Beginner
10 parts
Python Foundations for Sports Data
Zero to competent: install Python, learn pandas on real standings, and finish by building a league table from raw results.
11 free courses · 93 parts · ~11 hours of material
Courses
Every tutorial on this site belongs to exactly one course, in a deliberate order - foundations first, then the craft, then the sport you care about. Each course carries an annotated syllabus, a written capstone challenge, a five-question self-check, and a one-ZIP bundle of all its code and data.
Beginner to Intermediate
10 parts
Sports Data Visualization
Ten chart types, each built on real sports data, ending with the styling pass that makes a figure publishable.
Intermediate
12 parts
Statistics for Sports Data
The measurement toolkit: distributions, z-scores, percentiles, outliers, time series, Simpson's paradox — closing with what actually predicts winning.
Intermediate
10 parts
Randomness, Inference & Simulation
Monte Carlo seasons, bootstrap intervals, permutation tests, power, chi-square, Bayesian updating, regression to the mean — how to tell signal from luck.
Advanced
9 parts
Machine Learning from Scratch
Nine models and methods — gradient descent to decision trees — every one implemented in pure numpy on real NBA data.
Beginner
7 parts
Working with Real Sports APIs
Read API docs like a developer, then pull your first real data from MLB, the NBA, StatsBomb, nflverse, the NHL and ESPN.
Intermediate
7 parts
Baseball Analytics with Statcast
Exit velocity, pitch maps, spray charts, luck-hunting and Pythagorean wins — the richest free data in sports, put to work.
Intermediate
9 parts
Basketball Analytics with the NBA API
Ratings tables, shot charts, zone efficiency, the three-point revolution, rest and back-to-backs — and an Elo system you build yourself.
Intermediate
8 parts
Soccer Analytics with StatsBomb & xG
Pass maps, shot maps, heatmaps and pass networks from free pro event data — then a complete World Cup: scoring by stage and a Poisson scoreline model.
Intermediate
6 parts
NFL Analytics with nflverse
EPA built by hand, quarterback efficiency, play-calling tendencies, receiver value and the fourth-down decision.
Intermediate
5 parts
Hockey & Cross-League Projects
Four NHL builds — shots, leaders, form, and the PDO luck flag — then the capstone: measuring home advantage across five leagues at once.
Not sure where to begin? Start Here picks a first course for you. Wondering what data all of this runs on? It's documented, with sources and downloads, on the datasets page.