NEWMAC Score Predictor

Summary

A team project using historical NEWMAC soccer data to predict match outcomes for Clark Men's Soccer, comparing baseline, logistic regression, decision tree, and random forest models.

Problem

Translate soccer history into a data-driven forecast while comparing model accuracy across several machine-learning approaches.

Role

Contributed as an ML engineer on a Clark soccer team project connecting athletics, data science, and prediction.

Process

• Collected and structured conference match data.
• Trained multiple models and compared their performance.
• Presented final predictions where 0 represented loss, 1 draw, and 2 win.

Outcome

Built a predictive workflow that connected firsthand athletic context with statistical modeling.

Tools