Importance of attack speed in volleyball

Fellingham Gilbert W. (), Hinkle Lee J. and Hunter Iain
Additional contact information
Fellingham Gilbert W.: Department of Statistics, Brigham Young University
Hinkle Lee J.: Brigham Young University
Hunter Iain: Brigham Young University

Journal of Quantitative Analysis in Sports, 2013, vol. 9, issue 1, 87-96

Abstract: In this paper we examine the relationship of the speed of a set in volleyball with the outcome of the attack. A total of 1777 sets of a single male university level volleyball team were photographed using high speed cameras so that the time the set was in the air could be measured with accuracy to 1/100th of a second. Data were analyzed using a logistic regression model implemented using the Bayesian paradigm. Using these methods the probability of a kill resulting from a set of a particular speed could be calculated. In general, sets that traveled a further distance had significant increases in the probability of success with a faster set. No trends were seen with sets that were delivered to hitters that were closer to the setter. Decreasing outside set time from 1.53 to 0.85 s, significantly increased probability of a kill from 0.31 to 0.58 for the team studied. The speed of the set when the attacker is not near the setter appears to be an important component in the success of the attack in male collegiate volleyball.

Keywords: Bayca models; kill probability; logistic model; posterior probability (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://doi.org/10.1515/jqas-2012-0049 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:jqsprt:v:9:y:2013:i:1:p:87-96:n:8

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/jqas/html

DOI: 10.1515/jqas-2012-0049

Access Statistics for this article

Journal of Quantitative Analysis in Sports is currently edited by Mark Glickman

More articles in Journal of Quantitative Analysis in Sports from De Gruyter
Bibliographic data for series maintained by Peter Golla ().