Syncing to perform: A longitudinal case study of emotional and physiological synchrony in a team of male volleyball athletes
Bibliographic record
Abstract
Participation in group activities predicts feelings of connection with other group members that can enhance performance coordination. However, there is limited research exploring whether team routines predict perceptions of emotional synchrony, physiological synchrony, and performance outcomes in sport. The purpose of this study was to examine emotional and physiological synchrony among a team of 16 male university volleyball athletes over two months using a case study approach (Stake, 2005). Athletes participated in a pre-practice group visualization routine while wearing bioharnesses to continuously measure heart rate (HR) and heart rate variability (HRV). Athletes completed post-practice measures of emotional synchrony and individual and team performance. The coach also rated athlete and team performance. Multilevel modeling revealed time and emotional synchrony predicted higher coach ratings of team performance and higher athlete ratings of both team and athlete performance. However, emotional synchrony drove both coach and athlete performance ratings, especially early in the season. Indeed, performance ratings in the early season were lower than ratings made later in the season unless players perceived high emotional synchrony. On those days, coach and athlete's performance ratings were comparable to the higher performance ratings made later on. Visual examination of the physiological data depicted synchronization between athletes' physiological states during their pre-practice routines. This research represents a novel case study examining the association between emotional and physiological processes and performance within a team of athletes. Overall, emotional synchrony seems particularly beneficial for team performance early in the season.Acknowledgments: This research was supported by funding from the Canadian Foundation for Innovation (John R. Evans Leaders Fund) and an Early Researcher Award from Province of Ontario Ministry of Research and Innovation. We would like to thank Devin Bonk and Zoe Poucher for their assistance with data collection on this project.
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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 | 0.000 | 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) | 0.000 | 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".