Please use this identifier to cite or link to this item: http://hdl.handle.net/11718/14019
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dc.contributor.authorRastogi, Siddhartha K.-
dc.date.accessioned2015-07-07T12:12:21Z-
dc.date.available2015-07-07T12:12:21Z-
dc.date.issued2015-
dc.identifier.citationRastogi, S.K.. (2015). What’s a cricketer's worth?: Predicting bid prices for Indian Premier League auctions. 4th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence. Ahmedabad Indian Institute of Management, Ahmedabad.en_US
dc.identifier.urihttp://hdl.handle.net/11718/14019-
dc.description.abstractIndian Premier League is a tournament of twenty-over format cricket, played between teams representing different cities of India. It started in the year 2008 and has established itself over past six editions as a grand annual sports marketing affair. The team franchises as well as cricketers are auctioned every season under certain conditions. Despite such wealth of information, the studies on IPL auctions are rare barring the three cited models. The present paper studies the results of the year 2011 English-style auction of cricketers and recalibrates the old yet most accurate model so far presented by Rastogi and Deodhar (2009). Both the models use ordinary least square method of regression albeit with different variable. The old model lacks predictive power, whereas the recalibrated model presented in this model displays better predictive capability. It also succeeds in reducing overall predictability gap as well as stands significantly parsimonious vis-à-vis all the previously proposed models. Further, the final model presented is applied on 2013 and 2014 auction data to show superior results.en_US
dc.language.isoenen_US
dc.publisherIndian Institute of Management, Ahmedabaden_US
dc.relation.ispartofseriesIC 15;003-
dc.subjectIndian Premier League (IPL)en_US
dc.subjectTwenty-20 Cricketen_US
dc.subjectAuction Price of Cricketersen_US
dc.titleWhat’s a cricketer's worth?: Predicting bid prices for Indian Premier League auctionsen_US
dc.typeArticleen_US
Appears in Collections:4th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence

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