Publications and Preprints

2024

  • Alex Reinhart, David Brown, Ben Markey, Michael Laudenbach, Kachatad Pantusen, Ronald Yurko, and Gordon Weinberg. “Do LLMs write like humans? Variation in grammatical and rhetorical styles,” arXiv preprint, 2024. (preprint)

  • Ronald Yurko, Quang Nguyen, and Konstantinos Pelechrinis. “NFL Ghosts: A framework for evaluating defender positioning with conditional density estimation,” arXiv preprint, 2024. (preprint)

  • Adriana Gonzalez Sanchez, Sierra Martinez, Ronald Yurko, and Ryan Elmore. “Does Icing the Field Goal Kicker Work in the National Football League?”, CHANCE, 2024. (link)

  • Yujin Kim, Minwoo Jeong, In Gyeong Koh, Chanhee Kim, Hyeji Lee, Jae Hyun Kim, Ronald Yurko, Il Bin Kim, Jeongbin Park, Donna M Werling, Stephan J Sanders, and Joon-Yong. “CWAS-Plus: estimating category-wide association of rare noncoding variation from whole-genome sequencing data with cell-type-specific functional data,” Briefings in Bioinformatics, 2024. (link)

  • Quang Nguyen, Ruitong Jiang, Meg Ellingwood, and Ronald Yurko. “Fractional tackles: Leveraging player tracking data for within-play tackling evaluation in american football,” arXiv preprint, 2024. (preprint)

  • Ryan Brill, Ronald Yurko, and Abraham J Wyner. “Exploring the difficulty of estimating win probability: a simulation study,” arXiv preprint, 2024. (preprint)

  • Ryan Brill, Ronald Yurko, and Abraham J Wyner. “Analytics, have some humility: a statistical view of fourth-down decision making,” arXiv preprint, 2024. (preprint)

2023

  • Quang Nguyen, Ronald Yurko, and Gregory J Matthews. “Here Comes the STRAIN: Analyzing Defensive Pass Rush in American Football with Player Tracking Data,” The American Statistician, 2023. (link)

2021

  • Ronald Yurko, Kathryn Roeder, Bernie Devlin, and Max G’Sell. “An approach to gene-based testing accounting for dependence of tests among nearby genes,” Briefings in Bioinformatics, 2021. (link)

  • Ronald Yurko, Kathryn Roeder, Bernie Devlin, and Max G’Sell. “H-MAGMA, inheriting a shaky statistical foundation, yields excess false positives,” Annals of Human Genetics, 2021. (link, preprint)

  • Riccardo Fogliato, Natalia L Oliveira, and Ronald Yurko. “TRAP: a predictive framework forthe Assessment of Performance in Trail Running,” Journal of Quantitative Analysis in Sports, 2021. (link, preprint)

2020

  • Ronald Yurko, Francesca Matano, Lee F Richardson, Nicholas Granered, Taylor Pospisil, Konstantinos Pelechrinis, and Samuel L Ventura. “Going deep: models for continuous-time within-play valuation of game outcomes in american football with tracking data,” Journal of Quantitative Analysis in Sports, 2020. (link)

  • Ronald Yurko, Max G’Sell, Kathryn Roeder, and Bernie Devlin. “A selective inference approach for false discovery rate control using multiomics covariates yields insights into disease risk,” Proceedings of the National Academy of Sciences, 2020. (link)

  • Sarah Mallepalle, Ronald Yurko, Konstantinos Pelechrinis, and Samuel L Ventura. “Extracting NFL tracking data from images to evaluate quarterbacks and pass defenses,” Journal of Quantitative Analysis in Sports, 2020. (link), preprint

  • Rishav Dutta, Ronald Yurko, and Samuel L Ventura. “Unsupervised methods for identifying pass coverage among defensive backs with nfl player tracking data,” Journal of Quantitative Analysis in Sports, 2020. (link, preprint)

2019

  • Ronald Yurko, Samuel Ventura, and Maksim Horowitz. “nflWAR: a reproducible method for offensive player evaluation in football,” Journal of Quantitative Analysis in Sports, 2019. (link, extended edition)

  • Konstantinos Pelechrinis, Ronald Yurko, and Sam Ventura. “Reducing Concussions in the NFL: A Data-Driven Approach,” CHANCE, 2019. (link)