Analysis of factors that affect the standard of soccer in africa: the case of east african countries
Bibliographic record
Abstract
IntroductionSoccer or association football is the world's most popular sport being played in every nation without exception (Reilly, 1996). The sport is played by millions of people and has billions of fans and supporters all over the world including 205 playing nations and members of Federation of International Football Association (FIFA). Indeed, the game is rated Africa's best sport with 53 countries affiliated to Confederation of African Football (CAF) and the Federation of International Football Association (FIFA).Efforts directed towards development of soccer in Africa have seen several management and administrative structures of the sport being setup at continental, regional and national levels. Further more, due to the popularity of the sport, most of the African countries have invested heavily in it, so as to bring about success. Indeed Kgathi (2003) noted that achievements of national teams at International competitions often bring glory and stirs nationalistic sentiments to both the leadership and citizenly. However, there has been limited success by most African countries in international tournaments especially at World Cup. Aptly, it is only soccer teams from Cameroon, Nigeria, Senegal and Ghana which have reached the quarter finals of the World Cup.The performance at the continental level of the three East African countries is dismal. This is more so as none of East African countries has ever reached the World Cup finals, Olympics or even won the African Cup of Nations that is held every two years since 1957 (Njororai 2000, 2003).For example, Nyanjom (2010), observed that football in Kenya has suffered through the years from corruption, mismanagement and political intrigue resulting in the countries failure to make any significant impact in regional, continental or global competitions.The unimpressive performance of African teams at the World Cup and the FIFA/Coca-Cola world rankings have consistently shown that the standard of football in Africa is very low. Specifically, the standards of soccer in East Africa are even lower compared to North West and South African Countries. It is against this background that it was necessary to establish factors that affect the standard of the sport in East African region. Sport administration in Kenya suffers from multiple problems including weak financial management and leadership, poor governance and failure to invest in youth programmes.Schnabel in Singh (1982) defined sports performance as the unity of process and results of a sports motor action or of a complex sequence of action measured or evaluated according to agreed socially determined norms. Such evaluations lead to the eventual ranking of teams. On the basis of ranking, African teams are way behind other continents such as South America and Europe. The countries that have excelled in international soccer competitions also have better political, economic, social and cultural conditions which are indispensable for producing outstanding players (Singh, 1982). However isolated cases exist where countries such as Brazil and Argentina with not so elaborate economies have dominated soccer at the global scene for a long period of time. The prevailing conditions in a country serve as a medium in which sports training can be effectively carried out. The current study therefore emphasized on how a personnel (environmental) factors influence soccer development in Kenya, Uganda and Tanzania. It is acknowledged that sports performance is a complete matrix of a combination of both a personnel and personal factors such as physiological, biochemical, biomechanical, skill traits, body composition and somatotypes (Salmela, 1992). Therefore, the personnel factors investigated in this study include facilities, equipment, funding, incentives and quality of technically trained personnel. Studies done in East Africa on soccer have pointed out the technical and tactical inadequacies of the teams especially in Kenya (Njororai, 2000) and the organizational weakness of soccer in Uganda (Waiswa, 2005). …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".