Data-Driven Player Valuation and Game Strategies in the NBA
| dc.contributor | Aalto University | en |
| dc.contributor | Aalto-yliopisto | fi |
| dc.contributor.advisor | Hekkala, Riitta | |
| dc.contributor.author | Lamberg, Oskari | |
| dc.contributor.department | Tieto- ja palvelujohtamisen laitos | fi |
| dc.contributor.school | Kauppakorkeakoulu | fi |
| dc.contributor.school | School of Business | en |
| dc.date.accessioned | 2023-09-17T16:02:54Z | |
| dc.date.available | 2023-09-17T16:02:54Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | In the dynamic and continuously evolving landscape of professional sports, the integration of data-driven approaches has become important in decision-making processes across various domains. This thesis embarks on a comprehensive exploration into the relationship between data analytics, player valuation, and game strategies within the context of the National Basketball Association (NBA). The study encompasses a literature review of data utilization in the NBA, and an exploration of its impact on game strategy, player performance assessment, and injury prevention. The research focuses on the 2022-2023 NBA season as a case study. The season’s dataset is analysed to uncover relationship between player’s on-court performance and salary. Employing regression analysis, the study unveils that offensive statistics have a bigger impact on player salaries in comparison to defensive metrics. Moreover, the study explores the role of data analytics in enhancing game strategies, player performance analysis, and injury prevention. This thesis underscores the influence of data-driven methodologies on player valuation and game strategies in the NBA. As the league continues to evolve, this research contributes a deeper understanding of how data-driven approaches are shaping the future of sports management and performance optimization. | en |
| dc.format.extent | 20+11 | |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.uri | https://aaltodoc.aalto.fi/handle/123456789/123554 | |
| dc.identifier.urn | URN:NBN:fi:aalto-202309175911 | |
| dc.language.iso | en | en |
| dc.programme | Tieto- ja palvelujohtaminen | en |
| dc.subject.keyword | sports analytics | en |
| dc.subject.keyword | data analytics | en |
| dc.subject.keyword | NBA | en |
| dc.subject.keyword | player valuation | en |
| dc.title | Data-Driven Player Valuation and Game Strategies in the NBA | en |
| dc.type | G1 Kandidaatintyö | fi |
| dc.type.ontasot | Bachelor's thesis | en |
| dc.type.ontasot | Kandidaatintyö | fi |
