An in-depth exploration of a positional subgroup in professional sport
Bibliographic record
Abstract
An inevitable structural feature within sport teams involves ‘the groups within the group,’ otherwise known as subgroups. Although there is a large body of literature dedicated to group dynamics constructs at the total team level, little research has explored such topics at a positional subgroup level, particularly in professional sports. Thus, the purpose of this study was to provide an in-depth exploration of group dynamics perceptions from a specific positional subgroup in professional sports, with a particular emphasis on group cohesion and leadership. Specifically, we interviewed six experienced professional gridiron football offensive linemen to explore their perspectives of the factors influencing group cohesion within their positional subgroup. The analysis revealed environmental factors as well as internal roles and interpersonal processes that shaped group development and cohesion within the subgroup. Notably, the impact of veteran athlete leadership and how the behaviors of both the coaching staff and general managers could either positively or negatively influence group cohesion in professional football were apparent. Therefore, the present results are of interest to members of professional organizations generally, and gridiron football specifically, including general managers, head coaches, assistant coaches, support staff, and athletes regarding how the dynamics within a positional subgroup can impact individual and team outcomes. Lay summary: This article describes professional athletes’ opinions about group cohesion and leadership. All athletes were part of a positional subgroup in gridiron football. The analysis revealed environmental factors as well as internal roles and interpersonal processes that shaped group development and cohesion within the subgroup and the team as a whole.IMPLICATIONS FOR PRACTICEProfessional general managers seeking to build high-functioning positional subgroups whereby members are highly interdependent should consider avoiding frequent athlete turnover and providing incentives for veterans to actively engage with mentoring newcomers.Professional head and assistant coaches looking to maximize individual and team outcomes should encourage veteran athletes to establish normative expectations within their positional subgroups that are unique but align with those from the superordinate team.The complexity of the professional gridiron football environment undoubtedly means that the head coach must delegate various tasks to their assistant coaches and athlete leaders to enhance the team environment.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".