Comparative analysis of data mining versus human intuition in the prediction of horse race outcomes

Dwyer, Sean (2024) Comparative analysis of data mining versus human intuition in the prediction of horse race outcomes. Masters thesis, Dublin, National College of Ireland.

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Abstract

Research into how machine learning models can be applied to predict the outcome of horse races. An investigation into the use of different data and learning model approaches to find the most effective and profitable strategies. Compare these against industry experts, and incorporate their knowledge to gain an edge.

Various regression and classification models were employed to predict the race outcome. Pitting the best prediction model against its human counterpart yielded higher profits for the machine learning models. In conclusion, these results show that machine learning is better at predicting horse race outcome than human experts. These results could be further improved and optimized over time as more data becomes available for reiterative model retraining.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Basilio, Jorge UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science G Geography. Anthropology. Recreation > GV Recreation Leisure > Games and Amusements > Gambling Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning G Geography. Anthropology. Recreation > GV Recreation Leisure > Sports
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	15 Aug 2025 18:09
Last Modified:	15 Aug 2025 18:09
URI:	https://norma.ncirl.ie/id/eprint/8557

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