Predicting the Outcome of NBA Playoffs Based on the Maximum Entropy Principle by Ge Cheng, Zhenyu Zhang, Moses Ntanda Kyebambe, Nasser Kimbugwe

“…In this article, we formalize the problem of predicting NBA game results as a classification problem and apply the principle of Maximum Entropy to construct an NBA Maximum Entropy (NBAME) model that fits to discrete statistics for NBA games, and then predict the outcomes of NBA playoffs using the model. Our results reveal that the model is able to predict the winning team with 74.4% accuracy, outperforming other classical machine learning algorithms that could only afford a maximum prediction accuracy of 70.6% in the experiments that we performed.…”
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Choking or Delivering Under Pressure? The Case of Elimination Games in NBA Playoffs by Elia Morgulev, Yair Galily

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Statistical logic of scoring interaction in NBA playoffs (2014-2019): The influence of time and space by Raúl Martínez-Santos, Asier Oiarbide, Mario Enjuanes

“…Basketball is a sport of deceptions, but also of numbers, and the knowledge of its internal logic has benefited for decades from the contributions of colleagues such as Sampaio and Ibáñez-Godoy. Accepting that NBA playoffs are the most demanding competition in our sport, we set two complementary goals for this study: to provide the a priory probabilities associated with field shots based on space and time, and to show the way we followed to calculate them in the R environment. …”
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