Attacking styles of play in football: a comparison between UEFA Champions League and Copa Libertadores da América
Bibliographic record
Abstract
This investigation aimed to compare the attacking styles of play (ASPs) between participants in the UEFA Champions League (UCL) and Copa Libertadores de América (CLA). 224 matches from the round of 16 to the semi-finals were analysed, including UEFA Champions League (n = 112, seasons 2017–2019 and 2020–2022) and Copa Libertadores (n = 112, seasons 2019–2022), comprising 31 teams from UCL and 37 teams from CLA. Nine key attacking performance indicators related to ball possession, corner kicks, shots on goal, and goals scored were collected. Hierarchical cluster analysis was performed to distinguish different ASPs, and an association measure was used to identify the key performance indicators that differentiate these styles. UCL teams exhibited a broader range of ASPs compared to CLA teams, demonstrating greater variability. Ball possession indicators were found to be significant in differentiating the ASPs. UCL teams showed a preferred ASP while also employing other styles to diversify their attacking behaviour. In contrast, CLA teams favoured two preferred ASPs, a pattern that became more pronounced as the tournaments progressed. In conclusion, European and South American teams display differences in both the quantity and preference for attacking styles across different phases of their respective continental competitions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".