A preventive model for hamstring injuries in professional soccer: Learning algorithms

Ayala, Francisco, López-Valenciano, Alejandro, Jose, Antonio, De Ste Croix, Mark B ORCID: 0000-0001-9911-4355, Vera-García, Francisco, García-Vaquero, Maria, Ruiz-Pérez, Iñaki and Myer, Gregory (2019) A preventive model for hamstring injuries in professional soccer: Learning algorithms. International Journal of Sports Medicine, 40 (5). pp. 344-353. ISSN 1439-3964

[img] Text (Peer reviewed version)
De Ste Croix (2018) 6383 A preventive model for hamstring injuries in professional soccer.pdf - Accepted Version
Restricted to Repository staff only until 13 March 2020. (Publisher Embargo).
Available under License All Rights Reserved.

Download (897kB)
[img] Text (Supplemental Digital Content 1)
SDC 1.pdf - Accepted Version
Restricted to Repository staff only until 13 March 2020. (Publisher Embargo).
Available under License All Rights Reserved.

Download (102kB)
[img] Text (Supplemental Digital Content 2)
SDC 2.pdf - Accepted Version
Restricted to Repository staff only until 13 March 2020. (Publisher Embargo).
Available under License All Rights Reserved.

Download (163kB)
[img] Text (Supplemental Digital Content 3)
SDC 3.pdf - Accepted Version
Restricted to Repository staff only until 13 March 2020. (Publisher Embargo).
Available under License All Rights Reserved.

Download (152kB)
[img] Text (Supplemental Digital Content 4)
SDC 4.pdf - Accepted Version
Restricted to Repository staff only until 13 March 2020. (Publisher Embargo).
Available under License All Rights Reserved.

Download (331kB)
[img] Text (Supplemental Digital Content 5)
SDC 5.pdf - Accepted Version
Restricted to Repository staff only until 13 March 2020. (Publisher Embargo).
Available under License All Rights Reserved.

Download (338kB)
[img] Text (Supplemental Digital Content 6)
SDC 6.pdf - Accepted Version
Restricted to Repository staff only until 13 March 2020. (Publisher Embargo).
Available under License All Rights Reserved.

Download (239kB)
[img] Text (Supplemental Digital Content 7)
SDC 7.pdf - Accepted Version
Restricted to Repository staff only until 13 March 2020. (Publisher Embargo).
Available under License All Rights Reserved.

Download (179kB)
[img] Text (Supplemental Digital Content 8)
SDC 8.pdf - Accepted Version
Restricted to Repository staff only until 13 March 2020. (Publisher Embargo).
Available under License All Rights Reserved.

Download (296kB)
[img] Image (Supplemental Digital Content 9)
SDC 9. First classifier.jpg - Accepted Version
Restricted to Repository staff only until 13 March 2020. (Publisher Embargo).
Available under License All Rights Reserved.

Download (669kB)
[img] Image (Supplemental Digital Content 10)
SDC 10. Second classifier.jpg - Accepted Version
Restricted to Repository staff only until 13 March 2020. (Publisher Embargo).
Available under License All Rights Reserved.

Download (618kB)
[img] Image (Supplemental Digital Content 11)
SDC 11. Third classifier.jpg - Accepted Version
Restricted to Repository staff only until 13 March 2020. (Publisher Embargo).
Available under License All Rights Reserved.

Download (679kB)
[img] Image (Supplemental Digital Content 12)
SDC 12. Fourth classifier.jpg - Accepted Version
Restricted to Repository staff only until 13 March 2020. (Publisher Embargo).
Available under License All Rights Reserved.

Download (655kB)
[img] Image (Supplemental Digital Content 13)
SDC 13. Fifth classifier.jpg - Accepted Version
Restricted to Repository staff only until 13 March 2020. (Publisher Embargo).
Available under License All Rights Reserved.

Download (605kB)
[img] Image (Supplemental Digital Content 14)
SDC 14. Sixth classifier.jpg - Accepted Version
Restricted to Repository staff only until 13 March 2020. (Publisher Embargo).
Available under License All Rights Reserved.

Download (607kB)
[img] Image (Supplemental Digital Content 15)
SDC 15. Seventh classifier.jpg - Accepted Version
Restricted to Repository staff only until 13 March 2020. (Publisher Embargo).
Available under License All Rights Reserved.

Download (661kB)
[img] Image (Supplemental Digital Content 16)
SDC 16. Eighth classifier.jpg - Accepted Version
Restricted to Repository staff only until 13 March 2020. (Publisher Embargo).
Available under License All Rights Reserved.

Download (622kB)
[img] Image (Supplemental Digital Content 17)
SDC 17. Ninth classifier.jpg - Accepted Version
Restricted to Repository staff only until 13 March 2020. (Publisher Embargo).
Available under License All Rights Reserved.

Download (675kB)
[img] Image (Supplemental Digital Content 18)
SDC 18. Tenth classifier.jpg - Accepted Version
Restricted to Repository staff only until 13 March 2020. (Publisher Embargo).
Available under License All Rights Reserved.

Download (622kB)

Abstract

Hamstring strain injury (HSI) is one of the most prevalent and severe injury in professional soccer. The purpose was to analyse and compare the predictive ability of a range of machine learning techniques to select the best performing injury risk factor model to identify professional soccer players at high risk of HSIs. A total of 96 male professional soccer players underwent a pre-season screening evaluation that included a large number of individual, psychological and neuromuscular measures. Injury surveillance was prospectively employed to capture all the HSI occurring in the 2013/2014 season. There were 18 HSIs. Injury distribution was 55.6% dominant leg and 44.4% non-dominant leg. The model generated by the SmooteBoostM1 technique with a cost-sensitive ADTree as the base classifier reported the best evaluation criteria (area under the receiver operating characteristic curve score=0.837, true positive rate=77.8%, true negative rate=83.8%) and hence was considered the best for predicting HSI. The prediction model showed moderate to high accuracy for identifying professional soccer players at risk of HSI during pre-season screenings. Therefore, the model developed might help coaches, physical trainers and medical practitioners in the decision-making process for injury prevention.

Item Type: Article
Article Type: Article
Uncontrolled Keywords: Injury Prevention; Injury Risk; Screening; Decision Making
Subjects: G Geography. Anthropology. Recreation > GV Recreation Leisure > GV557 Sports
G Geography. Anthropology. Recreation > GV Recreation Leisure > GV557 Sports > GV861 Ball games: Baseball, football, golf, etc.
R Medicine > RC Internal medicine > RC1200 Sports Medicine
Divisions: Schools and Research Institutes > School of Sport and Exercise
Research Priority Areas: Sport, Exercise, Health & Wellbeing
Depositing User: Kate Greenaway
Date Deposited: 10 Jan 2019 17:58
Last Modified: 17 May 2019 14:00
URI: http://eprints.glos.ac.uk/id/eprint/6383

University Staff: Request a correction | Repository Editors: Update this record

University Of Gloucestershire

Bookmark and Share

Find Us On Social Media:

Social Media Icons Facebook Twitter Google+ YouTube Pinterest Linkedin

Other University Web Sites

University of Gloucestershire, The Park, Cheltenham, Gloucestershire, GL50 2RH. Telephone +44 (0)844 8010001.