Algebra Foundations For Baseball Analytics
3 units · 15 lessons
Translate baseball planning questions into unit-safe expressions and equations.
Deadball Academy
STEM pathways in baseball analytics, physics, math, and Statcast literacy.
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Learning paths
Each path maps to the same lesson library—open lessons in context, or jump straight into a track from the library.
Geometry Foundations For Baseball Context
3 units · 15 lessons
Model field and flight geometry with coordinates, distances, and angles.
Trigonometry And Precalculus For Baseball Modeling
3 units · 15 lessons
Use trig and vector tools to decompose motion and orientation in baseball models.
Calculus I And II For Baseball Dynamics
3 units · 15 lessons
Compute and interpret derivatives and integrals for motion and accumulation questions.
Multivariable Calculus And Differential Equations
3 units · 15 lessons
Work with partial derivatives, gradients, and multivariable constraints in models.
Baseball Physics Foundations
6 units · 60 lessons
Derive and validate mechanics-based ball-flight models.
Statistical Modeling For Baseball
5 units · 42 lessons
Build, validate, and critique predictive/statistical models for baseball outcomes.
Data Analysis With Statcast
5 units · 45 lessons
Construct reproducible data workflows from event-level baseball data.
Environmental Science For Baseball Systems
3 units · 15 lessons
Explain atmospheric and environmental factors that alter ball flight and operations.
Biological Mechanics Of Baseball
3 units · 15 lessons
Explain how major body systems support baseball-specific demands without clinical diagnosis.
Communicating Sports Analytics Insights
6 units · 41 lessons
Translate technical findings into decision-ready narratives.
Why Deadball Academy
Deadball Academy teaches baseball analytics the way serious analysts work: explicit definitions, reproducible models, and defensible communication.
Self-study learners, student cohorts, and instructors who want one curriculum spine from algebra through Statcast literacy.
Measurement lineage: box scores to tracking data—same discipline of defining quantities before drawing conclusions.
Reproducibility: assumptions stated, limits named, and work that another analyst can re-run or audit.
Shared standards: aligned units, vocabulary, and checkpoints so classrooms and independent study stay on the same rails.