BreeZing Through the Tidyverse
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Self-paced course · Beginner

BreeZing Through the Tidyverse

Master employer-ready R on real NFL, NBA, and MLB data, starting from zero: data wrangling, visualization, and reproducible reporting.

20 modules  ·  56 lessons  ·  40+ code reviews  ·  15+ quizzes  ·  NFL Draft capstone
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Taught by Paul Sabin. Included with AthlyticZ Membership.

Paul Sabin, PhD
Paul Sabin, PhD
Co-Founder, Senior Fellow

Who this is for

  • Anyone starting with R, from zero. No prior programming needed, and it is ideal if you want job-ready analytics skills on real sports data.

Not for you if

  • You're already fluent in the tidyverse. This starts from fundamentals
  • You want Python. This is R
  • You want deep statistical theory. This is applied and hands-on

What you leave with

  • Fluent dplyr and tidyr for real-world data wrangling
  • Publication-quality ggplot2 visualizations
  • Reproducible reports and project workflows
  • A completed NFL Draft analysis capstone

The full curriculum

20 sections · 56 lessons. Every section is listed with its lesson count; click any section to see its lessons.
Expand all
01Course Introduction4 lessons
1.1Welcome and Course Overview
1.2Packages and Options
1.3Introducing Sports Datasets
1.4Basic R Code
02Data Exploration4 lessons
2.1Atomic Data Types
2.2Data Structures
2.3Reading in Data
2.4Piping & Data Summaries
03Basics3 lessons
3.1Assigning Values in R
3.2Calling Functions in R
3.3Math Operations & Sequences
04Coding Style & Tidy Workflow4 lessons
4.1Spaces & Indentation
4.2Pivot Longer
4.3Pivot Wider
4.4Nested Data
05Loops & Vectorization3 lessons
5.1For Loops
5.2While Loops
5.3Vectorization
Career payoffdplyr and ggplot2 fluency is the baseline on nearly every analytics job posting.
06Functions & Logic3 lessons
6.1If Statements
6.2Probability Functions
6.3Writing Functions
07Data Wrangling (Part 1)3 lessons
7.1Select
7.2Group By, Summarize, & Filter
7.3Mutate
08Data Wrangling (Part 2)3 lessons
8.1Tidyselect
8.2Across
8.3Missing Values
09RStudio Shortcuts1 lesson
9.1RStudio Shortcuts
10Data Visualization (Part 1)4 lessons
10.1Base R plots
10.2Intro to ggplot2
10.3Histograms
10.4Densities
Career payoffReproducible reporting is what separates a hire from a hobbyist in interviews.
11Data Visualization (Part 2)4 lessons
11.1Customizing Themes
11.2Colors, Palettes & Facets
11.3Team Logos & Colors
11.4Calibration Plots
12Factors1 lesson
12.1Intro to Factors
13Simulation (Part 1)2 lessons
13.1Setting up Simulation
13.2Intro to data.tables
14Simulation (Part 2)2 lessons
14.1Parallelization
14.2Rcpp Introduction
15Strings3 lessons
15.1Intro to Strings
15.2stringr
15.3Regular Expressions
Career payoffThe NFL Draft capstone is a portfolio piece you can show from day one.
16Dates/Times2 lessons
16.1Intro to Dates
16.2Intro to Lubridate
17Joins1 lesson
17.1Joining Data in R
18Purrr2 lessons
18.1Intro to Purrr
18.2Split Data Models
19Communication3 lessons
19.1Intro to Quarto
19.2Quarto with Word and PowerPoint
19.3Additional Resources
20Case Study: NFL Draft Analysis4 lessons
20.1NFL Draft Curves and Data Loading
20.2NFL Draft Pick Value Plots
20.3NFL Draft Quarto Report
20.4NFL Draft & Trades Finalized Report

What's included

  • Lifetime accessEvery module and lesson, yours to keep and revisit, forever.
  • Posit cloud workspaceA provisioned enterprise IDE and compute. Nothing to install.
  • Project files and codeEvery notebook, dataset, and finished build, to keep and adapt.
  • All future updatesNew lessons and refreshes as the tools move, at no extra cost.
  • Self-pacedStart today, go at your own pace, no cohort to wait for.
  • Included with MembershipOr get this course and the full catalog with Membership.

Your instructor

Paul Sabin, PhD
Paul Sabin, PhD
Co-Founder, Senior Fellow
Known for Co-Founder, Senior Fellow

Paul is a data science and analytics leader bringing quantitative rigor to sports ownership, consulting, and investment. He is co-founder of Sage Sports Group and a Senior Fellow at the Wharton Sports Analytics & Business Initiative, where he also lectures in statistics and data science. A PhD statistician, he was previously VP of Football Analytics at SumerSports, where he led roster construction optimization and grew the analytics department to 10+ staff. As a sports data scientist and analytics writer at ESPN, he built proprietary metrics including BPI, FPI, Strength of Record, the Allstate Playoff Predictor, the NBA Draft Model, and Real Plus-Minus across college football, the NFL, and the NBA, and led ESPN's soccer analytics work building fantasy projections and match forecasting models. His experience spans player tracking data, TV ratings modeling, and professional club engagements.

LinkedIn →

Questions

Is this included with Membership?

Yes. AthlyticZ Membership includes this and the entire course catalog, plus the live Masterclass. If you plan to take more than a couple of courses, Membership is the better math. Both figures are on their order pages.

Is it self-paced?

Yes. Start today and go at your own pace, with lifetime access to every lesson and all future updates.

Do I need to install anything?

No. You work on the provisioned Posit platform in the browser, on the same enterprise tools professional teams use.

Taking more than one course? Get everything.

Membership includes this course, the full course catalog of 645 lessons, and every live Masterclass. If you are taking more than a couple of courses it is the better math, and the figures are on the order pages.

Explore Membership

BreeZing Through the Tidyverse

Master employer-ready R on real NFL, NBA, and MLB data, starting from zero: data wrangling, visualization, and reproducible reporting.

Enroll now
BreeZing Through the Tidyverseself-paced, yours to keep
Enroll