Mining Trackman Golf Data
2015 (English)In: 2015 International Conference on Computational Science and Computational Intelligence (CSCI) / [ed] Hamid R. Arabnia, Leonidas Deligiannidis & Quoc-Nam Tran, Los Alamitos, CA: IEEE Computer Society, 2015, 380-385 p.Conference paper (Refereed)
Recently, innovative technology like Trackman has made it possible to generate data describing golf swings. In this application paper, we analyze Trackman data from 275 golfers using descriptive statistics and machine learning techniques. The overall goal is to find non-trivial and general patterns in the data that can be used to identify and explain what separates skilled golfers from poor. Experimental results show that random forest models, generated from Trackman data, were able to predict the handicap of a golfer, with a performance comparable to human experts. Based on interpretable predictive models, descriptive statistics and correlation analysis, the most distinguishing property of better golfers is their consistency. In addition, the analysis shows that better players have superior control of the club head at impact and generally hit the ball straighter. A very interesting finding is that better players also tend to swing flatter. Finally, an outright comparison between data describing the club head movement and ball flight data, indicates that a majority of golfers do not hit the ball solid enough for the basic golf theory to apply.
Place, publisher, year, edition, pages
Los Alamitos, CA: IEEE Computer Society, 2015. 380-385 p.
Research subject Natural sciences
IdentifiersURN: urn:nbn:se:his:diva-12251DOI: 10.1109/CSCI.2015.77ISI: 000380405100068ScopusID: 2-s2.0-84964425566ISBN: 978-1-4673-9795-7 OAI: oai:DiVA.org:his-12251DiVA: diva2:928208
2015 International Conference on Computational Science and Computational Intelligence (CSCI), Las Vegas, Nevada, USA, 7-9 December 2015
ProjectsTIKT 1- GOATS
Project funded by VGR, TIKT collaboration Univ. Skövde and Univ. Borås.2016-05-152016-05-152016-08-19Bibliographically approved