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Professor Wayne Winston
Learn how probability, math, and statistics can be used to help baseball, football and basketball teams improve, player and lineup selection as well as in game strategy.
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What's inside
Syllabus
Before you start...
Module 1
You will learn how to predict a team’s won loss record from the number of runs, points, or goals scored by a team and its opponents. Then we will introduce you to multiple regression and show how multiple regression is used to evaluate baseball hitters. Excel data tables, VLOOKUP, MATCH, and INDEX functions will be discussed.
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Syllabus
Before you start...
Module 1
You will learn how to predict a team’s won loss record from the number of runs, points, or goals scored by a team and its opponents. Then we will introduce you to multiple regression and show how multiple regression is used to evaluate baseball hitters. Excel data tables, VLOOKUP, MATCH, and INDEX functions will be discussed.
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Provides an edge in understanding sports-related topics across fields such as mathematics, probability, and statistics
Covers a comprehensive study of sports-related topics, from analyzing player metrics to simulating tournament outcomes
Suitable for learners with an interest in sports analytics and improving team performance
Taught by Professor Wayne Winston, recognized for his expertise in sports analytics
Involves the use of Excel tools and concepts for data analysis and player evaluations
May require prior knowledge of Excel and statistical concepts
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Reviews summary
Math behind moneyball: sports analytics intro
According to learners, this course offers an engaging introduction to applying math and statistics concepts like regression and simulation to the world of sports analytics. Students particularly appreciated the practical Excel applications and the detailed dives into topics like WAR, Moneyball strategies, and aspects of basketball and football analytics. Many found it a fascinating way to learn quantitative methods through relatable examples from baseball, football, and basketball, with some noting its use for fantasy sports and betting insights. However, some reviews cautioned that the material might feel a bit dated due to specific references and that the level of statistical depth might be too basic for experienced analysts or challenging for complete beginners without prior exposure.
Good intro, but level varies based on background.
"A great first step into sports analytics concepts."
"Too basic if you already have a strong background in stats or finance."
"Needed more background in statistics or Excel than I expected."
"Found some parts challenging without a prior math background."
Useful for fantasy sports or betting insights.
"Helped me improve my daily fantasy sports picks."
"Gave me insights for understanding sports betting concepts."
"Good for understanding probability and strategy in gambling."
"I can directly apply some concepts to my fantasy league research."
Hands-on demos provide valuable applied skills.
"The Excel modules were very useful and practical."
"Liked learning PivotTables and other functions through sports data."
"Gave me practical tools for analyzing sports data using Excel."
"The hands-on exercises in Excel were a highlight for me."
Applying math and stats to sports is captivating.
"Applying stats to Moneyball is fascinating and kept me engaged."
"Really enjoyed seeing how analytics are used in different sports."
"Makes learning regression interesting with real sports examples."
"The topic is inherently interesting for any sports fan."
Specific examples may feel a bit old.
"References like the 2016 bracket feel a bit outdated."
"Could use more modern sports analytics examples and trends."
"Wish the course material was updated more recently."
"Some data points feel slightly old in the fast-moving world of sports analytics."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Math behind Moneyball with these
activities:
Review Basic Statistics
Show steps
Review the fundamentals of probability, expected value, and variance to strengthen your foundation for this course.
Browse courses on
Probability
Show steps
-
Revisit textbooks or online resources on probability and statistics
-
Solve practice problems related to mean, median, and mode
Work through practice problems related to probability and statistics
Show steps
Reinforce your understanding of probability and statistics through repetitive exercises, improving your ability to solve problems related to sports analytics.
Browse courses on
Probability
Show steps
-
Find a collection of practice problems
-
Solve the problems using the concepts covered in the course
-
Review your solutions and identify areas where you need improvement
Read 'The Mathematics of Baseball' by Alan Reifman
Show steps
Understand the mathematical principles behind baseball statistics, helping you better grasp the concepts covered in the course.
Show steps
-
Obtain a copy of the book
-
Read the book in its entirety
-
Take notes on key concepts and formulas
-
Apply the concepts to real-world baseball data
Five other activities
Expand to see all activities and additional details
Show all eight activities
Learn advanced Excel functions and techniques
Show steps
Enhance your ability to analyze sports data by mastering advanced Excel functions and techniques, such as data manipulation, pivot tables, and macros.
Browse courses on
Excel
Show steps
-
Find online tutorials or courses on advanced Excel
-
Follow the tutorials and practice using Excel to solve problems related to sports analytics
-
Apply the techniques to analyze your own sports data
Create a fantasy baseball team
Show steps
Apply your knowledge of baseball statistics and player evaluation to make informed Entscheidungen in a fantasy baseball league.
Browse courses on
Player Evaluation
Show steps
-
Join a fantasy baseball league
-
Research player statistics and projections
-
Draft a team of players
-
Manage your team throughout the season
Discuss sports analytics concepts with peers
Show steps
Engage with other students to exchange ideas, clarify concepts, and enhance your understanding of sports analytics through collaborative learning.
Show steps
-
Join a study group or online forum for the course
-
Participate in discussions and ask questions
-
Share your own insights and perspectives
Create a video tutorial explaining a sports analytics concept
Show steps
Solidify your understanding of a sports analytics concept by creating a video tutorial that explains it in a clear and engaging way, benefiting both yourself and others.
Show steps
-
Choose a concept to explain
-
Write a script for the video
-
Record and edit the video
-
Share the video online
Develop a data visualization dashboard for a sports team
Show steps
Apply your data analysis skills to create a comprehensive data visualization dashboard that tracks team performance, player metrics, and other relevant data, providing valuable insights for decision-making.
Browse courses on
Data Visualization
Show steps
-
Gather data from various sources
-
Clean and prepare the data
-
Choose appropriate visualization techniques
-
Develop the dashboard using a data visualization tool
Review Basic Statistics
Show steps
Review the fundamentals of probability, expected value, and variance to strengthen your foundation for this course.
Browse courses on
Probability
Show steps
Show steps
Show steps
- Revisit textbooks or online resources on probability and statistics
- Solve practice problems related to mean, median, and mode
Work through practice problems related to probability and statistics
Show steps
Reinforce your understanding of probability and statistics through repetitive exercises, improving your ability to solve problems related to sports analytics.
Browse courses on
Probability
Show steps
Show steps
Show steps
- Find a collection of practice problems
- Solve the problems using the concepts covered in the course
- Review your solutions and identify areas where you need improvement
Read 'The Mathematics of Baseball' by Alan Reifman
Show steps
Understand the mathematical principles behind baseball statistics, helping you better grasp the concepts covered in the course.
Show steps
Show steps
Show steps
- Obtain a copy of the book
- Read the book in its entirety
- Take notes on key concepts and formulas
- Apply the concepts to real-world baseball data
Five other activities
Expand to see all activities and additional details
Show all eight activities
Learn advanced Excel functions and techniques
Show steps
Enhance your ability to analyze sports data by mastering advanced Excel functions and techniques, such as data manipulation, pivot tables, and macros.
Browse courses on
Excel
Show steps
Show steps
Show steps
- Find online tutorials or courses on advanced Excel
- Follow the tutorials and practice using Excel to solve problems related to sports analytics
- Apply the techniques to analyze your own sports data
Create a fantasy baseball team
Show steps
Apply your knowledge of baseball statistics and player evaluation to make informed Entscheidungen in a fantasy baseball league.
Browse courses on
Player Evaluation
Show steps
Show steps
Show steps
- Join a fantasy baseball league
- Research player statistics and projections
- Draft a team of players
- Manage your team throughout the season
Discuss sports analytics concepts with peers
Show steps
Engage with other students to exchange ideas, clarify concepts, and enhance your understanding of sports analytics through collaborative learning.
Show steps
Show steps
Show steps
- Join a study group or online forum for the course
- Participate in discussions and ask questions
- Share your own insights and perspectives
Create a video tutorial explaining a sports analytics concept
Show steps
Solidify your understanding of a sports analytics concept by creating a video tutorial that explains it in a clear and engaging way, benefiting both yourself and others.
Show steps
Show steps
Show steps
- Choose a concept to explain
- Write a script for the video
- Record and edit the video
- Share the video online
Develop a data visualization dashboard for a sports team
Show steps
Apply your data analysis skills to create a comprehensive data visualization dashboard that tracks team performance, player metrics, and other relevant data, providing valuable insights for decision-making.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Gather data from various sources
- Clean and prepare the data
- Choose appropriate visualization techniques
- Develop the dashboard using a data visualization tool
Career center
Learners who complete Math behind Moneyball will develop knowledge and skills
that may be useful to these careers:
Baseball Analyst
Baseball Analyst
A course on 'Math behind Moneyball' is highly relevant for a Baseball Analyst. Baseball Analysts use mathematical and statistical models to analyze baseball data, evaluate players, and make predictions about game outcomes. They need to have a strong understanding of probability, statistics, and baseball. This course can help Baseball Analysts develop the skills needed to analyze data, make predictions, and make informed decisions about baseball teams and players.
Financial Analyst
Financial Analyst
A course on 'Math behind Moneyball' may be useful for a Financial Analyst. Financial Analysts use mathematical and statistical models to analyze financial data, make investment recommendations, and manage portfolios. They need to have a strong understanding of probability, statistics, and finance. This course can help Financial Analysts develop the skills needed to analyze data, make predictions, and make sound investment decisions.
Data Scientist
Data Scientist
A course on 'Math behind Moneyball' may be useful for a Data Scientist. Data Scientists use mathematical and statistical models to analyze data, identify trends, and make predictions. They need to have a strong understanding of probability, statistics, and computer science. This course can help Data Scientists develop the skills needed to analyze data, make predictions, and make informed decisions.
Sports Writer
Sports Writer
A course on 'Math behind Moneyball' may be useful for a Sports Writer. Sports Writers write articles and stories about sports for newspapers, magazines, and websites. They need to have a strong understanding of sports and the factors that influence player performance. This course can help Sports Writers develop the analytical skills needed to assess player value, write informed articles, and make predictions about game outcomes.
Actuary
Actuary
A course on 'Math behind Moneyball' may be useful for an Actuary. Actuaries use mathematical and statistical models to assess risk and uncertainty. They need to have a strong understanding of probability, statistics, and finance. This course can help Actuaries develop the skills needed to analyze data, make predictions, and make informed decisions about risk and uncertainty.
Statistician
Statistician
A course on 'Math behind Moneyball' may be useful for a Statistician. Statisticians use mathematical and statistical models to collect, analyze, and interpret data. They need to have a strong understanding of probability, statistics, and computer science. This course can help Statisticians develop the skills needed to analyze data, make predictions, and make informed decisions.
Economist
Economist
A course on 'Math behind Moneyball' may be useful for an Economist. Economists use mathematical and statistical models to analyze economic data, make predictions, and develop economic policies. They need to have a strong understanding of probability, statistics, and economics. This course can help Economists develop the skills needed to analyze data, make predictions, and make informed decisions about economic policies.
Operations Research Analyst
Operations Research Analyst
A course on 'Math behind Moneyball' may be useful for an Operations Research Analyst. Operations Research Analysts use mathematical and statistical models to solve complex problems in business and industry. They need to have a strong understanding of probability, statistics, and computer science. This course can help Operations Research Analysts develop the skills needed to analyze data, make predictions, and make informed decisions about business and industry.
Risk Manager
Risk Manager
A course on 'Math behind Moneyball' may be useful for a Risk Manager. Risk Managers use mathematical and statistical models to assess risk and uncertainty. They need to have a strong understanding of probability, statistics, and finance. This course can help Risk Managers develop the skills needed to analyze data, make predictions, and make informed decisions about risk and uncertainty.
Business Analyst
Business Analyst
A course on 'Math behind Moneyball' may be useful for a Business Analyst. Business Analysts use mathematical and statistical models to analyze business data, make predictions, and develop business strategies. They need to have a strong understanding of probability, statistics, and business. This course can help Business Analysts develop the skills needed to analyze data, make predictions, and make informed decisions about business strategies.
Quantitative Analyst
Quantitative Analyst
A course on 'Math behind Moneyball' may be useful for a Quantitative Analyst. Quantitative Analysts use mathematical and statistical models to analyze financial data, make investment recommendations, and manage portfolios. They need to have a strong understanding of probability, statistics, and finance. This course can help Quantitative Analysts develop the skills needed to analyze data, make predictions, and make sound investment decisions.
Market Researcher
Market Researcher
A course on 'Math behind Moneyball' may be useful for a Market Researcher. Market Researchers use mathematical and statistical models to analyze market data, make predictions, and develop marketing strategies. They need to have a strong understanding of probability, statistics, and marketing. This course can help Market Researchers develop the skills needed to analyze data, make predictions, and make informed decisions about marketing strategies.
Data Analyst
Data Analyst
A course on 'Math behind Moneyball' may be useful for a Data Analyst. Data Analysts use mathematical and statistical models to analyze data, identify trends, and make predictions. They need to have a strong understanding of probability, statistics, and computer science. This course can help Data Analysts develop the skills needed to analyze data, make predictions, and make informed decisions.
Sports Agent
Sports Agent
A course on 'Math behind Moneyball' may be useful for a Sports Agent. Sports Agents negotiate contracts, manage finances, and advise athletes on their careers. They need to have a strong understanding of the business of sports and the factors that influence player performance. This course can help Sports Agents develop the analytical skills needed to assess player value, negotiate contracts, and make informed decisions about their clients' careers.
Software Engineer
Software Engineer
A course on 'Math behind Moneyball' may be useful for a Software Engineer. Software Engineers use mathematical and statistical models to design, develop, and test software. They need to have a strong understanding of probability, statistics, and computer science. This course can help Software Engineers develop the skills needed to design, develop, and test software.
For more career information including salaries, visit:
OpenCourser.com/course/qjrwyf/math
Featured in The Course Notes
This course is mentioned in our blog,
The Course Notes. Read
one article that features
Math behind Moneyball:
To read more articles from OpenCourser, visit:
OpenCourser.com/notes
Reading list
We've selected 19 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Math behind Moneyball.
Save
A pioneering text on the application of probabilistic methods and sabermetrics in baseball. This text is most suitable as historical background reading, but may be less useful as a current reference.
Save
A comprehensive text that provides a broad overview of all aspects of baseball strategy, including advanced topics such as game theory and linear weights.
Save
The subject of this book is sabermetrics, or the analysis of baseball statistics. The authors cover a wide range of advanced metrics including on-base percentage, slugging percentage, and Fielding Independent Pitching.
Save
Delves into the history and use of statistics in baseball and argues that many conventional baseball wisdoms are not supported by the data.
One of the first books to use advanced statistics to analyze baseball teams. Covers the history of the game and its evolution, and helps to explain how to numerically evaluate players and on-field performance.
Save
The foundational text on sabermetrics, which provides valuable historical context for the course. While not as comprehensive or up-to-date as more recent texts, it remains a valuable resource.
A textbook that provides a broad overview of probability theory and statistics. This text helpful reference for understanding the mathematical foundations of sabermetrics.
A guide to evaluating pitchers using sabermetric analysis, this book provides detailed statistics and analysis of pitchers in Major League Baseball.
A guide to evaluating fielders using sabermetric analysis, this book provides detailed statistics and analysis of fielders in Major League Baseball.
A textbook that provides a detailed and rigorous introduction to econometrics. While primarily targeted at business and economics students, this text can be a valuable reference for understanding the advanced statistical models used in sabermetrics.
The official rulebook of Major League Baseball, this book provides the rules and regulations governing the game.
A classic text on the art and science of hitting in baseball. While not directly related to sabermetrics, this text can be helpful for understanding the context in which sabermetric analysis is applied.
Save
Collection of essays on baseball history, strategy, and statistics. It valuable resource for anyone interested in learning more about the game of baseball.
Save
A practical guide to pitching strategies and techniques for baseball players and coaches. While not directly related to sabermetrics, this text can be helpful for understanding the context in which sabermetric analysis is applied.
Explores the physics behind the game of baseball. It explains the principles of physics that govern the flight of a baseball, the swing of a bat, and the spin of a ball.
An annual publication that provides a comprehensive analysis of the top prospects in baseball. While not directly related to sabermetrics, this publication can be helpful for understanding the context in which sabermetric analysis is applied.
An annual publication that provides a comprehensive analysis of the upcoming baseball season, including projections, scouting reports, and historical data. While not a textbook, this publication can be a valuable resource for staying up-to-date on the latest sabermetric research.
A guide to the mental and emotional aspects of playing baseball. While not directly related to sabermetrics, this text can be helpful for understanding the context in which sabermetric analysis is applied.
An online magazine that provides in-depth sabermetric analysis and commentary. While not a textbook, this resource can be a valuable supplement to the course.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/qjrwyf/math
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Introductory
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Institution
University of Houston
Instructor
Professor Wayne Winston
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Featured in The Course Notes
Read
one article that features
this course,
Math behind Moneyball
from our blog, The Course Notes:
To read more articles from OpenCourser, visit:
OpenCourser.com/notes
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