About Me

Being born in 2001 right outside of Boston, sports have always been a part of my life. I knew David Ortiz's name before I knew my own. But when I left home to study math and statistics at Concordia University in Montreal, sports analytics had not even crossed my mind. Towards the end of my weeder classes (multi-var/calc, lin. alg...), I was in need of hands-on work and started to independently develop a statistic to assess offensive versatility in basketball. That was the inception, and during that time I approached the coaches of the men's basketball team at Concordia offering my services doing advanced analytics for them. After talking with the coaches, we decided to track and analyze lineup, shot-clock relative shooting, post possessions, and player shot selection data. This has helped the team assess offensive flow, the effectiveness of defensive gameplans, and optimize lineup rotations.

Initially I watched film and filled my school notebooks with hand-written play-by-by data, which I would painstakingly enter into excel. It was neither sustainable nor effective. It took until my first full season working with the team, coinciding with the opportunity to take a full course on sports analytics, for this to change. I eagerly marched into my professor's office hours, notebooks in hand, and was met with a look that showed a mix of disgust and awe. I can't remember exactly, but I believe the words "impressively stupid" were used. That course was my formal introduction to Python, and with my new skills, experience with real world data, and some guidance from my professor I was able to design a data infrastructure that met the needs of the coaches, and saved me countless hours. I continued to work on projects outside of school to increase the scope of my analysis, and it paid off. In the two seasons since then, the Concordia men's basketball team has improved from a record of 7-9 in 2022-2023, to 12-4 and 14-2 in 2023-24 and 2024-25 respectively, along with back-to-back appearances in the RSEQ championship game.

My love of math never left, and as I finished up my degree I had the opportunity to pursue higher/graduate level courses in mathematical modelling, data science, and dynamical systems.

Because of my foundation in mathematics, I can understand the inner workings of the statistical methods used in data science and machine learning. Partnered with my writing skills, this gives me the ability to interpret and communicate results in an intuitive and actionable manner that cuts through the noise that usually surrounds analytics.

In my free time, I enjoy writing and reading, cooking for friends, philosophy, and nature. Anything that lets me exercise my creative muscles outside the confines of a spreadsheet.