Στατιστικά μοντέλα για την απόδοση μιας ομάδας μπάσκετ: ποια στατιστικά στοιχεία είναι καθοριστικά για την απόδοση της ομάδας, σε ετήσια βάση
Statistical models for the performance of a basketball team: which statistics in the boxscore determine the team's season-long success
Καλλιακμάνης, Διονύσιος Γ.
Nowadays, more and more data is being produced, processed and stored at a rapid pace. This explosion in the volume of data has clearly affected the field of sports, and more specifically the field of basketball. Data analytics and sports are going hand-in-hand for some time now. Statistical learning refers to a set of tools for modeling and understanding complex datasets. Sports analytics are a collection of relevant, historical, statistics that when properly applied can provide a competitive advantage to a team or individual. Through the collection and analyzation of these data, sports analytics inform players, coaches and other staff in order to facilitate decision making both during and prior to sporting events. In this study, using actual data from the most prestigious European Basketball Tournament, we will analyze with statistical and machine learning techniques, which statistics in the box-score determine the team’s season-long success. Additionally, we will perform a descriptive analysis and visualize the results through graphs, charts and tables. Afterwards, we will employ logit, probit, cauchit and cloglog models aiming to found the key characteristics affecting the final outcome of a game. Finally, we will predict the accuracy and evaluate the performance of those models through different criteria, such as confusion matrix, area under curve (AUC) and random forest algorithm.