• Working with UC Davis D1 Women’s Soccer on applied performance and match analysis statistics

• Leveraging computer vision (YOLO) and CVAT based annotation workflows to extract insights from match footage

• Generating structured datasets and evaluating player movement and match events using Python to support performance analysis

• Built a machine-learning pipeline in Python to estimate real-time soccer match win probabilities, training models on historical match, team, and betting-odds data using pandas and scikit-learn

• Analyzed feature importance and model performance to identify key drivers of match outcomes, translating predictive insights into actionable betting and strategy metrics using data visualization and statistical evaluation.

Manage a quarterly budget allocating funds efficiently for repairs, improvements, and essential supplies. Coordinate with vendors, handle logistics, and ensure the living environment remains safe, clean, and functional.