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Sports Analytics: Using data to model athletic performance.
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Sports Analytics: Using data to model athletic performance.

This course is part of Sports Performance Analytics.

Course Cost

Free course

Intermediate

Skill Level

46 Hours

Self-paced lessons

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Sports Performance Analytics Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

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4.4

21,160 Enrolled

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English

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olive-leaves-logo

4.4

21,160 Enrolled

olive-leaves-logo

English

What you'll learn

  • Use Python to analyze and visualize sports performance data

  • Apply regression analysis to evaluate team and player statistics

  • Develop predictive models for sports outcomes

  • Create data representations and visualizations for different sports

  • Analyze salary impacts on team performance

  • Implement statistical methods to test sports phenomena like the hot hand effect

Skills you'll gain

Python Programming
Sports Analytics
Data Analysis
Regression Analysis
Statistical Modeling
Team Performance Analysis
Data Visualization
Baseball Analytics
Basketball Analytics
Cricket Analytics

This course includes:

6.2 Hours PreRecorded video

13 quizzes

Access on Mobile, Tablet, Desktop

FullTime access

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Share your certificate with prospective employers and your professional network on LinkedIn.

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Top companies offer this course to their employees

Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.

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There are 6 modules in this course

This comprehensive course introduces learners to sports analytics using Python, focusing on analyzing team performance across major sports leagues. The curriculum covers data representation techniques, regression analysis, and performance metrics, using real-world examples from MLB, NBA, NHL, EPL, and IPL. Students learn to extract meaningful insights from sports data, create analytical models, and develop practical skills in statistical analysis and data visualization, transforming them from consumers to producers of sports analytics.

Introduction to Sports Performance and Data

Module 1 · 9 Hours to complete

Introduction to Data Sources

Module 2 · 8 Hours to complete

Introduction to Sports Data and Plots in Python

Module 3 · 7 Hours to complete

Introduction to Sports Data and Regression Using Python

Module 4 · 7 Hours to complete

More on Regressions

Module 5 · 7 Hours to complete

Is There a Hot Hand in Basketball?

Module 6 · 8 Hours to complete

Fee Structure

Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Sports Performance Analytics

Reviews

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Faculties

These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.

Sports Analytics: Using data to model athletic performance.

Intermediate

Skill Level

46 Hours

Self-paced lessons

Course Cost

Free course

Completion

CERTIFICATE

Frequently asked Questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.