Notational Analysis of the Volleyball Serve

Ciuffarella, Andrea; Russo, Luca; Masedu, Francesco; Valenti, Marco; Izzo, R.; Angelis, Marco de

doi:10.2478/tperj-2013-0013

Cited by 24 publications

(47 citation statements)

References 11 publications

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“…Three categories of reception efficacy, adapted from existing coding schemes (Afonso et al, 2012; Ciuffarella et al, 2013), were used: error , when receiver's contact doesn't allow setting, or restricts the setting options to one; out , when the setter has to set outside the excellent setting zone, or in the setting zone, but without all setting options; and, effective , when the reception allows setting in the excellent setting zone with all setting options available to the setter. For reception efficacy, type of pass was also a considered as predictor variable.…”

Section: Methodsmentioning

confidence: 99%

Predicting Volleyball Serve-Reception

et al. 2016

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Serve and serve-reception performance have predicted success in volleyball. Given the impact of serve-reception on the game, we aimed at understanding what it is in the serve and receiver's actions that determines the selection of the type of pass used in serve-reception and its efficacy. Four high-level volleyball players received jump-float serves from four servers in two reception zones—zone 1 and 5. The ball and the receiver's head were tracked with two video cameras, allowing 3D world-coordinates reconstruction. Logistic-regression models were used to predict the type of pass used (overhand or underhand) and serve-reception efficacy (error, out, or effective) from variables related with the serve kinematics and related with the receiver's on-court positioning and movement. Receivers' initial position was different when in zone 1 and 5. This influenced the serve-related variables as well as the type of pass used. Strong predictors of using an underhand rather than overhand pass were higher ball contact of the server, reception in zone 1, receiver's initial position more to the back of the court and backward receiver movement. Receiver's larger longitudinal displacements and an initial position more to the back of the court had a strong relationship with the decreasing of the serve-reception efficacy. Receivers' positioning and movement were the factors with the largest impact on the type of pass used and the efficacy of the reception. Reception zone affected the variance in the ball's kinematics (with the exception of the ball's lateral displacement), as well as in the receivers' positioning (distances from the net and from the target). Also the reception zone was associated with the type of pass used by the receiver but not with reception efficacy. Given volleyball's rotation rule, the receiver needs to master receiving in the different reception zones; he/she needs to adapt to the diverse constraints of each zone to maintain performance efficacy. Thus, being able to flexibly vary positioning and passing, given local (zone) constraints, can yield an advantage in high-level volleyball serve-reception. Further, research needs to consider other serve modes (e.g., power-jump serve) and a full-court context of performance to support the present study's findings.

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Section: Methodsmentioning

confidence: 99%

Predicting Volleyball Serve-Reception

et al. 2016

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“…Estes possuem uma independência parcial (14) : embora cativos do sistema como um todo, criam momentos de instabilidade (ou desequilíbrio) que influenciam o sistema, levando a retornar ao estado anterior ou alcançar um novo estado de equilíbrio (3) . Apesar da complexidade de análise das partes, a sua interação fornece padrões que contribuirão para uma compreensão global sistémica (5) e para a otimização e melhoria do nível de performance competitivo (10) .…”

Section: Introductionunclassified

A importância de diferenciar o KII do KIII no Voleibol feminino de alto nível

Afonso¹,

Laporta²,

Mesquita³

2017

RPCD

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RESUMOApesar do voleibol apresentar seis complexos de jogo (K), a maioria das pesquisas dividem em apenas dois K (KI e KII). Desta forma, muita informação pode ser perdida ou tratada de modo similar, não obstante a sua divergência. A ação de contra-ataque é um exemplo, em que ela pode ocorrer como transição do side-out (KII) e transição da transição (KIII).Assim, a nossa hipótese é que existem diferenças entre as variáveis analisadas nestes dois complexos no voleibol, merecendo uma exploração cuidada. Para o efeito, recorreu-se à Análise de Redes Sociais, especificamente à centralidade de autovetor, para obter uma visão sistémica de todas as ações e perceber a sua relevância no todo. 15The importance of differentiating KII and KIII in high-level women's volleyball ABSTRACT Although volleyball features six game complexes (K), most research divide into only two K (KI and KII). In this way, much information can be lost or treated in a similar way, despite its divergence. Counter-attack action is an example, where it can occur as a side-out (KII) transition and transition of transition (KIII). Thus, our hypothesis is that there are differences between the variables analyzed in these two complexes in volleyball, deserving a careful exploration. For this purpose, we used Social Network Analysis, specifically to eigenvector centrality, to obtain a systemic view of all actions and to perceive their relevance in the whole.Thirteen matches of the final phase of the World Grand Prix 2015 were analyzed, resulting in differences in the variables between the complexes. Specifically, the KII presented greater variability in its actions compared to KIII. The results also call for the inclusion of "out-of-system" situations in training.

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“…These works have established that the jump serve is the most common type of serve in high-level men's volleyball and that a successful jump serve is the most difficult to return (Ciuffarella et al 2013;Moras et al 2008). The most common service location is the middle-back of the receiving team's side of the playing court, followed by the left-back (Ciuffarella et al 2013), from the receiving team's perspective. But serves to the right-back are the most difficult to receive (Elftmann 2013).…”

Section: Introductionmentioning

confidence: 97%

“…Various observational studies using data from Italian professional men's volleyball (Ciuffarella et al 2013), NCAA women's volleyball (Elftmann 2013) and Olympic men's volleyball (Moras et al 2008) have sought to draw conclusions about what factors make a serve difficult to receive, focusing on service type (jump, float or jumpfloat), speed, and location. These works have established that the jump serve is the most common type of serve in high-level men's volleyball and that a successful jump serve is the most difficult to return (Ciuffarella et al 2013;Moras et al 2008).…”

Section: Introductionmentioning

confidence: 99%

A linear model for estimating optimal service error fraction in volleyball

Burton¹,

Powers²

2015

Journal of Quantitative Analysis in Sports

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Volleyball coaches are frequently forced to address the question of athlete service errors as a part of their overall service strategy. This is usually done in an ad hoc fashion with an arbitrarily selected maximum allowable service error fraction or maximum allowable service error-to-ace ratio. In this article, an analysis of service outcomes leads to a mathematical expression for the point-scoring fraction in terms of service ace fraction, service error fraction, and opponent modified sideout fraction. These parameters are assumed to be monotonic functions of an athlete or team's serving aggressiveness and a linear model for the service error-to-ace ratio is used to close the point-scoring optimization problem. The model provides estimates of the optimal service error fraction for individual athletes based on their service ace fraction and the opponent modified sideout fraction against the server overall and also when restricted to only serves that led to perfect passes. Case studies of the Bay to Bay 17 Black Boys' USAV Juniors team and the Brigham Young University Men's NCAA Division I team are used to demonstrate the application of the model and standard errors for the predicted optimal service error fractions are calculated with bootstrap resampling.

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Notational Analysis of the Volleyball Serve

Cited by 24 publications

References 11 publications

Predicting Volleyball Serve-Reception

Predicting Volleyball Serve-Reception

A importância de diferenciar o KII do KIII no Voleibol feminino de alto nível

A linear model for estimating optimal service error fraction in volleyball

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