"Elite Sports: Challenges of Data collection and information extraction"

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dc.contributor.advisor Djordjilovic, Vera it_IT
dc.contributor.author Mailat, Denisa Ioana <1998> it_IT
dc.date.accessioned 2023-10-02 it_IT
dc.date.accessioned 2024-02-21T12:17:43Z
dc.date.issued 2023-10-27 it_IT
dc.identifier.uri http://hdl.handle.net/10579/25446
dc.description.abstract This work's overall objective is to highlight the difficulties that arise when working with data in the present time and with nowadays tools through the analysis of elite sports data. In particular, this dissertation's purpose is two-fold. Firstly, we aim to perform a trend analysis in salary increases for two of the most practiced and popular sports in history - Basketball and Tennis - to identify possible gender differences in these growths, or other relevant insights. Secondly, we aim to explain in detail the process we have gone through in building and refining the data set for our analysis with a particular focus on the challenges and questions that subsequently arose from this process. Taking into consideration data from the American female and male basketball leagues, respectively the WNBA and NBA, we perform a statistical analysis intending to find possible and meaningful differences in how player's wages increased over time. We also perform a similar analysis for the singles winners' prizes of the four Grand Slams in the calendar year. it_IT
dc.language.iso en it_IT
dc.publisher Università Ca' Foscari Venezia it_IT
dc.rights © Denisa Ioana Mailat, 2023 it_IT
dc.title "Elite Sports: Challenges of Data collection and information extraction" it_IT
dc.title.alternative Elite Sports: Challenges of Data Collection and Information Extraction it_IT
dc.type Master's Degree Thesis it_IT
dc.degree.name Data analytics for business and society it_IT
dc.degree.level Laurea magistrale it_IT
dc.degree.grantor Dipartimento di Economia it_IT
dc.description.academicyear LM_2022/2023_sessione-autunnale it_IT
dc.rights.accessrights embargoedAccess it_IT
dc.thesis.matricno 869412 it_IT
dc.subject.miur SECS-S/01 STATISTICA it_IT
dc.description.note it_IT
dc.degree.discipline it_IT
dc.contributor.co-advisor it_IT
dc.date.embargoend 2025-02-20T12:17:43Z
dc.provenance.upload Denisa Ioana Mailat (869412@stud.unive.it), 2023-10-02 it_IT
dc.provenance.plagiarycheck Vera Djordjilovic (vera.djordjilovic@unive.it), 2023-10-16 it_IT

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