Navin Chandradat

I’m a data analyst focused on building and validating datasets, applying statistical models, and supporting data-driven decision-making in fast-paced environments. I bring a strong foundation in predictive modelling across both sports and enterprise data.

In my projects, I’ve quantified performance impact using win probability and EPA from NFL play-by-play, and used regression and the Bradley-Terry model to identify meaningful predictors and quantify home-field advantage. I enjoy turning messy data into analysis-ready inputs and then communicating results clearly.

As a Data Collector at Pro Football Focus, I collect and validate player participation and alignment data from NFL and NCAA games, using All-22 film to improve accuracy over broadcast-level collection. I also collaborate cross-functionally to ensure data quality for downstream analysis and game preparation.

Earlier, I contributed weekly venture funding outputs by collecting and structuring 30–40 deals from unstructured sources and validating attributes through cross-referencing. I’ve also supported web-based course content and taught calculus, finance, and statistics as a teaching assistant—values that shaped how I approach accuracy, clarity, and repeatable workflows.