Pubblicazione:
G-RAPM: revisiting player contributions in regularized adjusted plus-minus models for basketball analytics
G-RAPM: revisiting player contributions in regularized adjusted plus-minus models for basketball analytics
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Data
2022
Autori
Luca Grassetti
Titolo del Periodico
ISSN Periodico
Titolo volume
Editore
Pearson
Progetti di ricerca
Strutture
Fascicolo Periodico
Abstract
Identification and analysis of players ranking have a central role in the sports analytics. An essential tool in this framework is the Regularized Adjusted Plus-Minus (RAPM) model. When player and lineup effects are included simultaneously, the interpretation of the RAPM model results can be cumbersome. The present work aims at estimating a modified version of the RAPM model, adopting a one-sided assumption for player effects. The proposed specification allows for a direct performance interpretation. The model can be estimated feasibly within the Bayesian framework, allowing for straightforward generalisations.
Descrizione
Parole chiavi
RAPM, Basketball, Sports Management, Player Performances and Lineup Synergies