Our approach
A position, not a brochure: why AthlyticZ exists, what we lean into, and what we refuse to skip.
AthlyticZ exists because the job changed faster than the way it was taught. The people who teach here hold front-office, research and production roles now, and they teach the job as it is done this season: the data as it arrives, the model that has to run on Tuesday, the app a coaching staff opens on a phone in the tunnel.
We teach production data science through sport. The sport is the hook. The skill is the point. Every session is built around a real question a working analyst gets asked, answered the way that analyst answers it at their desk, with the code on the screen and the reasoning out loud.
We lean in hard. Every session shows the tools a working analyst uses, used the way a working analyst uses them: an agent drafting the first pass of a pipeline, a model written in conversation and then read line by line, a Shiny app scaffolded in minutes and made production-grade over the hour. We teach the tools, and we teach the hands on the wheel.
Our view is plain. Analysts who put AI in the loop will do more and better work, and analysts who do not will fall behind. So the tools are not a module at the end. They are in the room from the first minute, and the sessions built around them, Kickoff to Production in Minutes, Ask the Box Score Anything and Build an AI Agent That Turns Cricket Commentary Into Data, are taught by people who ship this way every week.
An agent can write the model. You have to know when it is wrong. That is why the fundamentals stay: the hierarchical model that shrinks the wrong way, the chain that never mixed, the cross-validation that leaked the answer into the features. Each of those looks fine in the output and is wrong in the world.
The math is taught where it matters, at the point where it changes a decision, and skipped where it does not. You see a posterior drawn before you see it coded, and you are asked what the number means for the player, the lineup, the budget. MCMC in Practice, Hierarchical Modeling using PyMC in Baseball and Variational Inference in Sports carry that weight on purpose, and Becoming a BayeZian is the long form of the same idea.
The sessions come from the market. Each quarter we read what hiring managers in sport are asking for, in their postings and in the work they hand to a new analyst, and we build the next sessions from that reading. Aging curves in R, penalized regression on attendance, multiple imputation on injury data, a game-day pipeline that runs itself on GitHub Actions: each one started as a line in a posting or a question from a front office.
The postings we are reading now are on the jobs board, each mapped to the sessions and courses that answer it. The current line-up is the Sessions shelf: fifteen recordings from the 2026 run, each one bought once and kept.
Every session is taught by a practitioner in the role they hold now. Their roles are on the team page, with the sessions and courses each of them teaches. The 15 people on this roster, in the roles they hold today:
Joseph Barbier, Data Consultant @ Yellow Sunflower. Maddy Brown, PhD · Analyst @ Her Hoop Stats. Nic Crane, PhD · Consultant @ NC Data Labs. Michael Czahor, PhD · Principal Data Scientist, AI @ Broadata Communications. Jasmine Daly, Principal Consultant @ Daly Analytics. Chris Fonnesbeck, PhD · Biostatistics @ Vanderbilt University Medical Center. David Granjon, PhD. Deepansh Khurana, Innovation Engineer (L5) @ Appsilon. Veerle Eeftink-van Leemput, Director @ Hypebright B.V.. Stefan Linner, Founder & R Developer @ LinneRProgramming. Greg Matthews, PhD · Director, Center for Data Science and Consulting @ Loyola University Chicago. Patrick McFarlane, Director of Predictive Modeling @ Philadelphia Phillies. Paul Sabin, PhD · Co-Founder @ Sage Sports Group. Christoph Scheuch, PhD · Associate Researcher @ Humboldt-Universität zu Berlin. Scott Spencer, PhD · Lecturer, Applied Analytics @ Columbia University.
That is the position. The work speaks.
First name and email. One message when a session recording, a skill, a cheat sheet or a posting worth your time arrives here, and no other mail. Replies reach a person.