FIFA/Coca-Cola World Rankings on the Predictability of the Men’s and Women’s FIFA World Cup: A Comparative Analysis
Bibliographic record
Abstract
Since 1992, the International Federation of Association Football (FIFA) has been ranking senior men’s national soccer teams based on a variety of criteria. In 2003, FIFA extended the FIFA/Coca-Cola World Rankings into ranking senior women’s national soccer teams. The FIFA/Coca-Cola World Rankings published just before the 1994 FIFA World Cup USA, 1998 FIFA World Cup France, 2002 FIFA World Cup Korea/Japan, 2006 FIFA World Cup Germany, 2010 FIFA World Cup South Africa, 2014 FIFA World Cup Brazil, 2018 FIFA World Cup Russia, 2003 FIFA World Cup USA, 2007 FIFA World Cup China, 2011 FIFA World Cup Germany, 2015 FIFA World Cup Canada, and the 2019 FIFA World Cup France were considered. These rankings were compared to the final results of those FIFA World Cups based on two different methods of displaying the teams finish and were analyzed. Of the top 16 teams in each of the Men’s FIFA World Cups, 74.1% of those teams advanced to the Round of 16. Meanwhile, 83.9% of the top 12 teams in each of the Women’s FIFA World Cups advanced to the Round of 16 or Quarterfinals. The Pearson correlation coefficient between the Pre-Tournament rankings and final results was calculated using both ranking methods. The Women’s World Cups had higher Pearson correlation coefficients for both methods than the Men’s World Cups. In addition, the Women’s World Cups had higher t-values and z-scores than the Men’s World Cup when tested for independence and association between the Pre-Tournament rankings and final results using both ranking methods. These findings indicate that the Women’s World Cups were more predictable than Men’s World Cups based on the FIFA/Coca-Cola World Rankings.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".