An iterative Markov rating method
Devlin Stephen (),
Treloar Thomas,
Creagar Molly and
Cassels Samuel
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Devlin Stephen: Mathematics, University of San Francisco, San Francisco, CA, USA
Treloar Thomas: Mathematics, Hillsdale College, Hillsdale, MI, USA
Creagar Molly: University of San Francisco, San Francisco, CA, USA
Cassels Samuel: Hillsdale College, Hillsdale, MI, USA
Journal of Quantitative Analysis in Sports, 2021, vol. 17, issue 2, 117-127
Abstract:
We introduce a simple and natural iterative version of the well-known and widely studied Markov rating method. We show that this iterative Markov method converges to the usual global Markov rating, and shares a close relationship with the well-known Elo rating. Together with recent results on the relationship between the global Markov method and the maximum likelihood estimate of the rating vector in the Bradley–Terry (BT) model, we connect and explore the global and iterative Markov, Elo, and Bradley–Terry ratings on real and simulated data.
Keywords: Elo; Markov; ranking; rating (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:jqsprt:v:17:y:2021:i:2:p:117-127:n:4
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DOI: 10.1515/jqas-2019-0070
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