Zuccolotto Paola - Basketball Data Science

Basketball Data Science

With Applications in R

CHAPMAN & HALL/CRC DATA SCIENCE SERIES

Reflecting the interdisciplinary nature of the field, this book series brings together researchers, practitioners, and instructors from statistics, computer science, machine learning, and analytics. The series will publish cutting-edge research, industry applications, and textbooks in data science.

The inclusion of concrete examples, applications, and methods is highly encouraged. The scope of the series includes titles in the areas of machine learning, pattern recognition, predictive analytics, business analytics, Big Data, visualization, programming, software, learning analytics, data wrangling, interactive graphics, and reproducible research.

Published Titles

Feature Engineering and Selection

A Practical Approach for Predictive Models

Max Kuhn and Kjell Johnson

Probability and Statistics for Data Science

Math + R + Data

Norman Matloff

Introduction to Data Science

Data Analysis and Prediction Algorithms with R

Rafael A. Irizarry

Cybersecurity Analytics

Rakesh M. Verma and David J. Marchette

Basketball Data Science

With Applications in R

Paola Zuccolotto and Marica Manisera

For more information about this series, please visit: https://www.crcpress.com/Chapman--HallCRCData-Science-Series/book-series/CHDSS

Basketball Data Science

With Applications in R

Paola Zuccolotto
Marica Manisera

With contributions by Marco Sandri
Foreword by Ettore Messina

CRC Press

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To Leonardo and Raffaele,
the best basketball players ever.

To Alberto,
(whatever the sport) MVP.

To all three of them, budding Data Scientists.

Contents

When we are at home in San Antonio, I arrive in the office very early and the first email I read is the FaxBack, or the statistics relating to the next opponent and the comparison with the Spurs.

Invariably, I cant help smiling to myself, remembering that I am undoubtedly one of the old school coaches who has been given a cleanup in the last few years, learning, with a certain degree of pride, to converse with our analyst staff. I have learned not only to utilize the work of this group of five people who provide us daily with a mountain of data, but also I have devised my own set of criteria which help me to navigate my way through all the information, selecting those items which allow me to prepare for the game, studying our opponents strengths and weaknesses. I study the statistics which give me a better understanding of their tendencies and what they are likely to do in the crucial moments of the game.

In recent years, the National Basketball Association (NBA) teams have strengthened their analyst staff to prepare in the best way for the draft, to carry out player exchanges, and to study the most efficient attack and defense aspects of the game. This is to the point where, in some teams, the style of game sought by the coaching staff has been predominantly influenced by numbers. It is no secret that many of the teams have started requiring their players to aim for a shot from underneath the basket or from behind the three-point line, considering the middle distance shot totally inefficient. I am convinced that this could be a guideline but not a diktat; in other words, if all those in attack go for shots from below and shots from the three-point line, the defenders will do their best not to concede these shots. As a result, they may allow more shots from the middle. At this point, having some athletes in the team who can shoot well from this distance will become absolutely a must in order to win.

Personally, I believe that the human factor is always fundamental: first of all, speaking of simple things, I am interested in knowing, as well as the point averages, rebounds, turnovers, assists, how much of all this is done against the best teams. Too many players who average ten points per game for the season score most of those points against average and poor teams, whereas they are less successful against the top teams. Also, scoring ten points in the first two quarters of the game is not the same as scoring them in the final minutes when the outcome of the match is being decided.

Furthermore, the coachs decision as to whom to put on the field is based above all on feelings about the character of the individual players and their personal chemistry with the teammates, rather than exclusively on their technical skills, and about their ability to cope with pressure. Numbers can, and should, help us. However, communication between coaches and analysts can only be the central point of efficient management of resources, which are, before anything else, human.

I am grateful to Paola Zuccolotto and Marica Manisera for sharing this philosophical approach in their valuable work. I think that it is the correct route for bringing these two worlds closer together and achieving the maximum pooling of knowledge.

Lastly, I hope that they will let me have a copy of their book soon so that I can pass it on to the Spurs analysts. Italians do it better!

Ettore Messina