Performing in the clutch: Prior exposure to pressure reduces choking in sports
Bibliographic record
Abstract
In sports, athletes are often susceptible to performance decrements when placed in high-pressure situations—a phenomenon known as In the current study, we sought to determine if the mindset participants are in affects their athletic performance in these situations. Using a simulated golf task, we examined the impact of prior exposure to differing levels of pressure on later performance in a high-pressure situation. Participants first completed a round of five putts under low (n = 39), moderate (n = 38), or high (n = 42) pressure. The mean likelihood for participants to successfully make a given shot on these five putts was not significantly different between groups (Mlow = 34.36±25.53, Mmod = 33.16±26.41, Mhigh = 37.14±25.21). Following a short break, participants completed a single putt under high pressure as a simulation of the clutch situations that commonly result in choking. A binary logistic regression revealed that participants who completed the initial round of putting under high pressure performed significantly better on the ensuing high-pressure shot than participants who had prior experience under low pressure (AŸ = 1.163; p = 0.031). The results of this study seem to support the notion that being in a high-pressure mindset or psychologically warmed-up to pressure results in stronger athletic performances in subsequent high-pressure situations than when athletes are previously in a low-pressure mindset and thrown into the fire.Acknowledgments: The authors would like to thank Dr. Karen Buro of Grant MacEwan University for her aid with the statistical analysis of this project.
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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 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".