Predictive Models

Predictive models are everywhere in sports. They are simpler than they seem.

The idea is to learn patterns from past data and apply them to the future.

Features are the inputs. Team strength, recent form, home advantage, injuries.

The model learns which features matter and how much.

Training is the process of fitting the model to past results.

Validation tests the model on data it has not seen. That tells you if it generalizes.

Overfitting is the trap. A model that memorizes the past fails on the future.

Good models are simple and robust. They beat guessing more often than not.

Build one yourself. The process teaches you how the pros think.