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
What's included
- Lifetime accessEvery module and lesson, yours to keep and revisit, forever.
- 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.
A practice world built from this course
The lessons teach the method. The practice world is where you use it, generated from this course's own code, data and recordings.
Interactive practice worlds built from each course's own code, data and recordings. Every quantity computed live from the source data, every instructor quotation verified against the recording, and no exercise published unless its reference solution runs and passes its own tests.
Your instructor
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 this too advanced, or too basic, for me?
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. If the "not for you" list above reads like you, start with the courses on /browse; if the outcome at the top reads like something you could use next week, it is pitched right.
What exactly do I get, and for how long?
20 sections · 56 lessons. Every lesson, the project files and code, and all future updates. Lifetime access: it is yours to keep.
What if it is not for me?
Twenty minutes on a call before you buy costs nothing, and it is the fastest way to tell. If you bought it and it is the wrong course for you, email michael@athlyticz.com and a person will answer.
Is it self-paced?
Yes. Start today and go at your own pace, with lifetime access to every lesson and all future updates.