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Int J Sports Med. 2015 Jan;36(1):41-8. doi: 10.1055/s-0034-1384547. Epub 2014 Sep 26.

Individualisation of time-motion analysis: a method comparison and case report series.

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Medical and Sports Science Department, Southampton Football Club, Southampton, United Kingdom.
Department of Sport, Health and Exercise Science, The University of Hull, Kingston upon Hull, United Kingdom.
School of Science and Health, The University of Western Sydney, Penrith, Australia.


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.

[Indexed for MEDLINE]

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