Training Sports Statistics

Sports Statistics

Statistics
Intermediate 150 minutes 5 lessons
Quantitative methods behind modern sports analytics: Pythagorean expectation, Elo ratings, regression to the mean, expected goals (xG), and advanced metrics like WAR and OPS+.

Learning Objectives

  • Apply Pythagorean expectation to project wins from scoring margins
  • Compute Elo and Bradley–Terry expected scores with home advantage
  • Separate talent from luck using shrinkage and reliability coefficients
  • Build single-shot logistic xG models and aggregate match probabilities
  • Construct and interpret advanced metrics (WAR, OPS+, RAPM)

Lessons

1
Pythagorean Expectation
30 min
2
Elo Ratings & Bradley–Terry
30 min
3
Regression to the Mean & Hot Hand
30 min
4
Expected Goals (xG) & Shot Quality
30 min
5
Advanced Metrics: WAR, OPS+
30 min

Quick Practice

Test your knowledge with a quick interactive challenge from this module.

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Key Concept Flashcards

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