“A fun, important book that will draw a lot of sports fans into analytics and mathematics. Lively and informative.”
— Roland B. Minton, author of "Sports Math: An Introductory Course in the Mathematics of Sports Science and Sports Analytics"
“Fun and full of puzzles and brainteasers in a mashup of mathematics. . . . Magic.”
— Robert Schaefer, New York Journal of Books, on "Math Bytes"
“Get in the Game is a playful and welcoming introduction to the interplay between sports and math. Assuming no math and using only a coin and a die, Chartier artfully illustrates why sports analytics matter through the simplest of questions: how do we measure greatness? This is a must-read for anyone curious about the analytical side of sport.”
— John Urschel, former NFL offensive lineman, Institute for Advanced Study, and coauthor of "Mind and Matter: A Life in Math and Football"
“I’ve always wished I could keep a miniature Tim Chartier on my shoulder while I’m watching sports: a brilliant, enthusiastic, friendly expert eager to share his insights about the games. With this book, you’ve got the next best thing.”
— Ben Orlin, author of "Math Games with Bad Drawings"
“Chartier uses instances of improbable (‘unforgettably unbelievable’) events in various sports to introduce concepts and calculations in probability. Dice experiments are featured, as well as spreadsheet calculations and simulation. Each chapter concludes with a ‘workout’ for the reader to try out the concepts introduced (answers are provided).”
— Mathematics Magazine
"The key aspect that separates this book from other statistics and probability books that I have read, as well as sport data analytics books, is that Chartier has worked very hard to ensure that any mention of statistics and probability in this book is done through the use of coin tosses or rolls of a die. He wants the reader to understand the underlying concepts of the book are no more complicated than understanding a 50/50 coin toss or the distribution of possible rolls of a six-sided die. He manages to extrapolate these two concepts to far more complex concepts such as the binomial and normal distributions, Pythagorean expectation and computer simulations in sports forecasting using a very clear path for readers with little experience in formal statistics and probability studies. . . . This is certainly the most accessible book on sport data analytics that I’ve read. If you know someone who likes different sports but isn’t too confident with their mathematical abilities then this is a good bet (pun intended)."
— Mathematics Today