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Regimes in baseball players' career data
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-8678-1164
2017 (English)In: Data mining and knowledge discovery, ISSN 1384-5810, E-ISSN 1573-756XArticle in journal (Refereed) Published
Abstract [en]

In this paper we investigate how we can use gated Bayesian networks, a type of probabilistic graphical model, to represent regimes in baseball players’ career data. We find that baseball players do indeed go through different regimes throughout their career, where each regime can be associated with a certain level of performance. We show that some of the transitions between regimes happen in conjunction with major events in the players’ career, such as being traded or injured, but that some transitions cannot be explained by such events. The resulting model is a tool for managers and coaches that can be used to identify where transitions have occurred, as well as an online monitoring tool to detect which regime the player currently is in.

Place, publisher, year, edition, pages
Springer-Verlag New York, 2017.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:liu:diva-141031DOI: 10.1007/s10618-017-0510-5Scopus ID: 2-s2.0-85019679633OAI: oai:DiVA.org:liu-141031DiVA: diva2:1143129
Available from: 2017-09-20 Created: 2017-09-20 Last updated: 2017-10-10Bibliographically approved

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Bendtsen, Marcus
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf