5 papers
NFL step-and-turn: A generative framework for evaluating player movement in American football
Quang Nguyen, Ronald Yurko
In sports analytics, player tracking data have driven significant advancements in the task of player evaluation. We present a novel generative framework for evaluating the observed…
A Bayesian circular mixed-effects model for explaining variability in directional movement in American football
Quang Nguyen, Ronald Yurko
Change of direction is a key element of player movement in American football, yet there remains a lack of objective approaches for in-game performance evaluation of this athletic t…
A multilevel model with heterogeneous variances for snap timing in the National Football League
Quang Nguyen, Ronald Yurko
Player tracking data have provided great opportunities to generate novel insights into understudied areas of American football, such as pre-snap motion. Using a Bayesian multilevel…
NFL Ghosts: A framework for evaluating defender positioning with conditional density estimation
Ronald Yurko, Quang Nguyen, Konstantinos Pelechrinis
Player attribution in American football remains an open problem due to the complex nature of twenty-two players interacting on the field, but the granularity of player tracking dat…
Fractional Tackles: Leveraging Player Tracking Data for Within-Play Tackling Evaluation in American Football
Quang Nguyen, Ruitong Jiang, Meg Ellingwood +1
Tackling is a fundamental defensive move in American football, with the main purpose of stopping the forward motion of the ball-carrier. However, current tackling metrics are manua…