Learning Soccer-Team Vecors
Reference
- Müller, R., Langer, S., Ritz, F., Roch, C., Illium, S., and Linnhoff-Popien, C. 2020. Soccer Team Vectors. Machine Learning and Knowledge Discovery in Databases: International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part II, Springer International Publishing, 247–257.
This study introduces STEVE (Soccer Team Vectors), a novel method for generating real-valued vectors representing soccer teams, organized so that similar teams are proximate in vector space. Utilizing publicly available match data, these vectors facilitate various machine learning applications, notably excelling in team market value estimation and enabling effective similarity search and team ranking. STEVE demonstrates superior performance over competing models in these domains. For further details, please consult the work by [Müller et al. 2020].
