activity
20162024
most citedThe Application of Machine Learning Techniques for Predicting Results in Team Sport: A Review

138 citations · 183 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2024★ 2 cited

TeamTrack: A Dataset for Multi-Sport Multi-Object Tracking in Full-pitch Videos

Atom Scott, Ikuma Uchida, Ning Ding +7

Multi-object tracking (MOT) is a critical and challenging task in computer vision, particularly in situations involving objects with similar appearances but diverse movements, as s…

cs.LG2024★ 1 cited

Machine Learning for Soccer Match Result Prediction

Rory Bunker, Calvin Yeung, Keisuke Fujii

Machine learning has become a common approach to predicting the outcomes of soccer matches, and the body of literature in this domain has grown substantially in the past decade and…

cs.MA2023★ 6 cited

Multi-agent statistical discriminative sub-trajectory mining and an application to NBA basketball

Rory Bunker, Vo Nguyen Le Duy, Yasuo Tabei +2

Improvements in tracking technology through optical and computer vision systems have enabled a greater understanding of the movement-based behaviour of multiple agents, including i…

cs.LG2023★ 4 cited

Evaluating Soccer Match Prediction Models: A Deep Learning Approach and Feature Optimization for Gradient-Boosted Trees

Calvin Yeung, Rory Bunker, Rikuhei Umemoto +1

Machine learning models have become increasingly popular for predicting the results of soccer matches, however, the lack of publicly-available benchmark datasets has made model eva…

stat.AP2020★ 9 cited

Performance Indicators Contributing To Success At The Group And Play-Off Stages Of The 2019 Rugby World Cup

Rory Bunker, Kirsten Spencer

Performance indicators that contributed to success at the group stage and play-off stages of the 2019 Rugby World Cup were analysed using publicly available data obtained from the…

cs.LG2020★ 15 cited

Supervised sequential pattern mining of event sequences in sport to identify important patterns of play: an application to rugby union

Rory Bunker, Keisuke Fujii, Hiroyuki Hanada +1

Given a set of sequences comprised of time-ordered events, sequential pattern mining is useful to identify frequent subsequences from different sequences or within the same sequenc…

cs.LG2019★ 138 cited

The Application of Machine Learning Techniques for Predicting Results in Team Sport: A Review

Rory Bunker, Teo Susnjak

Over the past two decades, Machine Learning (ML) techniques have been increasingly utilized for the purpose of predicting outcomes in sport. In this paper, we provide a review of s…

cs.LG2016★ 8 cited

Improving a Credit Scoring Model by Incorporating Bank Statement Derived Features

Rory P. Bunker, Wenjun Zhang, M. Asif Naeem

In this paper, we investigate the extent to which features derived from bank statements provided by loan applicants, and which are not declared on an application form, can enhance…