Basketball Data Science

Paola Zuccolotto and Marica Manisera are, respectively, Full and Associate Professor of Statistics at the University of Brescia. Paola Zuccolotto is the scientific director of the Big & Open Data Innovation Laboratory (BODaI-Lab), where she coordinates, together with Marica Manisera, the international project Big Data Analytics in Sports (BDsports). They carry out scientific research activity in the field of Statistical Science, both with a methodological and applied approach. They authored/co-authored several scientific articles in international journals and books, participated to many national and international conferences, also as organizers of specialized sessions, often on the topic of Sports Analytics. They regularly act as scientific reviewers for the world’s most prestigious journals in the field of Statistics. Paola Zuccolotto is a member of the Editorial Advisory Board of the Journal of Sports Sciences, while Marica Manisera is Associate Editor of the Journal of Sports Analytics; both of them are guest co-editors of special issues of international journals on Statistics in Sports. The International Statistical Institute (ISI) delegated them the task of revitalizing its Special Interest Group (SIG) on Sports Statistics. Marica Manisera is the Chair of the renewed ISI SIG on Sport. Both of them teach undergraduate and graduate courses in the field of Statistics and are responsible for the scientific area dedicated to Sport Analytics at the PhD “Analytics for Economics and Management” of the University of Brescia. They also teach courses and seminars on Sports Analytics in University Masters on Sports Engineering and specialized training projects devoted to people operating in the sports world. They supervise students’ internships, final reports and master’s theses on the subject of Statistics, often with applications to sport data. They also work in collaboration with high-school teachers, creating experimental educational projects to bring students closer to quantitative subjects through Sport Analytics.

1. Introduction. 2. Finding Groups in Data. 3. Finding Structures in Data with Machine Learning. 4. Modelling Relationships in Basketball. 5. Concluding Remarks and Future Perspectives.