Tracking and Comparing Self-Determined Motivation in Elite Youth Soccer: Influence of Developmental Activities, Age, and Skill
Bibliographic record
Abstract
Purpose: Our aim was to determine if self-determined motivation (SDM) in elite, men’s soccer changes over time and differs as a function of age, skill-grouping, and engagement in soccer play and practice. We tested predictions from the Developmental Model of Sport Participation (DMSP) regarding relations between practice and play and SDM among both elite and non-elite samples. Methods: Elite youth soccer players in the UK (n = 31; from the Under 13/U13 yr and U15 yr age groups) completed practice history and motivation questionnaires at time1 (T1) and ~2 years later (T2: now U15 yr & U17 yr). Non-elite players (n = 32; from U15 yr and U17 yr) completed the same questionnaires at T2 only. Results: For the elite groups, global SDM decreased over time for the current U17 group (from U15), but no change was seen for the current U15 group (from U13). Age group differences at T2 mirrored these data, with U17 players showing lower global SDM and higher controlled motivation than U15 elites. The non-elite players did not show age group differences, but elites scored higher for global SDM and autonomous motivation than non-elites. The recent hours accumulated in practice negatively correlated with global SDM in elite and non-elite groups, but play was unrelated to measures of motivation. Conclusions: Differences in SDM as a function of age and skill point towards the dynamic nature of these motivations over time, likely a result of proximity to external rewards related to professional status. Although high volumes of practice are related to lower global SDM in both skill groups, the absence of any relations between SDM and soccer play does not support a key prediction related to the DMSP.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".