Basketball predictions in the NCAAB and NBA: Similarities and differences. (29th June 2016)

• Record Type: Journal Article
• Authors: Zimmermann, Albrecht
• Is Part Of: Statistical analysis and data mining. Volume 9:Number 5(2016)
• Page Start: 350
• Page End: 364
• Publication Date: 2016-06-29
• Subjects: sports analytics -- basketball -- match outcome predictions; Data mining -- Statistical methods -- Periodicals; 006.312
• DOI: 10.1002/sam.11319
• Languages: English
• ISSNs: 1932-1864

Abstract

Abstract : Most work on predicting the outcome of basketball matches so far has focused on National College Athletics Association Basketball (NCAAB) games. Since NCAAB and professional (National Basketball Association, NBA) basketball have a number of differences, it is not clear to what degree these results can be transferred. We explore a number of different representations, training settings, and classifiers, and contrast their results on NCAAB and NBA data. We find that adjusted efficiencies work well for the NBA, the NCAAB regular season is not ideal for training to predict its post‐season, the two leagues require classifiers with different bias, and Naïve Bayes predicts the outcome of NBA playoff series well. © 2016 Wiley Periodicals, Inc. Statistical Analysis and Data Mining: The ASA Data Science Journal, 2016