Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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
Predicting the NHL playoffs with Poisson regression
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
2017 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Using historical data from the past two seasons of the National Hockey League, three different prediction models based on Poisson regression are developed. The aim is to determine whether taking into account the recent form of a team as well as data from how they have previously performed against their opponent can help make better predictions of how many goals they will score against this opponent and thereby calculate the likelihood of each outcome. The three models are evaluated using different measures, for example comparing the odds yielded by the models against the odds of bookmakers. Different ways to account for recent form are discussed. The paper concludes that using recent form and head-to-head data will indeed improve predictions.

Place, publisher, year, edition, pages
2017.
Keyword [en]
Predicting, Poisson regression
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:uu:diva-323435OAI: oai:DiVA.org:uu-323435DiVA: diva2:1106292
Subject / course
Statistics
Educational program
Bachelor Programme in Business and Economics
Supervisors
Examiners
Available from: 2017-06-15 Created: 2017-06-07 Last updated: 2017-06-15Bibliographically approved

Open Access in DiVA

fulltext(548 kB)16 downloads
File information
File name FULLTEXT01.pdfFile size 548 kBChecksum SHA-512
f7b1bd4ee55b747d0f5e3004eb2409bfcb8527130142bed9035f44d935ff1b206d4f941ed1914e061e7fb31123f7140f33988ae69ac41b42132b5bcb7be1404b
Type fulltextMimetype application/pdf

By organisation
Department of Statistics
Probability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar
Total: 16 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 148 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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