I’ve compiled a couple of projects that demonstrate my skills as a data scientist and programmer. Many of my statistics projects are sports-related, but the techniques that I use are applicable in many fields. The code for these projects can be found on my Github.

- I conducted a statistical study of teaser bets using 25 years of NFL data. By applying logistic regression, I identified condition under which teaser legs could yield positive expected returns. To read my analysis of the profitability of NFL teasers, click here.

- I wrote a follow-up article that proposes an original, market-neutral strategy for finding positive expected value teaser bets using arbitrage.

- I built a real-time win probability model trained on play-by-play data using XGBoost and neural nets to capture nonlinear behavior of game states. To learn more about how I created my NFL win probability model, click here (in progress). Use my model with the app below!