Int J Sports Med 2015; 36(01): 41-48
DOI: 10.1055/s-0034-1384547
Training & Testing
© Georg Thieme Verlag KG Stuttgart · New York

Individualisation of Time-Motion Analysis: A Method Comparison and Case Report Series

F. Hunter
1   Medical and Sports Science Department, Southampton Football Club, Southampton, United Kingdom
2   Department of Sport, Health and Exercise Science, The University of Hull, Kingston upon Hull, United Kingdom
,
J. Bray
2   Department of Sport, Health and Exercise Science, The University of Hull, Kingston upon Hull, United Kingdom
,
C. Towlson
2   Department of Sport, Health and Exercise Science, The University of Hull, Kingston upon Hull, United Kingdom
,
M. Smith
3   School of Science and Health, The University of Western Sydney, Penrith, Australia
,
S. Barrett
2   Department of Sport, Health and Exercise Science, The University of Hull, Kingston upon Hull, United Kingdom
,
J. Madden
2   Department of Sport, Health and Exercise Science, The University of Hull, Kingston upon Hull, United Kingdom
4   Medicine, Science and Fitness Department, Middlesbrough Football Club, Middlesbrough, United Kingdom
,
G. Abt
2   Department of Sport, Health and Exercise Science, The University of Hull, Kingston upon Hull, United Kingdom
,
R. Lovell
3   School of Science and Health, The University of Western Sydney, Penrith, Australia
› Author Affiliations
Further Information

Publication History



accepted after revision 12 May 2014

Publication Date:
26 September 2014 (online)

Abstract

This study compared the intensity distribution of time-motion analysis data, when speed zones were categorized by different methods. 12 U18 players undertook a routine battery of laboratory- and field-based assessments to determine their running speed corresponding to the respiratory compensation threshold (RCT), maximal aerobic speed (MAS), maximal oxygen consumption (vV˙O2max) and maximal sprint speed (MSS). Players match-demands were tracked using 5 Hz GPS units in 22 fixtures (50 eligible match observations). The percentage of total distance covered running at high-speed (%HSR), very-high speed (%VHSR) and sprinting were determined using the following speed thresholds: 1) arbitrary; 2) individualised (IND) using RCT, vV˙O2max and MSS; 3) individualised via MAS per se; 4) individualised via MSS per se; and 5) individualised using MAS and MSS as measures of locomotor capacities (LOCO). Using MSS in isolation resulted in 61% and 39% of player's % HSR and % VHSR, respectively, being incorrectly interpreted, when compared to the IND technique. Estimating the RCT from fractional values of MAS resulted in erroneous interpretations of % HSR in 50% of cases. The present results suggest that practitioners and researchers should avoid using singular fitness characteristics to individualise the intensity distribution of time-motion analysis data. A combination of players’ anaerobic threshold, MAS, and MSS characteristics are recommended to individualise player-tracking data.

 
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