Project case study
Football Statistics ML Model
A predictive analytics project using Python to study footballer statistics, engineer meaningful features and estimate goal-scoring performance.
What was the project?
This personal learning project examined whether historical footballer statistics could be used to predict goal-scoring performance. It demonstrates an end-to-end machine learning workflow rather than a single model experiment.
Problem and approach
The approach combined data preparation, feature engineering, regression and perceptron models, algorithm comparison and model optimisation. Pandas, NumPy, Matplotlib and Jupyter supported the analysis and communication of findings.
Delivered outcomes
- Compared regression and perceptron approaches.
- Engineered features from footballer statistics.
- Evaluated model performance on historical data.
- Documented leading performance indicators.
Skills demonstrated
Python data science, feature engineering, model evaluation, predictive analytics, visualisation and translating model output into practical insight.