Group cohesion in football: a scoping review and bibliometric analysis (1996-2024)
Bibliographic record
Abstract
Introduction: Group cohesion, understood as the dynamic process that reflects a team’s tendency to remain united in the pursuit of common goals and achieving the socio-affective needs of its members, is a decisive factor for performance in team sports. In football, however, while technical and tactical advances are extensively documented, human and social dimensions remain less explored, resulting in a fragmented body of literature. Objective: To map and analyse the scientific production on group cohesion in football published between 1996 and 2024. Methodology: A scoping review supported by bibliometric techniques was conducted using data collected from Scopus and Web of Science. Sixty-four articles were identified and examined with regard to temporal evolution, authorship networks, journals, instruments employed, geographical distribution, and sample characteristics. Results: Studies predominantly involved male youth samples, with limited participation of coaches and elite clubs. The scientific output also revealed temporal trends and networks of collaboration among authors, with greater concentration in Spain and Canada. Discussion: The findings confirm the fragmented nature of the field and the under-representation of women’s and elite-level football, contrasting with the recognised importance of cohesion for sporting success. Conclusions: Significant gaps were identified in the literature, reinforcing the need to broaden methodological and sample diversity. This study provides a comprehensive overview to guide future research and support team management strategies, such as the systematic application of validated instruments.
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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 | 0.037 | 0.134 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.227 | 0.192 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| 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".