Sports Analytics Using R | Online Seminar

A Practical Introduction for Analysts, Coaches, and Researchers

This course introduces you to the fundamentals of sports analytics using R. We will focus primarily on creating effective data visualizations that lead to actionable insights. Designed for both beginners and those with some experience as analysts, the course focuses on practical skills for sourcing, cleaning, visualizing, and presenting sports data through interactive dashboards.

Throughout the course, we will work with real-world sports datasets to apply skills in a practical context. By transforming raw data into meaningful visualizations and interactive dashboards, you’ll be equipped to communicate insights clearly and effectively to diverse audiences. Whether presenting to coaches, performance analysts, or fans, the emphasis will be on tailoring visual outputs to ensure accessibility and impact, ultimately supporting data-driven decision-making and performance enhancement.

Starting April 28, this seminar will be presented as a 3-day synchronous, livestream workshop via Zoom. Each day will feature two lecture sessions with hands-on exercises, separated by a 1-hour break. Live attendance is recommended for the best experience. But if you can’t join in real time, recordings will be available within 24 hours and can be accessed for four weeks after the seminar.

Closed captioning is available for all live and recorded sessions. Captions can be translated to a variety of languages including Spanish, Korean, and Italian. For more information, click here.

ECTS Equivalent Points: 1

Computing

You should have the most recent versions of R and RStudio installed on your local machine. The course assumes very basic familiarity with coding in R.

If you’d like to take the course but are concerned that you don’t know enough R, working through this free one-hour video will get you up to speed. Or, for more resources, you can check out our page on learning R.

Who Should Register?

This workshop is ideal for sports analysts, coaches and performance staff, students and academic researchers in sports science, and anyone who is interested in turning sports data into actionable insights.

Outline

Module 1: Data cleaning and sourcing

- Importing data: CSV, Excel, APIs, for sports datasets
- Cleaning data: handling missing values, duplicates, and formatting issues
- Common errors in sports data: time formats, player IDs, inconsistent naming conventions
- Data types in sports analytics: match stats, player tracking, event logs
- Normalization techniques: per-90, per-minute, per-possession, z-scores, etc.

Module 2: Visualization techniques

- Basic plots in R: bar charts, heat maps, scatter plots, box plots, and line charts
- Using aes() or not: when to map aesthetics vs. hard-code values
- Faceting and wrapping: comparing players, teams, or seasons
- Adding interactivity: using plotly, ggiraph

Module 3: Building dashboards

- Quarto basics: markdown, code chunks, and rendering
- My first dashboard: layouts, embedding plots, and filtering data
- Tabs and sidebars: organizing content for usability
- Customizing colors and themes: branding, accessibility, and visual impact

Module 4: Performance optimization

- Using dashboards: how to use dashboards to inform tactical decisions
- Case study: recent data from Liverpool FC

Seminar Information

Tuesday, April 28 –
Thursday, April 30, 2026

Daily Schedule: All sessions are held live via Zoom. All times are ET (New York time).

9:00am-11:30pm (convert to your local time)
12:30pm-2:30pm

Payment Information

The fee of $995 includes all course materials.

PayPal and all major credit cards are accepted.

Our Tax ID number is 26-4576270.

Contact Information

+1 610-715-0115 [email protected]

Sports Analytics Using R: A Short Course

A 3-Day Livestream Seminar Taught by Phil Barter, Ph.D.