Predicting Active NBA Players Most Likely to Be Inducted into the Basketball Hall of Famers Using Artificial Neural Networks in Microsoft Excel: Development and Usability Study.

Po-Hsin Chou,Ting-Ya Yang,Tsair-Wei Chien,Willy Chou,Yu-Tsen Yeh,Chao-Hung Yeh

doi:10.3390/ijerph18084256

Abstract

The prediction of whether active NBA players can be inducted into the Hall of Fame (HOF) is interesting and important. However, no such research have been published in the literature, particularly using the artificial neural network (ANN) technique. The aim of this study is to build an ANN model with an app for automatic prediction and classification of HOF for NBA players. We downloaded 4728 NBA players’ data of career stats and accolades from the website at basketball-reference.com. The training sample was collected from 85 HOF members and 113 retired Non-HOF players based on completed data and a longer career length (≥15 years). Featured variables were taken from the higher correlation coefficients (<0.1) with HOF and significant deviations apart from the two HOF/Non-HOF groups using logistical regression. Two models (i.e., ANN and convolutional neural network, CNN) were compared in model accuracy (e.g., sensitivity, specificity, area under the receiver operating characteristic curve, AUC). An app predicting HOF was then developed involving the model’s parameters. We observed that (1) 20 feature variables in the ANN model yielded a higher AUC of 0.93 (95% CI 0.93–0.97) based on the 198-case training sample, (2) the ANN performed better than CNN on the accuracy of AUC (= 0.91, 95% CI 0.87–0.95), and (3) an ready and available app for predicting HOF was successfully developed. The 20-variable ANN model with the 53 parameters estimated by the ANN for improving the accuracy of HOF has been developed. The app can help NBA fans to predict their players likely to be inducted into the HOF and is not just limited to the active NBA players.

Highlights

We assumed that if the National Basketball Association (NBA) active players were to stop playing tomorrow, what are the probabilities inducted into the Hall of Fame (HOF) and made a hypothesis of whether an app can be developed for predicting the active NBA players likely to be inducted into the basketball
The following tasks were aimed in three parts: Part 1: model building includes (1) determining the featured variables used for estimating model parameters and (2) comparing the model accuracies between the two artificial neural network (ANN)/convolutional neural network (CNN) models
All those 4728 NBA players were split into three parts: (1) the 152 HOF members, (2) the 4173 retired Non-HOF, and (3) the 707 active NBA players

Summary

Introduction

The Naismith Memorial Basketball Hall of Fame [1] is the highest career honor one can achieve after retirement for a player from National Basketball Association (NBA). When we hear the words “Hall of Fame,” various terms and implications come to our mind, such as greatness, distinction, honor, and various others [2]. It intrigues authors to expect that those admitted to a Hall of Fame (HOF) should be the epitomes of those traits by observing their NBA career stats and accolades. Should HOF be great players, but great honors for active players to pursuit. The premise to be eligible on the HOF ballot is the player who must be fully retired for at least three years [3]

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Discussion

Conclusion