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Brandon Armstrong
and
Matt Kata
Former Major League Baseball (MLB) player Matt Kata joins MathWorks to introduce you to data analysis using baseball statistics. By analyzing historic batting statistics, you will explore player careers and answer the question: When do great hitters peak in...
Read more
Former Major League Baseball (MLB) player Matt Kata joins MathWorks to introduce you to data analysis using baseball statistics. By analyzing historic batting statistics, you will explore player careers and answer the question: When do great hitters peak in...
Read more
Former Major League Baseball (MLB) player Matt Kata joins MathWorks to introduce you to data analysis using baseball statistics. By analyzing historic batting statistics, you will explore player careers and answer the question: When do great hitters peak in their career?
In this project, you will work in MATLAB, a programming environment used by millions of engineers and scientists, and now MLB players! You’ll have access to pitching, batting, and defensive statistics dating back to 1871, enabling you to explore and answer a wide variety of questions. You will compute statistics like On-base Plus Slugging (OPS), visualize results, and filter data to highlight players that meet criteria you specify, such as the number of home runs.
Whether you’re analyzing sports data, financial markets, or electric engine performance, you can apply the data analysis skills you learn in this project to many other fields and applications. So, step up to the plate and take a swing at MATLAB for data analysis.
Register for this course and see more details by visiting:
OpenCourser.com/course/pbpr6o/take
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Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Ideal for baseball fans seeking a deeper understanding of the sport through data analysis
Introduces MATLAB, a widely used software in scientific and engineering fields, including MLB
Hands-on project with access to comprehensive historical baseball statistics
Engaging real-world context that connects data analysis to sports
Teaches essential data analysis techniques using baseball as a case study
Instructor Matt Kata brings experience as a Major League Baseball player
Save this course
Save Take a Swing at Baseball Analytics: Explore Player Careers to your list so you can find it easily later:
Save
Save
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 Take a Swing at Baseball Analytics: Explore Player Careers with these
activities:
Find a mentor who is experienced in baseball analytics
Show steps
Provides guidance and support from an experienced professional in the field.
Show steps
-
Attend networking events or reach out to professionals in the field.
-
Explain your interest in baseball analytics and seek mentorship.
Explore MATLAB tutorials on data analysis and baseball statistics
Show steps
Enhance understanding of data analysis techniques by following guided tutorials, providing a structured approach to learning and solidifying concepts.
Browse courses on
Data Analysis
Show steps
-
Identify relevant MATLAB tutorials on data analysis and baseball statistics
-
Follow the tutorials step-by-step, practicing the techniques
-
Apply the learned techniques to analyze baseball data
-
Share insights and questions with fellow learners or a mentor
Review fundamental data visualization techniques
Show steps
Helps build a foundation of data visualization methods to prepare for deeper analysis techniques.
Browse courses on
Data Visualization
Show steps
-
Review common data visualization methods such as bar charts, scatter plots, and histograms.
-
Practice visualizing data using online resources or tools.
14 other activities
Expand to see all activities and additional details
Show all 17 activities
Follow Online Tutorials
Show steps
Follow online tutorials to reinforce your knowledge of MATLAB and baseball statistics.
Browse courses on
MATLAB
Show steps
-
Identify specific areas where you need additional support.
-
Search for online tutorials that cover these topics.
-
Follow the tutorials step-by-step, taking notes and practicing the concepts.
Read 'Data Analysis for Baseball' by Mike Fast
Show steps
Expands knowledge and provides a deeper understanding of baseball analytics by examining a related text.
View
The Science of Dream Teams: How Talent...
on Amazon
Show steps
-
Review the introductory chapters to gain an overview of baseball analytics concepts.
-
Read specific chapters relevant to the topics covered in the course.
Work Through Practice Problems
Show steps
Work through practice problems to solidify your understanding of baseball statistics and data analysis techniques.
Show steps
-
Review the course materials and identify areas where you need additional practice.
-
Find online practice problems or create your own.
-
Work through the problems, taking your time to understand the concepts.
-
Check your answers and make corrections as needed.
Complete guided tutorials on MATLAB for data analysis
Show steps
Improves understanding and strengthens practical skills by following guided tutorials designed to apply course concepts.
Show steps
-
Find tutorials on MATLAB's official website or other reputable sources.
-
Work through the tutorials, following the instructions and completing the exercises.
-
Experiment with different data analysis techniques using MATLAB.
Participate in Study Groups
Show steps
Join or form a study group to discuss the course material and work together on assignments.
Show steps
-
Find classmates who are interested in forming a study group.
-
Set regular meeting times and locations.
-
Review the course material together, ask questions, and work on assignments.
-
Provide feedback and support to your fellow group members.
Analyze player statistics to identify trends and outliers
Show steps
Practice data analysis skills by examining player statistics to identify patterns and anomalies, enhancing critical thinking and analytical abilities.
Browse courses on
Data Analysis
Show steps
-
Load player data into MATLAB
-
Calculate and visualize player statistics, such as batting average and OPS
-
Filter data to identify players meeting specific criteria, such as home runs hit
-
Create visualizations to explore relationships between different statistics
Practice data analysis exercises and problems
Show steps
Reinforces data analysis concepts through repetitive exercises, enhancing problem-solving skills.
Show steps
-
Find practice exercises and problem sets online or in textbooks.
-
Solve the exercises and problems, verifying your solutions using the provided answers.
-
Analyze your mistakes and identify areas for improvement.
Join online or local study groups for baseball analytics
Show steps
Provides a supportive environment for discussing course topics, sharing insights, and receiving feedback.
Show steps
-
Search for online or local study groups related to baseball analytics.
-
Attend regular meetings and actively participate in discussions.
-
Share your own insights and perspectives with the group.
Create a Data Visualization
Show steps
Create a data visualization to showcase your understanding of baseball statistics and data analysis.
Browse courses on
Data Visualization
Show steps
-
Choose a dataset and identify the key insights you want to communicate.
-
Select an appropriate visualization technique.
-
Create the visualization using MATLAB.
-
Write a brief description of your visualization, explaining the insights you have gained.
Develop a MATLAB script to analyze player data and generate insights
Show steps
Create a functional MATLAB script that automates data analysis tasks, fostering practical programming skills and deepening understanding of baseball statistics.
Browse courses on
MATLAB Programming
Show steps
-
Design and implement functions to calculate player statistics
-
Create user-friendly menus for selecting analysis parameters
-
Generate visualizations and reports to present insights
-
Document the script for clarity and reproducibility
Develop a Data Analysis Model
Show steps
Develop a data analysis model to predict player performance or identify trends in baseball data.
Browse courses on
Data Analysis
Show steps
-
Define the problem you want to solve or the question you want to answer.
-
Gather and clean the necessary data.
-
Choose an appropriate modeling technique.
-
Develop and train the model.
-
Evaluate the model's performance.
Write a blog post or article on the analysis of baseball statistics using MATLAB
Show steps
Communicate knowledge and insights gained from data analysis by creating a blog post or article, enhancing writing skills and fostering critical thinking.
Browse courses on
Data Analysis
Show steps
-
Choose a specific topic related to baseball statistics
-
Gather and analyze relevant data using MATLAB
-
Write a clear and engaging blog post or article presenting the findings
-
Promote the content on social media or other platforms
Create data visualizations to present your own analysis
Show steps
Provides an opportunity to apply data analysis skills creatively and demonstrate understanding by presenting findings.
Show steps
-
Choose a dataset of interest and perform your own data analysis.
-
Create visualizations using MATLAB or other tools to present your findings.
-
Present your analysis and visualizations to others, explaining your methods and insights.
Contribute to open-source baseball analytics projects
Show steps
Provides practical experience in baseball analytics while contributing to the open-source community.
Browse courses on
Open Source
Show steps
-
Identify open-source projects related to baseball analytics.
-
Read the project documentation and contribute to discussions.
-
Submit bug reports, feature requests, or code contributions.
Find a mentor who is experienced in baseball analytics
Show steps
Provides guidance and support from an experienced professional in the field.
Show steps
Show steps
Show steps
- Attend networking events or reach out to professionals in the field.
- Explain your interest in baseball analytics and seek mentorship.
Explore MATLAB tutorials on data analysis and baseball statistics
Show steps
Enhance understanding of data analysis techniques by following guided tutorials, providing a structured approach to learning and solidifying concepts.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Identify relevant MATLAB tutorials on data analysis and baseball statistics
- Follow the tutorials step-by-step, practicing the techniques
- Apply the learned techniques to analyze baseball data
- Share insights and questions with fellow learners or a mentor
Review fundamental data visualization techniques
Show steps
Helps build a foundation of data visualization methods to prepare for deeper analysis techniques.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Review common data visualization methods such as bar charts, scatter plots, and histograms.
- Practice visualizing data using online resources or tools.
14 other activities
Expand to see all activities and additional details
Show all 17 activities
Follow Online Tutorials
Show steps
Follow online tutorials to reinforce your knowledge of MATLAB and baseball statistics.
Browse courses on
MATLAB
Show steps
Show steps
Show steps
- Identify specific areas where you need additional support.
- Search for online tutorials that cover these topics.
- Follow the tutorials step-by-step, taking notes and practicing the concepts.
Read 'Data Analysis for Baseball' by Mike Fast
Show steps
Expands knowledge and provides a deeper understanding of baseball analytics by examining a related text.
View
The Science of Dream Teams: How Talent...
on Amazon
Show steps
Show steps
Show steps
- Review the introductory chapters to gain an overview of baseball analytics concepts.
- Read specific chapters relevant to the topics covered in the course.
Work Through Practice Problems
Show steps
Work through practice problems to solidify your understanding of baseball statistics and data analysis techniques.
Show steps
Show steps
Show steps
- Review the course materials and identify areas where you need additional practice.
- Find online practice problems or create your own.
- Work through the problems, taking your time to understand the concepts.
- Check your answers and make corrections as needed.
Complete guided tutorials on MATLAB for data analysis
Show steps
Improves understanding and strengthens practical skills by following guided tutorials designed to apply course concepts.
Show steps
Show steps
Show steps
- Find tutorials on MATLAB's official website or other reputable sources.
- Work through the tutorials, following the instructions and completing the exercises.
- Experiment with different data analysis techniques using MATLAB.
Participate in Study Groups
Show steps
Join or form a study group to discuss the course material and work together on assignments.
Show steps
Show steps
Show steps
- Find classmates who are interested in forming a study group.
- Set regular meeting times and locations.
- Review the course material together, ask questions, and work on assignments.
- Provide feedback and support to your fellow group members.
Analyze player statistics to identify trends and outliers
Show steps
Practice data analysis skills by examining player statistics to identify patterns and anomalies, enhancing critical thinking and analytical abilities.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Load player data into MATLAB
- Calculate and visualize player statistics, such as batting average and OPS
- Filter data to identify players meeting specific criteria, such as home runs hit
- Create visualizations to explore relationships between different statistics
Practice data analysis exercises and problems
Show steps
Reinforces data analysis concepts through repetitive exercises, enhancing problem-solving skills.
Show steps
Show steps
Show steps
- Find practice exercises and problem sets online or in textbooks.
- Solve the exercises and problems, verifying your solutions using the provided answers.
- Analyze your mistakes and identify areas for improvement.
Join online or local study groups for baseball analytics
Show steps
Provides a supportive environment for discussing course topics, sharing insights, and receiving feedback.
Show steps
Show steps
Show steps
- Search for online or local study groups related to baseball analytics.
- Attend regular meetings and actively participate in discussions.
- Share your own insights and perspectives with the group.
Create a Data Visualization
Show steps
Create a data visualization to showcase your understanding of baseball statistics and data analysis.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a dataset and identify the key insights you want to communicate.
- Select an appropriate visualization technique.
- Create the visualization using MATLAB.
- Write a brief description of your visualization, explaining the insights you have gained.
Develop a MATLAB script to analyze player data and generate insights
Show steps
Create a functional MATLAB script that automates data analysis tasks, fostering practical programming skills and deepening understanding of baseball statistics.
Browse courses on
MATLAB Programming
Show steps
Show steps
Show steps
- Design and implement functions to calculate player statistics
- Create user-friendly menus for selecting analysis parameters
- Generate visualizations and reports to present insights
- Document the script for clarity and reproducibility
Develop a Data Analysis Model
Show steps
Develop a data analysis model to predict player performance or identify trends in baseball data.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Define the problem you want to solve or the question you want to answer.
- Gather and clean the necessary data.
- Choose an appropriate modeling technique.
- Develop and train the model.
- Evaluate the model's performance.
Write a blog post or article on the analysis of baseball statistics using MATLAB
Show steps
Communicate knowledge and insights gained from data analysis by creating a blog post or article, enhancing writing skills and fostering critical thinking.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Choose a specific topic related to baseball statistics
- Gather and analyze relevant data using MATLAB
- Write a clear and engaging blog post or article presenting the findings
- Promote the content on social media or other platforms
Create data visualizations to present your own analysis
Show steps
Provides an opportunity to apply data analysis skills creatively and demonstrate understanding by presenting findings.
Show steps
Show steps
Show steps
- Choose a dataset of interest and perform your own data analysis.
- Create visualizations using MATLAB or other tools to present your findings.
- Present your analysis and visualizations to others, explaining your methods and insights.
Contribute to open-source baseball analytics projects
Show steps
Provides practical experience in baseball analytics while contributing to the open-source community.
Browse courses on
Open Source
Show steps
Show steps
Show steps
- Identify open-source projects related to baseball analytics.
- Read the project documentation and contribute to discussions.
- Submit bug reports, feature requests, or code contributions.
Career center
Learners who complete Take a Swing at Baseball Analytics: Explore Player Careers will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist is responsible for developing and implementing machine learning and artificial intelligence solutions. They work with data scientists to collect, analyze, and interpret data, and they use this information to build models that can make predictions and solve problems. This course may be useful for aspiring Data Scientists as it provides an introduction to data analysis and machine learning techniques.
Statistician
Statistician
A Statistician collects, analyzes, interprets, and presents data. They use statistical methods to draw conclusions about data and to make predictions. This course may be useful for aspiring Statisticians as it provides an introduction to data analysis and visualization techniques.
Data Visualization Specialist
Data Visualization Specialist
A Data Visualization Specialist is responsible for creating visual representations of data. They work with data analysts and other stakeholders to communicate insights from data. This course may be useful for aspiring Data Visualization Specialists as it provides an introduction to data analysis and visualization techniques.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst is responsible for developing and implementing mathematical and statistical models to analyze financial data. They use these models to make predictions about financial markets and to make investment decisions. This course may be useful for aspiring Quantitative Analysts as it provides an introduction to data analysis and visualization techniques.
Epidemiologist
Epidemiologist
An Epidemiologist is responsible for investigating the causes and distribution of diseases. They work with public health officials to develop and implement strategies to prevent and control diseases. This course may be useful for aspiring Epidemiologists as it provides an introduction to data analysis and visualization techniques.
Data Analyst
Data Analyst
A Data Analyst collects, analyzes, interprets, and presents data. They help businesses make informed decisions by providing insights into data. This course may be useful for aspiring Data Analysts as it provides an introduction to data analysis using real-world data from baseball statistics.
Biostatistician
Biostatistician
A Biostatistician is responsible for designing and conducting statistical studies in the field of medicine. They work with medical researchers to analyze data and to make predictions about the effectiveness of new treatments and drugs. This course may be useful for aspiring Biostatisticians as it provides an introduction to data analysis and visualization techniques.
Actuary
Actuary
An Actuary is responsible for assessing and managing risk. They use mathematical and statistical models to analyze data and to make predictions about future events. This course may be useful for aspiring Actuaries as it provides an introduction to data analysis and visualization techniques.
Market Researcher
Market Researcher
A Market Researcher is responsible for conducting research to understand consumer behavior and preferences. They work with businesses to develop and implement marketing strategies to reach target markets. This course may be useful for aspiring Market Researchers as it provides an introduction to data analysis and visualization techniques.
Business Analyst
Business Analyst
A Business Analyst is responsible for analyzing business processes and identifying areas for improvement. They work with stakeholders to define and prioritize requirements, and they develop and implement solutions to improve business performance. This course may be useful for aspiring Business Analysts as it provides an introduction to data analysis and visualization techniques.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst is responsible for developing and implementing mathematical and statistical models to solve business problems. They work with businesses to improve efficiency and productivity. This course may be useful for aspiring Operations Research Analysts as it provides an introduction to data analysis and visualization techniques.
Financial Analyst
Financial Analyst
A Financial Analyst is responsible for analyzing financial data to make investment recommendations. They work with clients to develop and implement investment strategies. This course may be useful for aspiring Financial Analysts as it provides an introduction to data analysis and visualization techniques.
Economist
Economist
An Economist is responsible for studying the production, distribution, and consumption of goods and services. They work with governments and businesses to develop and implement economic policies. This course may be useful for aspiring Economists as it provides an introduction to data analysis and visualization techniques.
Database Administrator
Database Administrator
A Database Administrator is responsible for managing and maintaining databases. They work with database users to define requirements, and they develop and implement database solutions to meet those requirements. This course may be useful for aspiring Database Administrators as it provides an introduction to data analysis and database management techniques.
Software Engineer
Software Engineer
A Software Engineer designs, develops, tests, and maintains software applications. They work with stakeholders to define requirements, and they develop and implement software solutions to meet those requirements. This course may be useful for aspiring Software Engineers as it provides an introduction to programming and data analysis techniques.
For more career information including salaries, visit:
OpenCourser.com/course/pbpr6o/take
Reading list
We've selected 11 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
Take a Swing at Baseball Analytics: Explore Player Careers.
This annual publication provides in-depth analysis of Major League Baseball teams and players, using advanced sabermetric statistics. It includes projections, player rankings, and historical data, making it a valuable resource for understanding the game and evaluating players.
Save
This annual publication from Bill James provides comprehensive analysis of Major League Baseball teams and players, using both traditional and advanced statistics. It includes projections, player rankings, and historical data, making it a valuable resource for anyone interested in the game.
Written by legendary hitter Ted Williams, this book provides a wealth of practical insights and advice on hitting techniques. Offers a valuable perspective from one of the greatest players in baseball history.
Save
Tells the story of the Oakland Athletics and their use of sabermetrics to gain a competitive advantage. Provides a glimpse into the application of data analysis in baseball.
This publication provides detailed analysis of Major League Baseball fielders, using advanced defensive metrics. It includes rankings, player evaluations, and historical data, making it a valuable resource for anyone interested in the defensive side of the game.
Save
Explores the history and use of statistics in baseball. Provides an overview of the different metrics and their impact on the game.
Provides a comprehensive history of baseball, from its origins to the present day. Offers a deeper appreciation for the game's cultural and historical significance.
Introduces the fundamental principles of statistics and data analysis. Provides a broader context for understanding the statistical methods used in baseball analytics.
Save
Provides a collection of essays on the game of baseball, covering topics such as history, strategy, and player profiles. It good choice for anyone interested in learning more about the game and its culture.
Save
Provides a behind-the-scenes look at the minds of Major League Baseball managers. It covers topics such as leadership, decision-making, and team management. It good choice for anyone interested in learning more about the art of managing.
Save
Offers a comprehensive guide to pitching mechanics, from fundamentals to advanced techniques. Provides insights from one of the world's leading pitching coaches.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/pbpr6o/take
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Time
3 hours
Via
Coursera
Institution
MathWorks
Instructors
Brandon Armstrong
Matt Kata
Good to know
Ideal for baseball fans seeking a deeper understanding of the sport through data analysis
Introduces MATLAB, a widely used software in scientific and engineering fields, including MLB
Hands-on project with access to comprehensive historical baseball statistics
Engaging real-world context that connects data analysis to sports
Teaches essential data analysis techniques using baseball as a case study
Instructor Matt Kata brings experience as a Major League Baseball player
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