56 citations · 139 across the 8 of their papers we have counts for
8 papers
Large-Scale In-Game Outcome Forecasting for Match, Team and Players in Football using an Axial Transformer Neural Network
Michael Horton, Patrick Lucey
Football (soccer) is a sport that is characterised by complex game play, where players perform a variety of actions, such as passes, shots, tackles, fouls, in order to score goals,…
You Cannot Do That Ben Stokes: Dynamically Predicting Shot Type in Cricket Using a Personalized Deep Neural Network
Will Gürpınar-Morgan, Daniel Dinsdale, Joe Gallagher +2
The ability to predict what shot a batsman will attempt given the type of ball and match situation is both one of the most challenging and strategically important tasks in cricket.…
Improved Structural Discovery and Representation Learning of Multi-Agent Data
Jennifer Hobbs, Matthew Holbrook, Nathan Frank +2
Central to all machine learning algorithms is data representation. For multi-agent systems, selecting a representation which adequately captures the interactions among agents is ch…
Rugby-Bot: Utilizing Multi-Task Learning & Fine-Grained Features for Rugby League Analysis
Matthew Holbrook, Jennifer Hobbs, Patrick Lucey
Sporting events are extremely complex and require a multitude of metrics to accurate describe the event. When making multiple predictions, one should make them from a single source…
Generating Multi-Agent Trajectories using Programmatic Weak Supervision
Eric Zhan, Stephan Zheng, Yisong Yue +2
We study the problem of training sequential generative models for capturing coordinated multi-agent trajectory behavior, such as offensive basketball gameplay. When modeling such s…
Fine-Grained Retrieval of Sports Plays using Tree-Based Alignment of Trajectories
Long Sha, Patrick Lucey, Stephan Zheng +3
We propose a novel method for effective retrieval of multi-agent spatiotemporal tracking data. Retrieval of spatiotemporal tracking data offers several unique challenges compared t…