What do you think?
Rate this book
Analytic Methods in Sports: Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports
The Most Useful Techniques for Analyzing Sports DataOne of the greatest changes in the sports world in the past 20 years has been the use of mathematical methods to analyze performances, recognize trends and patterns, and predict results. Analytic Methods in Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports provides a concise yet thorough introduction to the analytic and statistical methods that are useful in studying sports. The book gives you all the tools necessary to answer key questions in sports analysis. It explains how to apply the methods to sports data and interpret the results, demonstrating that the analysis of sports data is often different from standard statistical analysis. Requiring familiarity with mathematics but no previous background in statistics, the book integrates a large number of motivating sports examples throughout and offers guidance on computation and suggestions for further reading in each chapter.
- GenresSports
254 pages, Kindle Edition
First published August 5, 2014
3 people are currently reading
119 people want to read
Ratings & Reviews
Friends & Following
Create a free account to discover what your friends think of this book!
Community Reviews
Displaying 1 of 1 review
July 23, 2017
The quote «Analytic methods use data to draw conclusions and make decisions in sports» is the book's best summary. Besides, they rely on analysis and interpretations, more than on formulas and calculations.
I was a bit disappointed with the book because despite reading "basketball" in the title, most of examples are baseball and football related. There is some basketball and hockey, even a pair of examples of soccer, tennis and golf. But I am a huge basketball fan and I was hoping to find more statistics of these particular sport. My interests are mainly basketball and the statistics themselves, thence my personal decision to rate this book with two stars: it contains too much MLB and NFL for me.
The book has somehow a pedagogical structure, based on the statistics not on the sports. Severini constructs statistical concepts step by step, and provides many examples to understand how they can be applied. You shouldn't approach this book with a sports-focused gaze, but with an idea about how to use statistics methods in sports. You won't really learn almost anything about the aforementioned sports.
After a short introduction, chapters 2 and 3 cover the (spanish) secondary curriculum: unidimensional descriptive statistics (different types of variables and the main central measures of central tendency and dispersion), as well as basic probability theory and binomial and normal distributions.
Chapter 4 covers error margins, chapter 5 correlations and linear dependence to detect statistical relationships. Chapter 6 covers linear and polynomial regression and chapter 7 the latter but with several predictor variables.
Finally, the author also provides a website that includes quite a few spreadsheets with datasets used in the examples of the book. Severini has written how to use Excel to obtain certain results, so readers can follow the calculations Severini makes.
I was a bit disappointed with the book because despite reading "basketball" in the title, most of examples are baseball and football related. There is some basketball and hockey, even a pair of examples of soccer, tennis and golf. But I am a huge basketball fan and I was hoping to find more statistics of these particular sport. My interests are mainly basketball and the statistics themselves, thence my personal decision to rate this book with two stars: it contains too much MLB and NFL for me.
The book has somehow a pedagogical structure, based on the statistics not on the sports. Severini constructs statistical concepts step by step, and provides many examples to understand how they can be applied. You shouldn't approach this book with a sports-focused gaze, but with an idea about how to use statistics methods in sports. You won't really learn almost anything about the aforementioned sports.
After a short introduction, chapters 2 and 3 cover the (spanish) secondary curriculum: unidimensional descriptive statistics (different types of variables and the main central measures of central tendency and dispersion), as well as basic probability theory and binomial and normal distributions.
Chapter 4 covers error margins, chapter 5 correlations and linear dependence to detect statistical relationships. Chapter 6 covers linear and polynomial regression and chapter 7 the latter but with several predictor variables.
Finally, the author also provides a website that includes quite a few spreadsheets with datasets used in the examples of the book. Severini has written how to use Excel to obtain certain results, so readers can follow the calculations Severini makes.
Displaying 1 of 1 review