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Predicting Season Outcomes for the NBA

González Dos Santos, Teno (author)
Linköpings universitet
Wang, Chunyan, 1972- (author)
Linköpings universitet,Institutionen för datavetenskap,Tekniska fakulteten
Carlsson, Niklas, 1977- (author)
Linköpings universitet,Databas och informationsteknik,Tekniska fakulteten,IDA/ADIT
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Lambrix, Patrick, Professor, 1965- (author)
Linköpings universitet,Databas och informationsteknik,Tekniska fakulteten,Swedish e-Science Research Centre, Stockholm, Sweden,IDA/ADIT
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 (creator_code:org_t)
2022-04-30
2022
English.
In: Machine Learning and Data Mining for Sports Analytics. - Cham, Switzerland : Springer. - 9783031020438 - 9783031020445 ; , s. 129-142
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • Predicting game or season outcomes is important for clubs as well as for the betting industry. Understanding the critical factors of winning games and championships gives clubs a competitive advantage when selecting players for the team and implementing winning strategies. In this paper, we work with NBA data from 10 seasons and propose an approach for predicting game outcomes that is then used for predicting which team will be champion and which stages a team will reach in the playoffs. We show that our approach has a similar performance as the odds from betting companies and does better than ELO.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Keyword

sports analytics
basketball

Publication and Content Type

ref (subject category)
kon (subject category)

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