149 citations · 529 across the 35 of their papers we have counts for
39 papers
Inverse Bayesian Optimization: Learning Human Acquisition Functions in an Exploration vs Exploitation Search Task
Nathan Sandholtz, Yohsuke Miyamoto, Luke Bornn +1
This paper introduces a probabilistic framework to estimate parameters of an acquisition function given observed human behavior that can be modeled as a collection of sample paths…
A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessions
Javier Fernandez, Luke Bornn, Daniel Cervone
The expected possession value (EPV) of a soccer possession represents the likelihood of a team scoring or receiving the next goal at any time instance. By decomposing the EPV into…
SoccerMap: A Deep Learning Architecture for Visually-Interpretable Analysis in Soccer
Javier Fernández, Luke Bornn
We present a fully convolutional neural network architecture that is capable of estimating full probability surfaces of potential passes in soccer, derived from high-frequency spat…
Estimating locomotor demands during team play from broadcast-derived tracking data
Jacob Mortensen, Luke Bornn
The introduction of optical tracking data across sports has given rise to the ability to dissect athletic performance at a level unfathomable a decade ago. One specific area that h…
Measuring Spatial Allocative Efficiency in Basketball
Nathan Sandholtz, Jacob Mortensen, Luke Bornn
Every shot in basketball has an opportunity cost; one player's shot eliminates all potential opportunities from their teammates for that play. For this reason, player-shot efficien…
Home Sweet Home: Quantifying Home Court Advantages For NCAA Basketball Statistics
Matthew van Bommel, Luke Bornn, Peter Chow-White +1
Box score statistics are the baseline measures of performance for National Collegiate Athletic Association (NCAA) basketball. Between the 2011-2012 and 2015-2016 seasons, NCAA team…