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Cricket Analytics

Resource type
Thesis type
(Thesis) Ph.D.
Date created
2015-12-16
Authors/Contributors
Abstract
This thesis consists of a compilation of three research papers and a non-statistical essay.Chapter 2 considers the decision problem of when to declare during the third innings of atest cricket match. There are various factors that affect the decision of the declaring teamincluding the target score, the number of overs remaining, the relative desire to win versusdraw, and the scoring characteristics of the particular match. Decision rules are developedand these are assessed against historical matches. We observe that there are discrepanciesbetween the optimal time to declare and what takes place in practice.Chapter 3 considers the determination of optimal team lineups in Twenty20 cricket where alineup consists of three components: team selection, batting order and bowling order. Viamatch simulation, we estimate the expected runs scored minus the expected runs allowed fora given lineup. The lineup is then optimized over a vast combinatorial space via simulatedannealing. We observe that the composition of an optimal Twenty20 lineup sometimesresults in nontraditional roles for players. As a by-product of the methodology, we obtainan “all-star” lineup selected from international Twenty20 cricket.Chapter 4 is a first attempt to investigate the importance of fielding in cricket. We introducethe metric of expected runs saved due to fielding which is both interpretable and is directlyrelevant to winning matches. The metric is assigned to individual players and is based ona textual analysis of match commentaries using random forest methodology. We observethat the best fielders save on average 1.2 runs per match compared to a typical fielder.Chapter 5 is a non-statistical essay of two cricketing greats from Sri Lanka who establishednumerous world records and recently retired from the game. Though their record-breakingperformances are now part of cricketing statistics, this chapter is not a contribution whichadds to the statistical literature, and should not be regarded as a component of the thesisin terms of analytics.
Document
Identifier
etd9381
Copyright statement
Copyright is held by the author.
Permissions
This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Scholarly level
Supervisor or Senior Supervisor
Thesis advisor: Swartz, Tim
Download file Size
etd9381_GPerera.pdf 609.22 KB

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