Notational Analysis of Elite Men's Water Polo Related to Specific Margins of Victory.
Bibliographic record
Abstract
The present study aimed to analyze the water polo matches of the men's World Championships, comparing technical and tactical aspects of winning and losing teams, during closed (≤ 3 goals of margin of victory at the end of the 4(th) quarter; winning, W; losing, L) and unbalanced (>3 goals; winning, MW; losing, ML) games. Therefore, 42 of the 48 (6 were draw at end of the 4(th) quarter) matches were considered. According to each game situation (i.e., even, counterattack, power-play, transition), a notational analysis was performed in relation to the following aspects: occurrence of actions, action outcome, execution and origin of shots, and mean duration. In addition, the occurrence of the offensive (and role) and defensive arrangements of even and power-play were analyzed. To show differences (p < 0.05) in terms of margin of victory, an analysis of variance was applied. Although ML (74 ± 11%) performed more even actions than W (68 ± 7%) and MW (69 ± 6%), the latter teams (W = 9 ± 6%; MW = 13 ± 6%) performed more counterattacks than L (3 ± 2%) and ML (5 ± 5%). Power-play is more played during closed (W = 20 ± 3%; L = 22 ± 3%) than unbalanced games (MW = 17 ± 4%; ML = 16 ± 7%). Moreover, differences in terms of margin of victory emerged for mean duration (even, power-play, transition), action outcome (even, power-play), zone origin (even, counterattack, power-play) and technical execution (even, power-play) of shots, and even and power-play offensive (and role) and defensive arrangements. Divergences mainly emerged between closed and unbalanced games, highlighting that the water polo matches of the men's World Championships need to be analyzed either considering the winning and losing outcome of match and specific margins of victory. Thus, coaches can advance their knowledge, considering that closed and unbalanced games are largely characterized by the opponent's exclusion fouls to perform power-play actions, and by a divergent grade of defensive skills regardless of game situation, respectively. Key pointsThe water polo matches of the men's World Championships need to be analyzed considering successful/unsuccessful teams as well as specific margins of victory.Closed matches are mainly characterized by a high occurrence of the opponent's exclusion fouls to perform the power-play actions.For the unbalanced matches, a divergent grade of defensive skills between teams has been highlighted.Coaches can improve their training, considering the opponent's exclusion fouls to perform the power-play actions towards a closed match, and caring the defensive skills of each game situation towards an unbalanced match.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".