Examining the Attacks After the 20th Scores in Volleyball According to Nationality and Positions
Notice bibliographique
Résumé
The most efficient technique of scoring in volleyball is possible to be mentioned as attack. The numbers of efficient attacks performed after the 20th scores during the match are more important, and therefore this period should be managed more elaborately in terms of the technique and tactic. Therefore, it is considered that players’ presenting more productive performances with the drills related to the match after the trainings will be more efficient upon winning the match. The purpose of this study was to investigate the attacks performed after the 20th scores in 2017-2018 Volleyball Sultans League session according to the nationalities and positions. The study included totally 124 female players with natives (n=86) and foreigners (n=38) from 12 teams between 26 and 30 years old (28.25±1,62).  The numbers of the attacks performed after the 20th scores of 17.918 rallies in 496 sets (except from the 5th set) of 125 matches played by 12 teams during the session were evaluated. All matches were recorded with a video recorder by the researcher. The videos were analyzed by the experts in 3 repetitions. Attack errors, blocked attack, bad attacks, good attacks, numbers of attacks, coverage and totals numbers of attacks performed after the 20th scores during the match were recorded in numbers. Lilliefors Kolmogorov-Smirnov Test indicated whether the study data were appropriate for the normal distribution or not (p<.05). In data analysis, descriptive statistics such as number, percentage, arithmetic average and standard deviation were used; and Independent Samples T-Test and One-Way Variance Analysis (One-Way ANOVA) were used for determining the difference between dependent and independent variables. Tukey HSD Post-Hoc test was performed for finding among which groups there were differences between the units in one-way variance analysis (ANOVA). While interpreting the data, 0.01 and 0.05 were accepted as the level of significance. The research data were analyzed using SPSS 21 statistical software. As result of the findings obtained in the study, it was determined that there were significant differences in whole attacks performed by the players in terms of nationalities and positions (p<0.05). In conclusion, because the 20th scores are referred the critic period called as the golden scores, foreigners and opposite spiker’s that had high level conditional abilities for winning had more attacks.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».