteit Brussel Brussel, Belgium Email: vdebossc@vub.ac.be http://www.icsspe.org