The Effect of Different Attentional Focus on the Penalty Kicking Performance of Adolescent Male Soccer Players in Different Levels
Bibliographic record
Abstract
Background.Previous studies have shown that an external versus the internal focus of attention is an effective and efficient method to improve athletes' performance under anxious conditions.Objectives.The current study aimed to assess the effect of the practice with a distinct focus of attention on the penalty kicking performance of adolescent soccer players with different expertise.Methods.Twenty-four skilled and 24 novice adolescent male soccer players were recruited in the current study.Also, skill-level and age-matched goalkeepers also took part in the study to induce anxiety to the penalty takers.The penalty takers were required to practice penalty kicking toward designated target areas with either an external or internal focus of attention.Results.The results of the mixed analysis of variance (ANOVA) indicated that in the post-test, skilled adolescent soccer players demonstrated superior accuracy with an external versus internal focus (p<0.05).In contrast, the novices showed greater consistency with an internal than external focus (p<0.05).Remarkably, the better performance of accuracy in the post-test was not at the cost of kicking velocity (p>0.05).Conclusion.The current study suggests that an appropriate combination of expertise and instruction type (internal vs. external) is critical for improving the penalty kicking performance of adolescent male soccer players.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".