Time-Motion Analysis of Elite Male Kickboxing Competition
Bibliographic record
Abstract
The objective of the study was to analyze the time structure of high-level kickboxing matches. A total of 45 combats from 2 male World Championships were monitored using a time-motion analysis system. The combat time structure (i.e., high-intensity activity [HIA], low-intensity activity [LIA], and referee breaks or pauses) during competition and weight divisions was determined and compared. Results indicated that the time structures were HIA: 2.2 ± 1.2 seconds; LIA: 2.3 ± 0.8 seconds; pauses: 5.4 ± 4.3 seconds; and 3.4 ± 1.2 seconds between 2 subsequent HIA. The fighting to nonfighting ratio was found to be 1:1. Moreover, the number of HIA and LIA and the time of LIA decreased in latter rounds (e.g., the average number of HIA was 27.1 ± 7.1, 25.1 ± 6.6, and 24.9 ± 6.1, respectively, for rounds 1, 2, and 3), meanwhile the time and number of pauses increased (e.g., the average pause times were 12.8 ± 11.4, 22.3 ± 22.6, and 24.6 ± 23.3 seconds, respectively, for rounds 1, 2, and 3). The activity times did not differ among weight categories. The present results confirm the intermittent nature of kickboxing competition and provide coaches with more information on how to structure training sessions to mimic the physical demands in competition.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".