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Markov Decision Processes and ARIMA models to analyze and predict Ice Hockey player’s performance
Linköpings universitet, Institutionen för datavetenskap, Statistik och maskininlärning.
2019 (engelsk)Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
Abstract [en]

In this thesis, player’s performance on ice hockey is modelled to create newmetricsby match and season for players. AD-trees have been used to summarize ice hockey matches using state variables, which combine context and action variables to estimate the impact of each action under that specific state using Markov Decision Processes. With that, an impact measure has been described and four player metrics have been derived by match for regular seasons 2007-2008 and 2008-2009. General analysis has been performed for these metrics and ARIMA models have been used to analyze and predict players performance. The best prediction achieved in the modelling is the mean of the previous matches. The combination of several metrics including the ones created in this thesis could be combined to evaluate player’s performance using salary ranges to indicate whether a player is worth hiring/maintaining/firing

sted, utgiver, år, opplag, sider
2019. , s. 44
Emneord [en]
Markov Decision Processes, Arima models, Ice hockey, Ad-tree, modelling, prediction
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-154349ISRN: LIU-IDA/STAT-A--19/001—SEOAI: oai:DiVA.org:liu-154349DiVA, id: diva2:1286538
Fag / kurs
Statistics
Presentation
2019-01-14, Alan Turing, Linköping, 16:56 (engelsk)
Veileder
Examiner
Tilgjengelig fra: 2019-02-07 Laget: 2019-02-07 Sist oppdatert: 2019-02-12bibliografisk kontrollert

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