Deriving an exact batting survival function in cricket

West, M; kachoyan, B

Deriving an exact batting survival function in cricket

West, M

kachoyan, B

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Publication Type:: Conference Proceeding
Citation:: 2018
Issue Date:: 2018

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Field	Value	Language
dc.contributor.author	West, M https://orcid.org/0000-0003-0983-3407
dc.contributor.author	kachoyan, B
dc.date	2018-07-25
dc.date.accessioned	2020-06-15T00:55:58Z
dc.date.available	2020-06-15T00:55:58Z
dc.date.issued	2018
dc.identifier.citation	2018
dc.identifier.uri	http://hdl.handle.net/10453/141423
dc.description.abstract	This paper derives a general batting survival function from a minimalist set of assumptions, specifically taking into account that a different number of runs can be scored at each point of an innings. It is shown how this approaches a memoryless survival function at a moderately low score. The paper also shows that an estimate of the value of the underlying parameters can be derived from a batsman’s aggregated data summaries available from most common cricket databases. Finally the paper compares the theoretical survival function with those derived from product limit estimates (PLE) to reinforce both that the theoretical distribution is a good estimate of any underlying distribution, and that the whole PLE curve is useful for highlighting specific characteristics in the careers of individual batsmen.
dc.language	en
dc.relation.isbasedon	10.13140/RG.2.2.15169.40802
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.title	Deriving an exact batting survival function in cricket
dc.type	Conference Proceeding
utslib.location.activity	University of the Sunshine Coast
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2020-06-15T00:55:53Z
pubs.finish-date	2018-07-18
pubs.publication-status	Published online
pubs.start-date	2018-07-25

Abstract:

This paper derives a general batting survival function from a minimalist set of assumptions, specifically taking into account that a different number of runs can be scored at each point of an innings. It is shown how this approaches a memoryless survival function at a moderately low score. The paper also shows that an estimate of the value of the underlying parameters can be derived from a batsman’s aggregated data summaries available from most common cricket databases. Finally the paper compares the theoretical survival function with those derived from product limit estimates (PLE) to reinforce both that the theoretical distribution is a good estimate of any underlying distribution, and that the whole PLE curve is useful for highlighting specific characteristics in the careers of individual batsmen.

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http://hdl.handle.net/10453/141423