Advertisement

Methodology and Computing in Applied Probability

, Volume 12, Issue 4, pp 659–665 | Cite as

Runs of Markov Chains and Streaks in Baseball

  • José Luis Palacios
Article

Abstract

We find the almost sure limits of the proportions of the total number of runs, and of the number of runs of a given length, over the number of transitions, for the states of a finite irreducible Markov chain. We apply these results to the streaks of wins and losses of the Chicago White Sox in the years 1999 through 2008.

Keywords

Runs Streaks Baseball 

AMS 2000 Subject Classifications

Primary 60J10 Secondary 60J20 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bar-Eli M, Avugos S, Raab M (2006) Twenty years of “hot hand research”: review and critique. Psychol Sport Exerc 7:525–553CrossRefGoogle Scholar
  2. Feller W (1968) An introduction to probability theory and its applications, vol I, 3rd edn. Wiley, New YorkGoogle Scholar
  3. Kemeny JG, Snell JL (1960) Finite Markov chains. Van Nostrand, PrincetonMATHGoogle Scholar
  4. Martin DEK (2006) Hot-hand effects in sports and a recursive method of computing probabilities for streaks. Comput Oper Res 33:1983–2001MATHCrossRefGoogle Scholar
  5. Norris JR (1997) Markov chains. Cambridge University Press, CambridgeMATHGoogle Scholar
  6. Schbath S (2000) An overview on the distribution of word counts in Markov chains. J Comput Biol 7:193–201CrossRefGoogle Scholar
  7. Vergin RC (2000) Winning streaks in sports and the misperception of momentum. J Sport Behav 23:181–197Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Departamento de Cómputo Científico y EstadísticaUniversidad Simón BolívarCaracasVenezuela

Personalised recommendations