Performance analysis of the flip turn in swimming: The relationship between pressures and performance times
Bibliographic record
Abstract
This study examined the effects of pressure and other kinetic variables on freestyle flip turn performance. It was hypothesized that an increase in average and peak pressure, and a decrease in the magnitude difference between left and right foot pressure, would result in an improved performance of a swimmer as they performed a flip turn. Ten University level (varsity) swimmers performed five freestyle flip turns using their competition technique. Data were collected from a pressure pad mounted to the vertical wall of the pool and from an underwater camera in the sagittal plane. A negative correlation of .58 and .67 was seen for average and peak pressures respectively when compared to five-meter performance times. Average contact area throughout the push-off phase compared to average and maximum load was .94 and .88. An increase in average contact area from 40 cm2 to 50 cm2 resulted in a 26% increase in maximum load. No difference in performance was seen for varying maximum knee flexion angles. Differences between pressure magnitudes between left and right foot did not impact the five-meter performance time. Therefore, increased average contact area throughout the push-off phase caused higher average and maximum loads, and to a lesser extent average and peak pressures. Increases in pressure and load resulted in an improved five-meter performance time. It is concluded that flip turn performance increases through higher contact area with the feet when pushing off the wall.
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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 | 0.000 |
| 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".