Abstract Details
Activity Number:
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539
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Type:
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Contributed
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Date/Time:
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Wednesday, August 7, 2013 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Sports
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Abstract - #309994 |
Title:
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A Bayesian Stochastic Model for Batting Performance Evaluation in One-Day Cricket
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Author(s):
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Theodoro Koulis*+ and Saman Muthukumarana
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Companies:
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University of Manitoba and University of Manitoba
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Keywords:
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Markov chain ;
Bayesian ;
Performance evaluation ;
Forecasting ;
Model selection
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Abstract:
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We consider a Bayesian ergodic Markov chain to model individual batting performance in one-day cricket. A cut-point vector is used to create a discrete state space for batting performance. By choosing an appropriate cut-point vector, the next performance state only depends on the current state, so that an overall prediction of batting performance of a batsman can be made. One advantage of this Markov model is that it does not require the consideration of unforeseen factors. This is important since cricket has gone through several rule changes in recent years that have further induced unforeseen dynamic factors to the game.
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Authors who are presenting talks have a * after their name.
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