A Point-by-Point Analysis of Performance in a Fencing Match: Psychological Processes Associated with Winning and Losing Streaks
Bibliographic record
Abstract
This study aimed to revisit the complex nature of serial dependency of performance during a match, examining the prospective associations between psychological processes and subsequent performance at the within-person level of analysis, and explore whether psychological processes are associated with the likelihood of winning series of points. A process-oriented sequential approach was used with 16 elite fencers during a simulated competition. Multilevel regression analyses revealed that serial dependency of performance fluctuates within a match. Results of a Bayesian multilevel structural equation model showed that prior performance subsequently influenced psychological processes. Although psychological processes did not predict performance in the subsequent point, successive winnings were associated with higher perceived control and task-oriented coping and lower negative affectivity compared with both losing streaks and nonstreaks. Overall, serial dependencies of performance are nonstationary during a match whereas psychological processes significantly differ in episodes of winning after winning versus losing after losing.
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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 | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".