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Diego User

@diegouser19

Applied mathematics graduate who compared machine-learning models to predict professional tennis performance.

Spain
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At Sevilla FC, I integrated sports and neuropsychological data in Python and analysed how performance indicators related to sports metrics over time. I also checked internal KPIs against external and official performance metrics.

For my applied mathematics thesis, graded 10/10 with Honours, I compared machine-learning models on historical ATP match data to predict the share of games won. Temporal validation showed that accumulated competitive-load features modestly improved prediction, with the gain holding across other algorithms and an alternative time window.

Experience

Work history, roles, and key accomplishments

SF

Sports Data Analysis Intern

Sevilla FC

Sep 2025 - Mar 2026 (6 months)

Integrated and prepared sports and neuropsychological data from different sources for analysis in Python. Analyzed relationships between performance indicators and sports metrics, and assessed the consistency of internal KPIs against external metrics.

Education

Degrees, certifications, and relevant coursework

Universidad Loyola Andalucía logoUA

Universidad Loyola Andalucía

Bachelor's Degree, Applied Mathematics

2021 - 2026

Grade: 10/10 with Honours

Bachelor's Degree in Applied Mathematics from Universidad Loyola Andalucía, Seville, from 2021 to 2026. Thesis on predicting professional tennis performance was graded 10/10 with Honours.

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