National Teams in Women's Soccer World Cup from 1991 to 2015: Participation, Performance and Competitiveness
Bibliographic record
Abstract
IntroductionThe first Women's Soccer World Cup was held in 1991 in China. Since then, the number of teams participating in the competition is increasing as well as the number of studies about the sport (Datson et al., 2014). Most of the studies about women's soccer have investigated the sociological and physiological aspects of the sport and the frequent injuries suffered by the athletes. Just a few studies have investigated athletes and teams characteristics in this tournament.Studies about Women's World Cup analyzed the perceptions of stress and coping of the athletes during the preparatory period to the 1999 finals (Holt and Hogg, 2002), compared characteristics of women's soccer matches to men's matches in 1991 (Miyamura et al., 1997) and analyzed the offensive tactics of the quarterfinalists teams in 1999 (Konstadinidou and Tsigilis, 2005).Although analysis of international competitions, such as the World Cup and Olympic Games, provides valuable information about changes and trends among the top teams in women's soccer (Bergier et al., 2008), no study to date has examined the participation and performance of national teams throughout the editions of the championship.Studies about national women's soccer discussed about the recognition, legitimacy and visibility of women's soccer in the United States and the Netherlands (Knoppers and Anthonissen, 2003), Canada (Ann Hall, 2003), Norway (Fasting, 2003), Sweden (Hjelm and Olofsson, 2003), South Africa (Pelak, 2010) and Brazil (Votre and Mourao, 2013). However, the identification of the national teams with highest participations and performances during World Cup editions would allow inferring which countries are giving greater support and growth opportunity to the athletes.Performance of the teams can be analyzed through their final ranking in the championship or using performance indicators. The performance analysis is often facilitated if the performance indicators are expressed as ratios (Hughes and Barlett, 2002). In the case of FIFA Women's World Cup, the analysis of the goals per games ratio throughout all editions can give indications about the development of the national teams and the competitiveness among them over the years.Therefore, the first aim of this study was to analyze nation teams' participation in Women's World Cup from 1991 to 2015. The second aim was to analyze, through participation in quarterfinals and ratio of goals per game, performance and competitiveness of teams throughout the editions.Material & methodsParticipants and proceduresIn order to carry out this study, all the seven editions of Women's World Cup from 1991 to 2015 were analyzed. From each edition were collected the total goals scored, participating teams and final team rankings. From each championship were collected data from all played games.In tournaments from 1991 to 2015 there were a total of 232 played games. From 1991 to 2011 the championships were composed by five phases: group stage, quarterfinals, semi-finals, play-off for third place and final. The 2015 edition also had the round of 16 phases. Games from all the phases were analyzed.From each match were collected the participant teams and the final score of the game. From the result of each game we calculated the goal difference between the winning and losing team. Goals scored in penalty decisions were not considered in this study.All data were collected on the official website of the Federation Internationale de Football Association. Data used in this study are public and available online.Statistical analysisAll data were tabulated and arranged in Microsoft Excel worksheet and then exported to GraphPad Prism 7 (San Diego, California, USA) in which were performed all statistical analyses. Descriptive statistics were used to summarize the collected data.From the collected data were calculated the ratio of goals per game for each edition of the championship and for each participant team. …
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".