Injury Patterns and Impact on Performance in the NBA League Using Sports Analytics by Vangelis Sarlis, George Papageorgiou, Christos Tjortjis

“…Its findings illuminate the interplay between injuries, salaries, and performance in the NBA, aiming to enhance player welfare and the league’s overall competitiveness. …”
Get full text

A Comprehensive Data Pipeline for Comparing the Effects of Momentum on Sports Leagues by Jordan Truman Paul Noel, Vinicius Prado da Fonseca, Amilcar Soares

“…More precisely, we use our pipeline to determine the differences in the predictive power of momentum-based features and standard statistical features for the National Hockey League (NHL), National Basketball Association (NBA), and five major first-division European football leagues. …”
Get full text

All-NBA Teams’ Selection Based on Unsupervised Learning by João Vítor Rocha da Silva, Paulo Canas Rodrigues

“…As the results of this paper a model is presented that may help not only the NBA to better evaluate players, but any basketball league; it also may be a source to researchers that aim to investigate player performance, development, and their impact over many seasons.…”
Get full text

The National Basketball Association’s (NBA) Digital Transformation: An Explanatory Case Study by James Santomier, Harald Dolles, Reinhard Kunz

“…The NBA developed an ecosystem-based consumer-focused hybrid business model, content-focused digital assets, and partnerships with media, brands, and cultural events. …”
Get full text

Luck and skill in professional League of Legends (E-sports) by Douglas, Cameron (Cameron David)

Get full text

Anthropometric and physical fitness indicators in the combine draft between the finalist and the eliminated player in the national basketball association all-star slam dunk contest... by Tse-Hau Tong, Guo-Wei Wang

“…Similiarly, coach from NBA or other basketball league, who want to improve the player's slam dunk performance, should use specific training programs to develop the slam dunk-related indicator.…”
Get full text

Enhancing Basketball Game Outcome Prediction through Fused Graph Convolutional Networks and Random Forest Algorithm by Kai Zhao, Chunjie Du, Guangxin Tan

“…Furthermore, models that rely on vector inputs tend to ignore the intricate interactions between teams and the spatial structure of the league. Therefore, this study aimed to apply graph neural networks to basketball game outcome prediction, by transforming structured data into unstructured graphs, to represent the interactions between teams in the 2012–2018 NBA season dataset. …”
Get full text