MétaCan
Menu
Back to cohort
Record W2163071147

Notational Analysis of Elite Men's Water Polo Related to Specific Margins of Victory.

2012· article· en· W2163071147 on OpenAlex
Corrado Lupo, Giancarlo Condello, Antonio Tessitore

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePubMed · 2012
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsnot available
Fundersnot available
KeywordsVictoryCounterattackOffensiveWater poloDuration (music)Power (physics)Outcome (game theory)EliteQuarter (Canadian coin)Margin (machine learning)Operations researchPsychologyOperations managementStatisticsComputer scienceMathematicsPolitical scienceEconomicsPhysicsMathematical economicsHistoryMedicinePhysical medicine and rehabilitationLaw
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.021
GPT teacher head0.247
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it